Original Research

Readmission rates are used as metrics for care quality and reimbursement, with penalties applied to hospitals with higher than expected rates¹ and up to 30% of pediatric readmissions deemed potentially preventable.² There is a paucity of information on how to prevent pediatric readmissions,³ yet pediatric hospitals are tasked with implementing interventions for readmission reduction.

The Hospital to Home Outcomes (H2O) trial was a 2-arm, randomized controlled trial in which patients discharged from hospital medicine and neuroscience services at a single institution were randomized to receive a single home visit from a registered nurse (RN) within 96 hours of discharge.⁴ RNs completed a structured nurse visit designed specifically for the trial. Lists of “red flags” or warning signs associated with common diagnoses were provided to assist RNs in standardizing education about when to seek additional care. The hypothesis was that the postdischarge visits would result in lower reutilization rates (unplanned readmissions, emergency department [ED] visits, and urgent care visits).⁵

Unexpectedly, children randomized to receive the postdischarge nurse visit had higher rates of 30-day unplanned healthcare reutilization, with children randomly assigned to the intervention demonstrating higher odds of 30-day healthcare use (OR 1.33; 95% CI 1.003-1.76).⁴ We sought to understand perspectives on these unanticipated findings by obtaining input from relevant stakeholders. There were 2 goals for the qualitative analysis: first, to understand possible explanations of the increased reutilization finding; second, to elicit suggestions for improving the nurse visit intervention.

 

METHODS

We selected an in-depth qualitative approach, using interviews and focus groups to explore underlying explanations for the increase in 30-day unplanned healthcare reutilization among those randomized to receive the postdischarge nurse visit during the H2O trial.⁴ Input was sought from 4 stakeholder groups—parents, primary care physicians (PCPs), hospital medicine physicians, and home care RNs—in an effort to triangulate data sources and elicit rich and diverse opinions. Approval was obtained from the Institutional Review Board prior to conducting the study.

Recruitment
Parents

Because we conducted interviews approximately 1 year after the trial’s conclusion, we purposefully selected families who were enrolled in the latter portion of the H2O trial in order to enhance recall. Beginning with the last families in the study, we sequentially contacted families in reverse order. We contacted 10 families in each of 4 categories (intervention/reutilization, intervention/no reutilization, control/reutilization, control/no reutilization). A total of 3 attempts were made by telephone to contact each family. Participants received a grocery store gift card for participating in the study.

Primary Care Physicians

We conducted focus groups with a purposive sample of physicians recruited from 2 community practices and 1 hospital-­owned practice.

Hospital Medicine Physicians

We conducted focus groups with a purposive sample of physicians from our Division of Hospital Medicine. There was a varying level of knowledge of the original trial; however, none of the participants were collaborators in the trial.

Home Care RNs

We conducted focus groups with a subset of RNs who were involved with trial visits. All RNs were members of the pediatric home care division associated with the hospital with specific training in caring for patients at home.

Data Collection

The study team designed question guides for each stakeholder group (Appendix 1). While questions were tailored for specific stakeholders, all guides included the following topics: benefits and challenges of nurse visits, suggestions for improving the intervention in future trials, and reactions to the trial results (once presented to participants). Only the results of the intention-to-treat (ITT) analysis were shared with stakeholders because ITT is considered the gold standard for trial analysis and allows easy understanding of the results.

A single investigator (A.L.) conducted parental interviews by telephone. Focus groups for PCPs, hospital medicine physicians, and RN groups were held at practice locations in private conference rooms and were conducted by trained moderators (S.N.S., A.L., and H.T.C.). Moderators probed responses to the open-ended questions to delve deeply into issues. The question guides were modified in an iterative fashion to include new concepts raised during interviews or focus groups. All interviews and focus groups were recorded and transcribed verbatim with all identifiable information redacted.

Data Analysis

During multiple cycles of inductive thematic analysis,⁶ we examined, discussed, interpreted, and organized responses to the open-ended questions,^6,7 analyzing each stakeholder group separately. First, transcripts were shared with and reviewed by the entire multidisciplinary team (12 members) which included hospital medicine physicians, PCPs, home care nursing leaders, a nurse scientist, a parent representative, research coordinators, and a qualitative research methodologist. Second, team members convened to discuss overall concepts and ideas and created the preliminary coding frameworks. Third, a smaller subgroup (research coordinator [A.L]., hospital medicine physician [S.R.], parent representative [M.M.], and qualitative research methodologist [S.N.S.]), refined the unique coding framework for each stakeholder group and then independently applied codes to participant comments. This subgroup met regularly to reach consensus about the assigned codes and to further refine the codebooks. The codes were organized into major and minor themes based on recurring patterns in the data and the salience or emphasis given by participants. The subgroup’s work was reviewed and discussed on an ongoing basis by the entire multidisciplinary team. Triangulation of the data was achieved in multiple ways. The preliminary results were shared in several forums, and feedback was solicited and incorporated. Two of 4 members of the subgroup analytic team were not part of the trial planning or data collection, providing a potentially broader perspective. All coding decisions were maintained in an electronic database, and an audit trail was created to document codebook revisions.

 

RESULTS

A total of 33 parents participated in the interviews (intervention/readmit [8], intervention/no readmit [8], control/readmit [8], and control/no readmit [9]). Although we selected families from all 4 categories, we were not able to explore qualitative differences between these groups because of the relatively low numbers of participants. Parent data was very limited as interviews were brief and “control” parents had not received the intervention. Three focus groups were held with PCPs (7 participants in total), 2 focus groups were held with hospital medicine physicians (12 participants), and 2 focus groups were held with RNs (10 participants).

Goal 1: Explanation of Reutilization Rates

During interviews and focus groups, the results of the H2O trial were discussed, and stakeholders were asked to comment on potential explanations of the findings. 4 major themes and 5 minor themes emerged from analysis of the transcripts (summarized in Table 1).

Theme 1: Appropriateness of Patient Reutilization

Hospital medicine physicians and home care RNs questioned whether the reutilization events were clinically indicated. RNs wondered whether children who reutilized the ED were also readmitted to the hospital; many perceived that if the child was ill enough to be readmitted, then the ED revisit was warranted (Table 2). Parents commented on parental decision-making and changes in clinical status of the child leading to reutilization (Table 2).

Theme 2: Impact of Red Flags/Warning Sign Instructions on Family’s Reutilization Decisions

Hospital medicine physicians and RNs discussed the potential concern that the “red flags” lacked sufficient context for appropriate family decision making. They hypothesized that, as a result, parents might have returned to the ED rather than accessing other avenues of care such as their primary care office. For example, 1 participant noted that, if a fever recurred days after it had resolved, then perhaps that would require different action steps than if a child had a persistent fever. RNs also mentioned that the discussion of red flags may have made families “more diligent” (Table 2).

Theme 3: Hospital-Affiliated RNs “Directing Traffic” Back to Hospital

Both physician groups were concerned that, because the study was conducted by hospital-employed nurses, families might have been more likely to reaccess care at the hospital. Thus, the connection with the hospital was strengthened in the H2O model, potentially at the expense of the connection with PCPs. Physicians hypothesized that families might “still feel part of the medical system,” so families would return to the hospital if there was a problem. PCPs emphasized that there may have been straightforward situations that could have been handled appropriately in the outpatient office (Table 2).

Theme 4: Home Visit RNs Had a Low Threshold for Escalating Care

Parents and PCPs hypothesized that RNs are more conservative and, therefore, would have had a low threshold to refer back to the hospital if there were concerns in the home. One parent commented: “I guess, nurses are just by trade accustomed to erring on the side of caution and medical intervention instead of letting time take its course. … They’re more apt to say it’s better off to go to the hospital and have everything be fine” (Table 2).

 

Minor Themes

Participants also explained reutilization in ways that coalesced into 5 minor themes: (1) families receiving a visit might perceive that their child was sicker; (2) patients in the control group did not reutilize enough; (3) receiving more education on a child’s illness drives reutilization; (4) provider access issues; and (5) variability of RN experience may determine whether escalated care. Supportive quotations found in Appendix 2.

We directly asked parents if they would want a nurse home visit in the future after discussing the results of the study. Almost all of the parents in the intervention group and most of the parents in the control group were in favor of receiving a visit, even knowing that patients who had received a visit were more likely to reutilize care.

Goal 2: Suggestions for Improving Intervention Design

Three major themes and 3 minor themes were related to improving the design of the intervention (Table 1).

Theme 1: Need for Improved Postdischarge Communication

All stakeholder groups highlighted postdischarge communication as an area that could be improved. Parents were frustrated with regard to attempts to connect with inpatient physicians after discharge. PCPs suggested developing pathways for the RN to connect with the primary care office as opposed to the hospital. Hospital medicine physicians discussed a lack of consensus regarding patient ownership following discharge and were uncertain about what types of postdischarge symptoms PCPs would be comfortable managing. RNs described specific situations when they had difficulty contacting a physician to escalate care (Table 3).

Theme 2: Individualizing Home Visits—One Size Does Not Fit All

All stakeholder groups also encouraged “individualization” of home visits according to patient and family characteristics, diagnosis, and both timing and severity of illness. PCPs recommended visits only for certain diagnoses. Hospital medicine physicians voiced similar sentiments as the PCPs and added that worrisome family dynamics during a hospitalization, such as a lack of engagement with the medical team, might also warrant a visit. RNs suggested visits for those families with more concerns, for example, those with young children or children recovering from an acute respiratory illness (Table 3).

Theme 3: Providing Context for and Framing of Red Flags

Physicians and nurses suggested providing more context to “red flag” instructions and education. RNs emphasized that some families seemed to benefit from the opportunity to discuss their postdischarge concerns with a medical professional. Others appreciated concrete written instructions that spelled out how to respond in certain situations (Table 3).

Minor Themes

Three minor themes were revealed regarding intervention design improvement (Table 1): (1) streamlining the discharge process; (2) improving the definition of the scope and goal of intervention; and (3) extending inpatient team expertise post discharge. Supportive quotations can be found in Appendix 3.

DISCUSSION

When stakeholders were asked about why postdischarge RN visits led to increased postdischarge urgent healthcare visits, they questioned the appropriateness of the reutilization events, wondered about the lack of context for the warning signs that nurses provided families as part of the intervention, worried that families were encouraged to return to the hospital because of the ties of the trial to the hospital, and suggested that RNs had a low threshold to refer patients back to the hospital. When asked about how to design an improved nurse visit to better support families, stakeholders emphasized improving communication, individualizing the visit, and providing context around the red-flag discussion, enabling more nuanced instructions about how to respond to specific events.

 

A synthesis of themes suggests that potential drivers for increased utilization rates may lie in the design and goals of the initial project. The intervention was designed to support families and enhance education after discharge, with components derived from pretrial focus groups with families after a hospital discharge.⁸ The intervention was not designed to divert patients from the ED nor did it enhance access to the PCP. A second trial of the intervention adapted to a phone call also failed to decrease reutilization rates.⁹ Both physician stakeholder groups perceived that the intervention directed traffic back to the hospital because of the intervention design. Coupled with the perception that the red flags may have changed a family’s threshold for seeking care and/or that an RN may be more apt to refer back to care, this failure to push utilization to the primary care office may explain the unexpected trial results. Despite the stakeholders’ perception of enhanced connection back to the hospital as a result of the nurse visit, in analysis of visit referral patterns, a referral was made directly back to the ED in only 4 of the 651 trial visits (Tubbs-Cooley H, Riddle SR, Gold JM, et al.; under review. Pediatric clinical and social concerns identified by home visit nurses in the immediate postdischarge period 2020).

Both H2O trials demonstrated improved recall of red flags by parents who received the intervention, which may be important given the stakeholders’ perspectives that the red flags may not have been contextualized well enough. Yet neither trial demonstrated any differences in postdischarge coping or time to return to normal routine. In interviews with parents, despite the clearly stated results of increased reutilization, intervention parents endorsed a desire for a home visit in the future, raising the possibility that our outcome measures did not capture parents’ priorities adequately.

When asked to recommend design improvements of the intervention, 2 major themes (improvement in communication and individualization of visits) were discussed by all stakeholder groups, providing actionable information to modify or create new interventions. Focus groups with clinicians suggested that communication challenges may have influenced reutilization likelihood during the postdischarge period. RNs expressed uncertainty about who to call with problems or questions at the time of a home visit. This was compounded by difficulty reaching physicians. Both hospital medicine physicians and PCPs identified system challenges including questions of patient ownership, variable PCP practice communication preferences, and difficulty in identifying a partnered staff member (on either end of the inpatient-outpatient continuum) who was familiar with a specific patient. While the communication issues raised may reflect difficulties in our local healthcare system, there is broad evidence of postdischarge communication challenges. In adults, postdischarge communication failures between home health staff and physicians are associated with an increased risk of readmission.¹⁰ The real or perceived lack of communication between inpatient and outpatient providers can add to parental confusion post discharge.¹¹ Although there have been efforts to improve the reliability of communication across this gulf,^12,13 it is not clear whether changes to discharge communication could help to avoid pediatric reutilization events.¹⁴

The theme of individualization of the home nurse visit is consistent with evidence regarding the impact of focusing the intervention on patients with specific diagnoses or demographics. In adults, reduced reutilization associated with postdischarge home nurse visits has been described in specific populations such as patients with heart failure and chronic obstructive pulmonary disease.¹⁵ Impact of home nurse visits on patients within diagnosis-specific populations with certain demographics (such as advanced age) has also been described.¹⁶ In the pediatric population, readmission rates vary widely by diagnosis.¹⁷ A systematic review of interventions to reduce pediatric readmissions found increased impact of discharge interventions in specific populations (asthma, oncology, and NICU).³

Next steps may lie in interventions in targeted populations that function as part of a care continuum bridging the patient from the inpatient to the outpatient setting. A home nurse visit as part of this discharge structure may prove to have more impact on reducing reutilization. One population which accounts for a large proportion of readmissions and where there has been recent focus on discharge transition of care has been children with medical complexity.¹⁸ This group was largely excluded from the H2O trial. Postdischarge home nurse visits in this population have been found to be feasible and address many questions and problems, but the effect on readmission is less clear.¹⁹ Family priorities and preferences related to preparation for discharge, including family engagement, respect for discharge readiness, and goal of returning to normal routines, may be areas on which to focus with future interventions in this population.²⁰ In summary, although widespread postdischarge interventions (home nurse visit⁴ and nurse telephone call⁹) have not been found to be effective, targeting interventions to specific populations by diagnosis or demographic factors may prove to be more effective in reducing pediatric reutilization.

There were several strengths to this study. This qualitative approach allowed us to elucidate potential explanations for the H2O trial results from multiple perspectives. The multidisciplinary composition of our analytic team and the use of an iterative process sparked diverse contributions in a dynamic, ongoing discussion and interpretation of our data.

This study should be considered in the context of several limitations. For families and RNs, there was a time lag between participation in the trial and participation in the qualitative study call or focus group which could lead to difficulty recalling details. Only families who received the intervention could give opinions on their experience of the nurse visit, while families in the control group were asked to hypothesize. Focus groups with hospital medicine physicians and PCPs were purposive samples, and complete demographic information of participants was not collected.

 

CONCLUSION

Key stakeholders reflecting on a postdischarge RN visit trial suggested multiple potential explanations for the unexpected increase in reutilization in children randomized to the intervention. Certain participants questioned whether all reutilization events were appropriate or necessary. Others expressed concerns that the H2O intervention lacked context and directed children back to the hospital instead of the PCP. Parents, PCPs, hospital medicine physicians, and RNs all suggested that future transition-focused interventions should enhance postdischarge communication, strengthen connection to the PCP, and be more effectively tailored to the needs of the individual patient and family.

Acknowledgments

Collaborators: H2O Trial Study Group: Joanne Bachus, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Monica L Borell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lenisa V Chang, MA, PhD; Patricia Crawford, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Sarah A Ferris, BA, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Judy A Heilman BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Jane C Khoury, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen Lawley, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lynne O’Donnell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Hadley S Sauers-Ford, MPH, Department of Pediatrics, UC Davis Health, Sacramento, California; Anita N Shah, DO, MPH, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lauren G Solan, MD, Med, University of Rochester, Rochester, New York; Heidi J Sucharew, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen P Sullivan, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Christine M White, MD, MAT, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio.

Readmission rates are used as metrics for care quality and reimbursement, with penalties applied to hospitals with higher than expected rates¹ and up to 30% of pediatric readmissions deemed potentially preventable.² There is a paucity of information on how to prevent pediatric readmissions,³ yet pediatric hospitals are tasked with implementing interventions for readmission reduction.

The Hospital to Home Outcomes (H2O) trial was a 2-arm, randomized controlled trial in which patients discharged from hospital medicine and neuroscience services at a single institution were randomized to receive a single home visit from a registered nurse (RN) within 96 hours of discharge.⁴ RNs completed a structured nurse visit designed specifically for the trial. Lists of “red flags” or warning signs associated with common diagnoses were provided to assist RNs in standardizing education about when to seek additional care. The hypothesis was that the postdischarge visits would result in lower reutilization rates (unplanned readmissions, emergency department [ED] visits, and urgent care visits).⁵

Unexpectedly, children randomized to receive the postdischarge nurse visit had higher rates of 30-day unplanned healthcare reutilization, with children randomly assigned to the intervention demonstrating higher odds of 30-day healthcare use (OR 1.33; 95% CI 1.003-1.76).⁴ We sought to understand perspectives on these unanticipated findings by obtaining input from relevant stakeholders. There were 2 goals for the qualitative analysis: first, to understand possible explanations of the increased reutilization finding; second, to elicit suggestions for improving the nurse visit intervention.

 

METHODS

We selected an in-depth qualitative approach, using interviews and focus groups to explore underlying explanations for the increase in 30-day unplanned healthcare reutilization among those randomized to receive the postdischarge nurse visit during the H2O trial.⁴ Input was sought from 4 stakeholder groups—parents, primary care physicians (PCPs), hospital medicine physicians, and home care RNs—in an effort to triangulate data sources and elicit rich and diverse opinions. Approval was obtained from the Institutional Review Board prior to conducting the study.

Recruitment
Parents

Because we conducted interviews approximately 1 year after the trial’s conclusion, we purposefully selected families who were enrolled in the latter portion of the H2O trial in order to enhance recall. Beginning with the last families in the study, we sequentially contacted families in reverse order. We contacted 10 families in each of 4 categories (intervention/reutilization, intervention/no reutilization, control/reutilization, control/no reutilization). A total of 3 attempts were made by telephone to contact each family. Participants received a grocery store gift card for participating in the study.

Primary Care Physicians

We conducted focus groups with a purposive sample of physicians recruited from 2 community practices and 1 hospital-­owned practice.

Hospital Medicine Physicians

We conducted focus groups with a purposive sample of physicians from our Division of Hospital Medicine. There was a varying level of knowledge of the original trial; however, none of the participants were collaborators in the trial.

Home Care RNs

We conducted focus groups with a subset of RNs who were involved with trial visits. All RNs were members of the pediatric home care division associated with the hospital with specific training in caring for patients at home.

Data Collection

The study team designed question guides for each stakeholder group (Appendix 1). While questions were tailored for specific stakeholders, all guides included the following topics: benefits and challenges of nurse visits, suggestions for improving the intervention in future trials, and reactions to the trial results (once presented to participants). Only the results of the intention-to-treat (ITT) analysis were shared with stakeholders because ITT is considered the gold standard for trial analysis and allows easy understanding of the results.

A single investigator (A.L.) conducted parental interviews by telephone. Focus groups for PCPs, hospital medicine physicians, and RN groups were held at practice locations in private conference rooms and were conducted by trained moderators (S.N.S., A.L., and H.T.C.). Moderators probed responses to the open-ended questions to delve deeply into issues. The question guides were modified in an iterative fashion to include new concepts raised during interviews or focus groups. All interviews and focus groups were recorded and transcribed verbatim with all identifiable information redacted.

Data Analysis

During multiple cycles of inductive thematic analysis,⁶ we examined, discussed, interpreted, and organized responses to the open-ended questions,^6,7 analyzing each stakeholder group separately. First, transcripts were shared with and reviewed by the entire multidisciplinary team (12 members) which included hospital medicine physicians, PCPs, home care nursing leaders, a nurse scientist, a parent representative, research coordinators, and a qualitative research methodologist. Second, team members convened to discuss overall concepts and ideas and created the preliminary coding frameworks. Third, a smaller subgroup (research coordinator [A.L]., hospital medicine physician [S.R.], parent representative [M.M.], and qualitative research methodologist [S.N.S.]), refined the unique coding framework for each stakeholder group and then independently applied codes to participant comments. This subgroup met regularly to reach consensus about the assigned codes and to further refine the codebooks. The codes were organized into major and minor themes based on recurring patterns in the data and the salience or emphasis given by participants. The subgroup’s work was reviewed and discussed on an ongoing basis by the entire multidisciplinary team. Triangulation of the data was achieved in multiple ways. The preliminary results were shared in several forums, and feedback was solicited and incorporated. Two of 4 members of the subgroup analytic team were not part of the trial planning or data collection, providing a potentially broader perspective. All coding decisions were maintained in an electronic database, and an audit trail was created to document codebook revisions.

 

RESULTS

A total of 33 parents participated in the interviews (intervention/readmit [8], intervention/no readmit [8], control/readmit [8], and control/no readmit [9]). Although we selected families from all 4 categories, we were not able to explore qualitative differences between these groups because of the relatively low numbers of participants. Parent data was very limited as interviews were brief and “control” parents had not received the intervention. Three focus groups were held with PCPs (7 participants in total), 2 focus groups were held with hospital medicine physicians (12 participants), and 2 focus groups were held with RNs (10 participants).

Goal 1: Explanation of Reutilization Rates

During interviews and focus groups, the results of the H2O trial were discussed, and stakeholders were asked to comment on potential explanations of the findings. 4 major themes and 5 minor themes emerged from analysis of the transcripts (summarized in Table 1).

Theme 1: Appropriateness of Patient Reutilization

Hospital medicine physicians and home care RNs questioned whether the reutilization events were clinically indicated. RNs wondered whether children who reutilized the ED were also readmitted to the hospital; many perceived that if the child was ill enough to be readmitted, then the ED revisit was warranted (Table 2). Parents commented on parental decision-making and changes in clinical status of the child leading to reutilization (Table 2).

Theme 2: Impact of Red Flags/Warning Sign Instructions on Family’s Reutilization Decisions

Hospital medicine physicians and RNs discussed the potential concern that the “red flags” lacked sufficient context for appropriate family decision making. They hypothesized that, as a result, parents might have returned to the ED rather than accessing other avenues of care such as their primary care office. For example, 1 participant noted that, if a fever recurred days after it had resolved, then perhaps that would require different action steps than if a child had a persistent fever. RNs also mentioned that the discussion of red flags may have made families “more diligent” (Table 2).

Theme 3: Hospital-Affiliated RNs “Directing Traffic” Back to Hospital

Both physician groups were concerned that, because the study was conducted by hospital-employed nurses, families might have been more likely to reaccess care at the hospital. Thus, the connection with the hospital was strengthened in the H2O model, potentially at the expense of the connection with PCPs. Physicians hypothesized that families might “still feel part of the medical system,” so families would return to the hospital if there was a problem. PCPs emphasized that there may have been straightforward situations that could have been handled appropriately in the outpatient office (Table 2).

Theme 4: Home Visit RNs Had a Low Threshold for Escalating Care

Parents and PCPs hypothesized that RNs are more conservative and, therefore, would have had a low threshold to refer back to the hospital if there were concerns in the home. One parent commented: “I guess, nurses are just by trade accustomed to erring on the side of caution and medical intervention instead of letting time take its course. … They’re more apt to say it’s better off to go to the hospital and have everything be fine” (Table 2).

 

Minor Themes

Participants also explained reutilization in ways that coalesced into 5 minor themes: (1) families receiving a visit might perceive that their child was sicker; (2) patients in the control group did not reutilize enough; (3) receiving more education on a child’s illness drives reutilization; (4) provider access issues; and (5) variability of RN experience may determine whether escalated care. Supportive quotations found in Appendix 2.

We directly asked parents if they would want a nurse home visit in the future after discussing the results of the study. Almost all of the parents in the intervention group and most of the parents in the control group were in favor of receiving a visit, even knowing that patients who had received a visit were more likely to reutilize care.

Goal 2: Suggestions for Improving Intervention Design

Three major themes and 3 minor themes were related to improving the design of the intervention (Table 1).

Theme 1: Need for Improved Postdischarge Communication

All stakeholder groups highlighted postdischarge communication as an area that could be improved. Parents were frustrated with regard to attempts to connect with inpatient physicians after discharge. PCPs suggested developing pathways for the RN to connect with the primary care office as opposed to the hospital. Hospital medicine physicians discussed a lack of consensus regarding patient ownership following discharge and were uncertain about what types of postdischarge symptoms PCPs would be comfortable managing. RNs described specific situations when they had difficulty contacting a physician to escalate care (Table 3).

Theme 2: Individualizing Home Visits—One Size Does Not Fit All

All stakeholder groups also encouraged “individualization” of home visits according to patient and family characteristics, diagnosis, and both timing and severity of illness. PCPs recommended visits only for certain diagnoses. Hospital medicine physicians voiced similar sentiments as the PCPs and added that worrisome family dynamics during a hospitalization, such as a lack of engagement with the medical team, might also warrant a visit. RNs suggested visits for those families with more concerns, for example, those with young children or children recovering from an acute respiratory illness (Table 3).

Theme 3: Providing Context for and Framing of Red Flags

Physicians and nurses suggested providing more context to “red flag” instructions and education. RNs emphasized that some families seemed to benefit from the opportunity to discuss their postdischarge concerns with a medical professional. Others appreciated concrete written instructions that spelled out how to respond in certain situations (Table 3).

Minor Themes

Three minor themes were revealed regarding intervention design improvement (Table 1): (1) streamlining the discharge process; (2) improving the definition of the scope and goal of intervention; and (3) extending inpatient team expertise post discharge. Supportive quotations can be found in Appendix 3.

DISCUSSION

When stakeholders were asked about why postdischarge RN visits led to increased postdischarge urgent healthcare visits, they questioned the appropriateness of the reutilization events, wondered about the lack of context for the warning signs that nurses provided families as part of the intervention, worried that families were encouraged to return to the hospital because of the ties of the trial to the hospital, and suggested that RNs had a low threshold to refer patients back to the hospital. When asked about how to design an improved nurse visit to better support families, stakeholders emphasized improving communication, individualizing the visit, and providing context around the red-flag discussion, enabling more nuanced instructions about how to respond to specific events.

 

A synthesis of themes suggests that potential drivers for increased utilization rates may lie in the design and goals of the initial project. The intervention was designed to support families and enhance education after discharge, with components derived from pretrial focus groups with families after a hospital discharge.⁸ The intervention was not designed to divert patients from the ED nor did it enhance access to the PCP. A second trial of the intervention adapted to a phone call also failed to decrease reutilization rates.⁹ Both physician stakeholder groups perceived that the intervention directed traffic back to the hospital because of the intervention design. Coupled with the perception that the red flags may have changed a family’s threshold for seeking care and/or that an RN may be more apt to refer back to care, this failure to push utilization to the primary care office may explain the unexpected trial results. Despite the stakeholders’ perception of enhanced connection back to the hospital as a result of the nurse visit, in analysis of visit referral patterns, a referral was made directly back to the ED in only 4 of the 651 trial visits (Tubbs-Cooley H, Riddle SR, Gold JM, et al.; under review. Pediatric clinical and social concerns identified by home visit nurses in the immediate postdischarge period 2020).

Both H2O trials demonstrated improved recall of red flags by parents who received the intervention, which may be important given the stakeholders’ perspectives that the red flags may not have been contextualized well enough. Yet neither trial demonstrated any differences in postdischarge coping or time to return to normal routine. In interviews with parents, despite the clearly stated results of increased reutilization, intervention parents endorsed a desire for a home visit in the future, raising the possibility that our outcome measures did not capture parents’ priorities adequately.

When asked to recommend design improvements of the intervention, 2 major themes (improvement in communication and individualization of visits) were discussed by all stakeholder groups, providing actionable information to modify or create new interventions. Focus groups with clinicians suggested that communication challenges may have influenced reutilization likelihood during the postdischarge period. RNs expressed uncertainty about who to call with problems or questions at the time of a home visit. This was compounded by difficulty reaching physicians. Both hospital medicine physicians and PCPs identified system challenges including questions of patient ownership, variable PCP practice communication preferences, and difficulty in identifying a partnered staff member (on either end of the inpatient-outpatient continuum) who was familiar with a specific patient. While the communication issues raised may reflect difficulties in our local healthcare system, there is broad evidence of postdischarge communication challenges. In adults, postdischarge communication failures between home health staff and physicians are associated with an increased risk of readmission.¹⁰ The real or perceived lack of communication between inpatient and outpatient providers can add to parental confusion post discharge.¹¹ Although there have been efforts to improve the reliability of communication across this gulf,^12,13 it is not clear whether changes to discharge communication could help to avoid pediatric reutilization events.¹⁴

The theme of individualization of the home nurse visit is consistent with evidence regarding the impact of focusing the intervention on patients with specific diagnoses or demographics. In adults, reduced reutilization associated with postdischarge home nurse visits has been described in specific populations such as patients with heart failure and chronic obstructive pulmonary disease.¹⁵ Impact of home nurse visits on patients within diagnosis-specific populations with certain demographics (such as advanced age) has also been described.¹⁶ In the pediatric population, readmission rates vary widely by diagnosis.¹⁷ A systematic review of interventions to reduce pediatric readmissions found increased impact of discharge interventions in specific populations (asthma, oncology, and NICU).³

Next steps may lie in interventions in targeted populations that function as part of a care continuum bridging the patient from the inpatient to the outpatient setting. A home nurse visit as part of this discharge structure may prove to have more impact on reducing reutilization. One population which accounts for a large proportion of readmissions and where there has been recent focus on discharge transition of care has been children with medical complexity.¹⁸ This group was largely excluded from the H2O trial. Postdischarge home nurse visits in this population have been found to be feasible and address many questions and problems, but the effect on readmission is less clear.¹⁹ Family priorities and preferences related to preparation for discharge, including family engagement, respect for discharge readiness, and goal of returning to normal routines, may be areas on which to focus with future interventions in this population.²⁰ In summary, although widespread postdischarge interventions (home nurse visit⁴ and nurse telephone call⁹) have not been found to be effective, targeting interventions to specific populations by diagnosis or demographic factors may prove to be more effective in reducing pediatric reutilization.

There were several strengths to this study. This qualitative approach allowed us to elucidate potential explanations for the H2O trial results from multiple perspectives. The multidisciplinary composition of our analytic team and the use of an iterative process sparked diverse contributions in a dynamic, ongoing discussion and interpretation of our data.

This study should be considered in the context of several limitations. For families and RNs, there was a time lag between participation in the trial and participation in the qualitative study call or focus group which could lead to difficulty recalling details. Only families who received the intervention could give opinions on their experience of the nurse visit, while families in the control group were asked to hypothesize. Focus groups with hospital medicine physicians and PCPs were purposive samples, and complete demographic information of participants was not collected.

 

CONCLUSION

Key stakeholders reflecting on a postdischarge RN visit trial suggested multiple potential explanations for the unexpected increase in reutilization in children randomized to the intervention. Certain participants questioned whether all reutilization events were appropriate or necessary. Others expressed concerns that the H2O intervention lacked context and directed children back to the hospital instead of the PCP. Parents, PCPs, hospital medicine physicians, and RNs all suggested that future transition-focused interventions should enhance postdischarge communication, strengthen connection to the PCP, and be more effectively tailored to the needs of the individual patient and family.

Acknowledgments

Collaborators: H2O Trial Study Group: Joanne Bachus, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Monica L Borell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lenisa V Chang, MA, PhD; Patricia Crawford, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Sarah A Ferris, BA, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Judy A Heilman BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Jane C Khoury, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen Lawley, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lynne O’Donnell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Hadley S Sauers-Ford, MPH, Department of Pediatrics, UC Davis Health, Sacramento, California; Anita N Shah, DO, MPH, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lauren G Solan, MD, Med, University of Rochester, Rochester, New York; Heidi J Sucharew, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen P Sullivan, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Christine M White, MD, MAT, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio.

Readmission rates are used as metrics for care quality and reimbursement, with penalties applied to hospitals with higher than expected rates¹ and up to 30% of pediatric readmissions deemed potentially preventable.² There is a paucity of information on how to prevent pediatric readmissions,³ yet pediatric hospitals are tasked with implementing interventions for readmission reduction.

The Hospital to Home Outcomes (H2O) trial was a 2-arm, randomized controlled trial in which patients discharged from hospital medicine and neuroscience services at a single institution were randomized to receive a single home visit from a registered nurse (RN) within 96 hours of discharge.⁴ RNs completed a structured nurse visit designed specifically for the trial. Lists of “red flags” or warning signs associated with common diagnoses were provided to assist RNs in standardizing education about when to seek additional care. The hypothesis was that the postdischarge visits would result in lower reutilization rates (unplanned readmissions, emergency department [ED] visits, and urgent care visits).⁵

Unexpectedly, children randomized to receive the postdischarge nurse visit had higher rates of 30-day unplanned healthcare reutilization, with children randomly assigned to the intervention demonstrating higher odds of 30-day healthcare use (OR 1.33; 95% CI 1.003-1.76).⁴ We sought to understand perspectives on these unanticipated findings by obtaining input from relevant stakeholders. There were 2 goals for the qualitative analysis: first, to understand possible explanations of the increased reutilization finding; second, to elicit suggestions for improving the nurse visit intervention.

 

METHODS

We selected an in-depth qualitative approach, using interviews and focus groups to explore underlying explanations for the increase in 30-day unplanned healthcare reutilization among those randomized to receive the postdischarge nurse visit during the H2O trial.⁴ Input was sought from 4 stakeholder groups—parents, primary care physicians (PCPs), hospital medicine physicians, and home care RNs—in an effort to triangulate data sources and elicit rich and diverse opinions. Approval was obtained from the Institutional Review Board prior to conducting the study.

Recruitment
Parents

Because we conducted interviews approximately 1 year after the trial’s conclusion, we purposefully selected families who were enrolled in the latter portion of the H2O trial in order to enhance recall. Beginning with the last families in the study, we sequentially contacted families in reverse order. We contacted 10 families in each of 4 categories (intervention/reutilization, intervention/no reutilization, control/reutilization, control/no reutilization). A total of 3 attempts were made by telephone to contact each family. Participants received a grocery store gift card for participating in the study.

Primary Care Physicians

We conducted focus groups with a purposive sample of physicians recruited from 2 community practices and 1 hospital-­owned practice.

Hospital Medicine Physicians

We conducted focus groups with a purposive sample of physicians from our Division of Hospital Medicine. There was a varying level of knowledge of the original trial; however, none of the participants were collaborators in the trial.

Home Care RNs

We conducted focus groups with a subset of RNs who were involved with trial visits. All RNs were members of the pediatric home care division associated with the hospital with specific training in caring for patients at home.

Data Collection

The study team designed question guides for each stakeholder group (Appendix 1). While questions were tailored for specific stakeholders, all guides included the following topics: benefits and challenges of nurse visits, suggestions for improving the intervention in future trials, and reactions to the trial results (once presented to participants). Only the results of the intention-to-treat (ITT) analysis were shared with stakeholders because ITT is considered the gold standard for trial analysis and allows easy understanding of the results.

A single investigator (A.L.) conducted parental interviews by telephone. Focus groups for PCPs, hospital medicine physicians, and RN groups were held at practice locations in private conference rooms and were conducted by trained moderators (S.N.S., A.L., and H.T.C.). Moderators probed responses to the open-ended questions to delve deeply into issues. The question guides were modified in an iterative fashion to include new concepts raised during interviews or focus groups. All interviews and focus groups were recorded and transcribed verbatim with all identifiable information redacted.

Data Analysis

During multiple cycles of inductive thematic analysis,⁶ we examined, discussed, interpreted, and organized responses to the open-ended questions,^6,7 analyzing each stakeholder group separately. First, transcripts were shared with and reviewed by the entire multidisciplinary team (12 members) which included hospital medicine physicians, PCPs, home care nursing leaders, a nurse scientist, a parent representative, research coordinators, and a qualitative research methodologist. Second, team members convened to discuss overall concepts and ideas and created the preliminary coding frameworks. Third, a smaller subgroup (research coordinator [A.L]., hospital medicine physician [S.R.], parent representative [M.M.], and qualitative research methodologist [S.N.S.]), refined the unique coding framework for each stakeholder group and then independently applied codes to participant comments. This subgroup met regularly to reach consensus about the assigned codes and to further refine the codebooks. The codes were organized into major and minor themes based on recurring patterns in the data and the salience or emphasis given by participants. The subgroup’s work was reviewed and discussed on an ongoing basis by the entire multidisciplinary team. Triangulation of the data was achieved in multiple ways. The preliminary results were shared in several forums, and feedback was solicited and incorporated. Two of 4 members of the subgroup analytic team were not part of the trial planning or data collection, providing a potentially broader perspective. All coding decisions were maintained in an electronic database, and an audit trail was created to document codebook revisions.

 

RESULTS

A total of 33 parents participated in the interviews (intervention/readmit [8], intervention/no readmit [8], control/readmit [8], and control/no readmit [9]). Although we selected families from all 4 categories, we were not able to explore qualitative differences between these groups because of the relatively low numbers of participants. Parent data was very limited as interviews were brief and “control” parents had not received the intervention. Three focus groups were held with PCPs (7 participants in total), 2 focus groups were held with hospital medicine physicians (12 participants), and 2 focus groups were held with RNs (10 participants).

Goal 1: Explanation of Reutilization Rates

During interviews and focus groups, the results of the H2O trial were discussed, and stakeholders were asked to comment on potential explanations of the findings. 4 major themes and 5 minor themes emerged from analysis of the transcripts (summarized in Table 1).

Theme 1: Appropriateness of Patient Reutilization

Hospital medicine physicians and home care RNs questioned whether the reutilization events were clinically indicated. RNs wondered whether children who reutilized the ED were also readmitted to the hospital; many perceived that if the child was ill enough to be readmitted, then the ED revisit was warranted (Table 2). Parents commented on parental decision-making and changes in clinical status of the child leading to reutilization (Table 2).

Theme 2: Impact of Red Flags/Warning Sign Instructions on Family’s Reutilization Decisions

Hospital medicine physicians and RNs discussed the potential concern that the “red flags” lacked sufficient context for appropriate family decision making. They hypothesized that, as a result, parents might have returned to the ED rather than accessing other avenues of care such as their primary care office. For example, 1 participant noted that, if a fever recurred days after it had resolved, then perhaps that would require different action steps than if a child had a persistent fever. RNs also mentioned that the discussion of red flags may have made families “more diligent” (Table 2).

Theme 3: Hospital-Affiliated RNs “Directing Traffic” Back to Hospital

Both physician groups were concerned that, because the study was conducted by hospital-employed nurses, families might have been more likely to reaccess care at the hospital. Thus, the connection with the hospital was strengthened in the H2O model, potentially at the expense of the connection with PCPs. Physicians hypothesized that families might “still feel part of the medical system,” so families would return to the hospital if there was a problem. PCPs emphasized that there may have been straightforward situations that could have been handled appropriately in the outpatient office (Table 2).

Theme 4: Home Visit RNs Had a Low Threshold for Escalating Care

Parents and PCPs hypothesized that RNs are more conservative and, therefore, would have had a low threshold to refer back to the hospital if there were concerns in the home. One parent commented: “I guess, nurses are just by trade accustomed to erring on the side of caution and medical intervention instead of letting time take its course. … They’re more apt to say it’s better off to go to the hospital and have everything be fine” (Table 2).

 

Minor Themes

Participants also explained reutilization in ways that coalesced into 5 minor themes: (1) families receiving a visit might perceive that their child was sicker; (2) patients in the control group did not reutilize enough; (3) receiving more education on a child’s illness drives reutilization; (4) provider access issues; and (5) variability of RN experience may determine whether escalated care. Supportive quotations found in Appendix 2.

We directly asked parents if they would want a nurse home visit in the future after discussing the results of the study. Almost all of the parents in the intervention group and most of the parents in the control group were in favor of receiving a visit, even knowing that patients who had received a visit were more likely to reutilize care.

Goal 2: Suggestions for Improving Intervention Design

Three major themes and 3 minor themes were related to improving the design of the intervention (Table 1).

Theme 1: Need for Improved Postdischarge Communication

All stakeholder groups highlighted postdischarge communication as an area that could be improved. Parents were frustrated with regard to attempts to connect with inpatient physicians after discharge. PCPs suggested developing pathways for the RN to connect with the primary care office as opposed to the hospital. Hospital medicine physicians discussed a lack of consensus regarding patient ownership following discharge and were uncertain about what types of postdischarge symptoms PCPs would be comfortable managing. RNs described specific situations when they had difficulty contacting a physician to escalate care (Table 3).

Theme 2: Individualizing Home Visits—One Size Does Not Fit All

All stakeholder groups also encouraged “individualization” of home visits according to patient and family characteristics, diagnosis, and both timing and severity of illness. PCPs recommended visits only for certain diagnoses. Hospital medicine physicians voiced similar sentiments as the PCPs and added that worrisome family dynamics during a hospitalization, such as a lack of engagement with the medical team, might also warrant a visit. RNs suggested visits for those families with more concerns, for example, those with young children or children recovering from an acute respiratory illness (Table 3).

Theme 3: Providing Context for and Framing of Red Flags

Physicians and nurses suggested providing more context to “red flag” instructions and education. RNs emphasized that some families seemed to benefit from the opportunity to discuss their postdischarge concerns with a medical professional. Others appreciated concrete written instructions that spelled out how to respond in certain situations (Table 3).

Minor Themes

Three minor themes were revealed regarding intervention design improvement (Table 1): (1) streamlining the discharge process; (2) improving the definition of the scope and goal of intervention; and (3) extending inpatient team expertise post discharge. Supportive quotations can be found in Appendix 3.

DISCUSSION

When stakeholders were asked about why postdischarge RN visits led to increased postdischarge urgent healthcare visits, they questioned the appropriateness of the reutilization events, wondered about the lack of context for the warning signs that nurses provided families as part of the intervention, worried that families were encouraged to return to the hospital because of the ties of the trial to the hospital, and suggested that RNs had a low threshold to refer patients back to the hospital. When asked about how to design an improved nurse visit to better support families, stakeholders emphasized improving communication, individualizing the visit, and providing context around the red-flag discussion, enabling more nuanced instructions about how to respond to specific events.

 

A synthesis of themes suggests that potential drivers for increased utilization rates may lie in the design and goals of the initial project. The intervention was designed to support families and enhance education after discharge, with components derived from pretrial focus groups with families after a hospital discharge.⁸ The intervention was not designed to divert patients from the ED nor did it enhance access to the PCP. A second trial of the intervention adapted to a phone call also failed to decrease reutilization rates.⁹ Both physician stakeholder groups perceived that the intervention directed traffic back to the hospital because of the intervention design. Coupled with the perception that the red flags may have changed a family’s threshold for seeking care and/or that an RN may be more apt to refer back to care, this failure to push utilization to the primary care office may explain the unexpected trial results. Despite the stakeholders’ perception of enhanced connection back to the hospital as a result of the nurse visit, in analysis of visit referral patterns, a referral was made directly back to the ED in only 4 of the 651 trial visits (Tubbs-Cooley H, Riddle SR, Gold JM, et al.; under review. Pediatric clinical and social concerns identified by home visit nurses in the immediate postdischarge period 2020).

Both H2O trials demonstrated improved recall of red flags by parents who received the intervention, which may be important given the stakeholders’ perspectives that the red flags may not have been contextualized well enough. Yet neither trial demonstrated any differences in postdischarge coping or time to return to normal routine. In interviews with parents, despite the clearly stated results of increased reutilization, intervention parents endorsed a desire for a home visit in the future, raising the possibility that our outcome measures did not capture parents’ priorities adequately.

When asked to recommend design improvements of the intervention, 2 major themes (improvement in communication and individualization of visits) were discussed by all stakeholder groups, providing actionable information to modify or create new interventions. Focus groups with clinicians suggested that communication challenges may have influenced reutilization likelihood during the postdischarge period. RNs expressed uncertainty about who to call with problems or questions at the time of a home visit. This was compounded by difficulty reaching physicians. Both hospital medicine physicians and PCPs identified system challenges including questions of patient ownership, variable PCP practice communication preferences, and difficulty in identifying a partnered staff member (on either end of the inpatient-outpatient continuum) who was familiar with a specific patient. While the communication issues raised may reflect difficulties in our local healthcare system, there is broad evidence of postdischarge communication challenges. In adults, postdischarge communication failures between home health staff and physicians are associated with an increased risk of readmission.¹⁰ The real or perceived lack of communication between inpatient and outpatient providers can add to parental confusion post discharge.¹¹ Although there have been efforts to improve the reliability of communication across this gulf,^12,13 it is not clear whether changes to discharge communication could help to avoid pediatric reutilization events.¹⁴

The theme of individualization of the home nurse visit is consistent with evidence regarding the impact of focusing the intervention on patients with specific diagnoses or demographics. In adults, reduced reutilization associated with postdischarge home nurse visits has been described in specific populations such as patients with heart failure and chronic obstructive pulmonary disease.¹⁵ Impact of home nurse visits on patients within diagnosis-specific populations with certain demographics (such as advanced age) has also been described.¹⁶ In the pediatric population, readmission rates vary widely by diagnosis.¹⁷ A systematic review of interventions to reduce pediatric readmissions found increased impact of discharge interventions in specific populations (asthma, oncology, and NICU).³

Next steps may lie in interventions in targeted populations that function as part of a care continuum bridging the patient from the inpatient to the outpatient setting. A home nurse visit as part of this discharge structure may prove to have more impact on reducing reutilization. One population which accounts for a large proportion of readmissions and where there has been recent focus on discharge transition of care has been children with medical complexity.¹⁸ This group was largely excluded from the H2O trial. Postdischarge home nurse visits in this population have been found to be feasible and address many questions and problems, but the effect on readmission is less clear.¹⁹ Family priorities and preferences related to preparation for discharge, including family engagement, respect for discharge readiness, and goal of returning to normal routines, may be areas on which to focus with future interventions in this population.²⁰ In summary, although widespread postdischarge interventions (home nurse visit⁴ and nurse telephone call⁹) have not been found to be effective, targeting interventions to specific populations by diagnosis or demographic factors may prove to be more effective in reducing pediatric reutilization.

There were several strengths to this study. This qualitative approach allowed us to elucidate potential explanations for the H2O trial results from multiple perspectives. The multidisciplinary composition of our analytic team and the use of an iterative process sparked diverse contributions in a dynamic, ongoing discussion and interpretation of our data.

This study should be considered in the context of several limitations. For families and RNs, there was a time lag between participation in the trial and participation in the qualitative study call or focus group which could lead to difficulty recalling details. Only families who received the intervention could give opinions on their experience of the nurse visit, while families in the control group were asked to hypothesize. Focus groups with hospital medicine physicians and PCPs were purposive samples, and complete demographic information of participants was not collected.

 

CONCLUSION

Key stakeholders reflecting on a postdischarge RN visit trial suggested multiple potential explanations for the unexpected increase in reutilization in children randomized to the intervention. Certain participants questioned whether all reutilization events were appropriate or necessary. Others expressed concerns that the H2O intervention lacked context and directed children back to the hospital instead of the PCP. Parents, PCPs, hospital medicine physicians, and RNs all suggested that future transition-focused interventions should enhance postdischarge communication, strengthen connection to the PCP, and be more effectively tailored to the needs of the individual patient and family.

Acknowledgments

Collaborators: H2O Trial Study Group: Joanne Bachus, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Monica L Borell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lenisa V Chang, MA, PhD; Patricia Crawford, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Sarah A Ferris, BA, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Judy A Heilman BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Jane C Khoury, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen Lawley, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lynne O’Donnell, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Hadley S Sauers-Ford, MPH, Department of Pediatrics, UC Davis Health, Sacramento, California; Anita N Shah, DO, MPH, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Lauren G Solan, MD, Med, University of Rochester, Rochester, New York; Heidi J Sucharew, PhD, Division of Biostatistics and Epidemiology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Karen P Sullivan, BSN, RN, Department of Patient Services, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Christine M White, MD, MAT, Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio.

Cataract surgery is one of the most common ambulatory procedures performed in the US.^1-3 With the aging of the US population, the number of Americans with cataracts is projected to increase from 24.4 million in 2010 to 38.7 million in 2030.⁴

Approximately 20% of all cataract patients have preoperative astigmatism of > 1.5 diopters (D), underscoring the importance of training residents in the placement of toric intraocular lenses (IOLs).⁵ However, the implantation of toric IOLs is more challenging than monofocal IOLs, requiring precise surgical alignment of the IOL.⁶ Successful toric IOL implantation also requires accurate calculation of the IOL cylinder power and target axis of alignment. It is unclear which toric IOL calculation formula offers the most accurate refractive predictions, and practitioners have designed strategies to apply different formulae depending on the biometric dimensions of the target eye.^7-9

Previous studies of resident-performed cataract surgery using toric IOLs^6,10-13 and studies that compare the performance of the Barrett and Holladay toric formulae have been limited by their small sample sizes (< 107 eyes).^7,14-16 Moreover, none of the studies that evaluate the comparative effectiveness of these biometric formulae were conducted at a teaching hospital.^7,14-16

Given the added complexity of toric IOL placement and variable surgical experience of residents as ophthalmologists-in-training, it is important to assess outcomes in teaching hospitals.¹³ The primary aims of this study were to assess the visual and refractive outcomes of cataract surgery using toric IOLs in a US Department of Veterans Affairs (VA) teaching hospital and to compare the relative accuracy of the Holladay 2 or Barrett toric biometric formulae in predicting postoperative refraction outcomes.

Methods

The Providence VA Medical Center (PVAMC) Institutional Review Board approved this study. This retrospective chart review included patients with cataract and corneal astigmatism who underwent cataract surgery using Acrysof toric IOLs, model SN6AT (Alcon) at the PVAMC teaching hospital between November 2013 and May 2018.

Only 1 eye was included from each study subject to avoid compounding of data with the use of bilateral eyes.¹⁷ In addition, bilateral cataract surgery was only performed on some patients at the PVAMC, so including both eyes from eligible patients would disproportionately weigh those patients’ outcomes. If both eyes had cataract surgery and their postoperative visual acuities were unequal, we chose the eye with the better postoperative visual acuity since refraction accuracy decreases with worsening best-corrected visual acuity (BCVA). If both eyes had cataract surgery and the postoperative visual acuity was the same, the first operated eye was chosen.^17,18

Exclusion criteria included worse than 20/40 BCVA, posterior capsular rupture, sulcus IOL, history of corneal disease, history of refractive surgery (laser-assisted in situ keratomileusis [LASIK]/photorefractive keratectomy [PRK]), axial length not measurable by the Lenstar optical biometer (Haag-Streit USA), or no postoperative refraction within 3 weeks to 4 months.^19,20

Patient age, race/ethnicity, gender, preoperative refraction, preoperative BCVA, postoperative refraction, postoperative BCVA, and IOL power were recorded from patient charts (Table 1). Preoperative and postoperative refractive values were converted to spherical equivalents. The preoperative biometry and most of the postoperative refractions were performed by experienced technicians certified by the Joint Commission on Allied Health Personnel in Ophthalmology. The main outcomes for the assessment of surgeries included the postoperative BCVA, postoperative spherical equivalent refraction, and postoperative residual refractive astigmatism.

Axial length (AL), preoperative anterior chamber depth (ACD), preoperative flat corneal front power (K1), preoperative steep corneal front power (K2), lens thickness, horizontal white-to-white (WTW) corneal diameter, and central corneal thickness (CCT) were recorded from the Lenstar biometric device. Predicted postoperative refractions for the Holladay 2 formula were calculated using Holladay IOL Consultant software (Holladay Consulting). Predicted postoperative refractions for the Barrett toric IOL formula were calculated using the online Barrett toric formula calculator.²¹ Since previous studies have shown that both the Holladay and Barrett formulae account for posterior corneal astigmatism, a comparison of refractive outcomes in eyes with against-the-rule astigmatism vs with-the-rule astigmatism was not performed.¹⁴ An estimated standardized value for surgically-induced astigmatism was entered into both formulae; 0.3 diopter (D) was chosen based on previously published averages.^22-24

A formula’s prediction error is defined as the predicted postoperative refraction minus the actual postoperative refraction. The mean absolute prediction error (MAE), defined as the mean of the absolute values of the prediction errors, and the median absolute prediction error (MedAE), defined as the median of the absolute values of the prediction errors, were used to assess the overall accuracy of each formula. Also, the percentages of eyes with postoperative refraction within ≥ 0.25 D, ≥ 0.50 D, and ≥ 1.0 D were calculated for both formulae. Two-tailed t tests were performed to compare the MAE between the formulae. Subgroup analyses were performed for short eyes (AL < 22 mm), medium length eyes (AL = 22-25 mm), and long eyes (AL > 25 mm). Statistical analysis was performed using STATA 11 (STATA Corp). The preoperative corneal astigmatism and postoperative refractive astigmatism of all the cases were compared in double-angle plots to assess how well the toric IOL neutralized the corneal astigmatism.

 

Results

Of 325 charts reviewed during the study period, 34 patients were excluded due to lack of postoperative refraction within the designated follow-up period, 5 for worse than 20/40 postoperative BCVA (4 had preexisting ocular disease), 2 for complications, and 1 for missing data. We included 283 eyes from 283 patients in the final study. Resident ophthalmologists were the primary surgeons in 87.6% (248/283) of the cases.

The median postoperative BCVA was 20/20, and 92% of patients had a postoperative BCVA of 20/25 or better. The prediction outcomes of the toric SN6AT IOLs are shown in Table 2. The Barrett toric formula had a lower MAE than the Holladay 2 formula, but this difference was not statistically significant. The Barrett toric formula also predicted a higher percentage of eyes with postoperative refraction within ≥ 0.25 D (53.2%), ≥ 0.5 D (77.3%), and ≥ 1.0 D (96.1%). For both formulae, > 95% of eyes had prediction errors that fell within 1.0 D.

While the Barrett formula demonstrated a lower MAE in all 3 AL groups, no statistically significant differences were found between the Barrett and Holladay formulae (P = .94, P = .49, and P = .08 for short, medium, and long eyes, respectively). Both formulae produced the lowest MAE in the long AL group: Barrett had a MAE of 0.221 D and Holladay 2 had one of 0.329 D. The Barrett formula produced its highest percentage of eyes with prediction errors falling within 0.25 D and 0.5 D in the long AL group. In comparison, both formulae had the highest MAEs in the short AL group (Barrett toric, 0.598 D; Holladay 2, 0.613 D) and produced the lowest percentage of eyes with prediction errors falling within ≥ 0.25 D and ≥ 0.5 D in the short AL group.

A cumulative histogram of the preoperative corneal and postoperative refractive astigmatism magnitude is shown in Figure 1. The same data are presented as double-angle plots in the Appendix, which shows that the centroid values for preoperative corneal astigmatism were greatlyreduced when compared with the postoperative refractive astigmatism (mean absolute value of 1.77 D ≥ 0.73 D to 0.5 D ≥ 0.50 D).

Preoperative corneal astigmatism and postoperative refractive astigmatism were compared since preoperative refractive astigmatism has noncorneal contributions, including lenticular astigmatism, and there is minimal expected change between preoperative and postoperative corneal astigmatism.¹⁴ For comparison, double-angle plots of postoperative refractive astigmatism prediction errors for the Holladay and Barrett formulae are shown in Figure 2.

    

Discussion

To our knowledge, this is the largest study of resident-performed cataract surgery using toric IOLs, the largest study that compared the performance of the Barrett toric and Holladay 2 formulae, and the first that compared these formulae in a teaching hospital setting. This study found no significant difference in the predictive accuracy of the Barrett and Holladay 2 biometric formulae for cataract surgery using toric IOLs. In addition, our refractive outcomes were consistent with the results of previous toric IOL outcome studies conducted in teaching and nonteaching hospital settings.^6,10-13

 

In 4 previous studies that compared the MAE of the Barrett and Holladay formulae for toric IOLs, the Barrett formula produced a lower MAE than the Holladay 2 formula.^7,14-16 However, this difference was significant in only 2 of the studies, which had sample sizes of only 68 and 107 eyes.^14,16 Furthermore, the Barrett toric formula produced the lower MAE for the entire AL range, though this was not statistically significant at our sample size. In addition, both formulae produced the lowest MAE in the long AL group and the highest MAE in the short AL group. The unique anatomy and high IOL power needed in short eyes may explain the challenges in attaining accurate IOL power predictions in this AL group.^19,25

Limitations

The sample size of this study may have prevented us from detecting statistically significant differences in the performance of the Barrett and Holladay formulae. However, our findings are consistent with studies that compare the accuracy of these formulae in teaching and nonteaching hospital settings. Second, the study was conducted at a VA hospital, and a high proportion of patients were male; thus, our findings may not be generalizable to patients who receive cataract surgery with toric IOLs in other settings.

Conclusions

In a single VA teaching hospital, the Barrett and Holladay 2 biometric formulae provide similar refractive predictions for cataract surgery using toric IOLs. Larger studies would be necessary to detect smaller differences in the relative performance of the biometric formulae.

Cataract surgery is one of the most common ambulatory procedures performed in the US.^1-3 With the aging of the US population, the number of Americans with cataracts is projected to increase from 24.4 million in 2010 to 38.7 million in 2030.⁴

Approximately 20% of all cataract patients have preoperative astigmatism of > 1.5 diopters (D), underscoring the importance of training residents in the placement of toric intraocular lenses (IOLs).⁵ However, the implantation of toric IOLs is more challenging than monofocal IOLs, requiring precise surgical alignment of the IOL.⁶ Successful toric IOL implantation also requires accurate calculation of the IOL cylinder power and target axis of alignment. It is unclear which toric IOL calculation formula offers the most accurate refractive predictions, and practitioners have designed strategies to apply different formulae depending on the biometric dimensions of the target eye.^7-9

Previous studies of resident-performed cataract surgery using toric IOLs^6,10-13 and studies that compare the performance of the Barrett and Holladay toric formulae have been limited by their small sample sizes (< 107 eyes).^7,14-16 Moreover, none of the studies that evaluate the comparative effectiveness of these biometric formulae were conducted at a teaching hospital.^7,14-16

Given the added complexity of toric IOL placement and variable surgical experience of residents as ophthalmologists-in-training, it is important to assess outcomes in teaching hospitals.¹³ The primary aims of this study were to assess the visual and refractive outcomes of cataract surgery using toric IOLs in a US Department of Veterans Affairs (VA) teaching hospital and to compare the relative accuracy of the Holladay 2 or Barrett toric biometric formulae in predicting postoperative refraction outcomes.

Methods

The Providence VA Medical Center (PVAMC) Institutional Review Board approved this study. This retrospective chart review included patients with cataract and corneal astigmatism who underwent cataract surgery using Acrysof toric IOLs, model SN6AT (Alcon) at the PVAMC teaching hospital between November 2013 and May 2018.

Only 1 eye was included from each study subject to avoid compounding of data with the use of bilateral eyes.¹⁷ In addition, bilateral cataract surgery was only performed on some patients at the PVAMC, so including both eyes from eligible patients would disproportionately weigh those patients’ outcomes. If both eyes had cataract surgery and their postoperative visual acuities were unequal, we chose the eye with the better postoperative visual acuity since refraction accuracy decreases with worsening best-corrected visual acuity (BCVA). If both eyes had cataract surgery and the postoperative visual acuity was the same, the first operated eye was chosen.^17,18

Exclusion criteria included worse than 20/40 BCVA, posterior capsular rupture, sulcus IOL, history of corneal disease, history of refractive surgery (laser-assisted in situ keratomileusis [LASIK]/photorefractive keratectomy [PRK]), axial length not measurable by the Lenstar optical biometer (Haag-Streit USA), or no postoperative refraction within 3 weeks to 4 months.^19,20

Patient age, race/ethnicity, gender, preoperative refraction, preoperative BCVA, postoperative refraction, postoperative BCVA, and IOL power were recorded from patient charts (Table 1). Preoperative and postoperative refractive values were converted to spherical equivalents. The preoperative biometry and most of the postoperative refractions were performed by experienced technicians certified by the Joint Commission on Allied Health Personnel in Ophthalmology. The main outcomes for the assessment of surgeries included the postoperative BCVA, postoperative spherical equivalent refraction, and postoperative residual refractive astigmatism.

Axial length (AL), preoperative anterior chamber depth (ACD), preoperative flat corneal front power (K1), preoperative steep corneal front power (K2), lens thickness, horizontal white-to-white (WTW) corneal diameter, and central corneal thickness (CCT) were recorded from the Lenstar biometric device. Predicted postoperative refractions for the Holladay 2 formula were calculated using Holladay IOL Consultant software (Holladay Consulting). Predicted postoperative refractions for the Barrett toric IOL formula were calculated using the online Barrett toric formula calculator.²¹ Since previous studies have shown that both the Holladay and Barrett formulae account for posterior corneal astigmatism, a comparison of refractive outcomes in eyes with against-the-rule astigmatism vs with-the-rule astigmatism was not performed.¹⁴ An estimated standardized value for surgically-induced astigmatism was entered into both formulae; 0.3 diopter (D) was chosen based on previously published averages.^22-24

A formula’s prediction error is defined as the predicted postoperative refraction minus the actual postoperative refraction. The mean absolute prediction error (MAE), defined as the mean of the absolute values of the prediction errors, and the median absolute prediction error (MedAE), defined as the median of the absolute values of the prediction errors, were used to assess the overall accuracy of each formula. Also, the percentages of eyes with postoperative refraction within ≥ 0.25 D, ≥ 0.50 D, and ≥ 1.0 D were calculated for both formulae. Two-tailed t tests were performed to compare the MAE between the formulae. Subgroup analyses were performed for short eyes (AL < 22 mm), medium length eyes (AL = 22-25 mm), and long eyes (AL > 25 mm). Statistical analysis was performed using STATA 11 (STATA Corp). The preoperative corneal astigmatism and postoperative refractive astigmatism of all the cases were compared in double-angle plots to assess how well the toric IOL neutralized the corneal astigmatism.

 

Results

Of 325 charts reviewed during the study period, 34 patients were excluded due to lack of postoperative refraction within the designated follow-up period, 5 for worse than 20/40 postoperative BCVA (4 had preexisting ocular disease), 2 for complications, and 1 for missing data. We included 283 eyes from 283 patients in the final study. Resident ophthalmologists were the primary surgeons in 87.6% (248/283) of the cases.

The median postoperative BCVA was 20/20, and 92% of patients had a postoperative BCVA of 20/25 or better. The prediction outcomes of the toric SN6AT IOLs are shown in Table 2. The Barrett toric formula had a lower MAE than the Holladay 2 formula, but this difference was not statistically significant. The Barrett toric formula also predicted a higher percentage of eyes with postoperative refraction within ≥ 0.25 D (53.2%), ≥ 0.5 D (77.3%), and ≥ 1.0 D (96.1%). For both formulae, > 95% of eyes had prediction errors that fell within 1.0 D.

While the Barrett formula demonstrated a lower MAE in all 3 AL groups, no statistically significant differences were found between the Barrett and Holladay formulae (P = .94, P = .49, and P = .08 for short, medium, and long eyes, respectively). Both formulae produced the lowest MAE in the long AL group: Barrett had a MAE of 0.221 D and Holladay 2 had one of 0.329 D. The Barrett formula produced its highest percentage of eyes with prediction errors falling within 0.25 D and 0.5 D in the long AL group. In comparison, both formulae had the highest MAEs in the short AL group (Barrett toric, 0.598 D; Holladay 2, 0.613 D) and produced the lowest percentage of eyes with prediction errors falling within ≥ 0.25 D and ≥ 0.5 D in the short AL group.

A cumulative histogram of the preoperative corneal and postoperative refractive astigmatism magnitude is shown in Figure 1. The same data are presented as double-angle plots in the Appendix, which shows that the centroid values for preoperative corneal astigmatism were greatlyreduced when compared with the postoperative refractive astigmatism (mean absolute value of 1.77 D ≥ 0.73 D to 0.5 D ≥ 0.50 D).

Preoperative corneal astigmatism and postoperative refractive astigmatism were compared since preoperative refractive astigmatism has noncorneal contributions, including lenticular astigmatism, and there is minimal expected change between preoperative and postoperative corneal astigmatism.¹⁴ For comparison, double-angle plots of postoperative refractive astigmatism prediction errors for the Holladay and Barrett formulae are shown in Figure 2.

    

Discussion

To our knowledge, this is the largest study of resident-performed cataract surgery using toric IOLs, the largest study that compared the performance of the Barrett toric and Holladay 2 formulae, and the first that compared these formulae in a teaching hospital setting. This study found no significant difference in the predictive accuracy of the Barrett and Holladay 2 biometric formulae for cataract surgery using toric IOLs. In addition, our refractive outcomes were consistent with the results of previous toric IOL outcome studies conducted in teaching and nonteaching hospital settings.^6,10-13

 

In 4 previous studies that compared the MAE of the Barrett and Holladay formulae for toric IOLs, the Barrett formula produced a lower MAE than the Holladay 2 formula.^7,14-16 However, this difference was significant in only 2 of the studies, which had sample sizes of only 68 and 107 eyes.^14,16 Furthermore, the Barrett toric formula produced the lower MAE for the entire AL range, though this was not statistically significant at our sample size. In addition, both formulae produced the lowest MAE in the long AL group and the highest MAE in the short AL group. The unique anatomy and high IOL power needed in short eyes may explain the challenges in attaining accurate IOL power predictions in this AL group.^19,25

Limitations

The sample size of this study may have prevented us from detecting statistically significant differences in the performance of the Barrett and Holladay formulae. However, our findings are consistent with studies that compare the accuracy of these formulae in teaching and nonteaching hospital settings. Second, the study was conducted at a VA hospital, and a high proportion of patients were male; thus, our findings may not be generalizable to patients who receive cataract surgery with toric IOLs in other settings.

Conclusions

In a single VA teaching hospital, the Barrett and Holladay 2 biometric formulae provide similar refractive predictions for cataract surgery using toric IOLs. Larger studies would be necessary to detect smaller differences in the relative performance of the biometric formulae.

Cataract surgery is one of the most common ambulatory procedures performed in the US.^1-3 With the aging of the US population, the number of Americans with cataracts is projected to increase from 24.4 million in 2010 to 38.7 million in 2030.⁴

Approximately 20% of all cataract patients have preoperative astigmatism of > 1.5 diopters (D), underscoring the importance of training residents in the placement of toric intraocular lenses (IOLs).⁵ However, the implantation of toric IOLs is more challenging than monofocal IOLs, requiring precise surgical alignment of the IOL.⁶ Successful toric IOL implantation also requires accurate calculation of the IOL cylinder power and target axis of alignment. It is unclear which toric IOL calculation formula offers the most accurate refractive predictions, and practitioners have designed strategies to apply different formulae depending on the biometric dimensions of the target eye.^7-9

Previous studies of resident-performed cataract surgery using toric IOLs^6,10-13 and studies that compare the performance of the Barrett and Holladay toric formulae have been limited by their small sample sizes (< 107 eyes).^7,14-16 Moreover, none of the studies that evaluate the comparative effectiveness of these biometric formulae were conducted at a teaching hospital.^7,14-16

Given the added complexity of toric IOL placement and variable surgical experience of residents as ophthalmologists-in-training, it is important to assess outcomes in teaching hospitals.¹³ The primary aims of this study were to assess the visual and refractive outcomes of cataract surgery using toric IOLs in a US Department of Veterans Affairs (VA) teaching hospital and to compare the relative accuracy of the Holladay 2 or Barrett toric biometric formulae in predicting postoperative refraction outcomes.

Methods

The Providence VA Medical Center (PVAMC) Institutional Review Board approved this study. This retrospective chart review included patients with cataract and corneal astigmatism who underwent cataract surgery using Acrysof toric IOLs, model SN6AT (Alcon) at the PVAMC teaching hospital between November 2013 and May 2018.

Only 1 eye was included from each study subject to avoid compounding of data with the use of bilateral eyes.¹⁷ In addition, bilateral cataract surgery was only performed on some patients at the PVAMC, so including both eyes from eligible patients would disproportionately weigh those patients’ outcomes. If both eyes had cataract surgery and their postoperative visual acuities were unequal, we chose the eye with the better postoperative visual acuity since refraction accuracy decreases with worsening best-corrected visual acuity (BCVA). If both eyes had cataract surgery and the postoperative visual acuity was the same, the first operated eye was chosen.^17,18

Exclusion criteria included worse than 20/40 BCVA, posterior capsular rupture, sulcus IOL, history of corneal disease, history of refractive surgery (laser-assisted in situ keratomileusis [LASIK]/photorefractive keratectomy [PRK]), axial length not measurable by the Lenstar optical biometer (Haag-Streit USA), or no postoperative refraction within 3 weeks to 4 months.^19,20

Patient age, race/ethnicity, gender, preoperative refraction, preoperative BCVA, postoperative refraction, postoperative BCVA, and IOL power were recorded from patient charts (Table 1). Preoperative and postoperative refractive values were converted to spherical equivalents. The preoperative biometry and most of the postoperative refractions were performed by experienced technicians certified by the Joint Commission on Allied Health Personnel in Ophthalmology. The main outcomes for the assessment of surgeries included the postoperative BCVA, postoperative spherical equivalent refraction, and postoperative residual refractive astigmatism.

Axial length (AL), preoperative anterior chamber depth (ACD), preoperative flat corneal front power (K1), preoperative steep corneal front power (K2), lens thickness, horizontal white-to-white (WTW) corneal diameter, and central corneal thickness (CCT) were recorded from the Lenstar biometric device. Predicted postoperative refractions for the Holladay 2 formula were calculated using Holladay IOL Consultant software (Holladay Consulting). Predicted postoperative refractions for the Barrett toric IOL formula were calculated using the online Barrett toric formula calculator.²¹ Since previous studies have shown that both the Holladay and Barrett formulae account for posterior corneal astigmatism, a comparison of refractive outcomes in eyes with against-the-rule astigmatism vs with-the-rule astigmatism was not performed.¹⁴ An estimated standardized value for surgically-induced astigmatism was entered into both formulae; 0.3 diopter (D) was chosen based on previously published averages.^22-24

A formula’s prediction error is defined as the predicted postoperative refraction minus the actual postoperative refraction. The mean absolute prediction error (MAE), defined as the mean of the absolute values of the prediction errors, and the median absolute prediction error (MedAE), defined as the median of the absolute values of the prediction errors, were used to assess the overall accuracy of each formula. Also, the percentages of eyes with postoperative refraction within ≥ 0.25 D, ≥ 0.50 D, and ≥ 1.0 D were calculated for both formulae. Two-tailed t tests were performed to compare the MAE between the formulae. Subgroup analyses were performed for short eyes (AL < 22 mm), medium length eyes (AL = 22-25 mm), and long eyes (AL > 25 mm). Statistical analysis was performed using STATA 11 (STATA Corp). The preoperative corneal astigmatism and postoperative refractive astigmatism of all the cases were compared in double-angle plots to assess how well the toric IOL neutralized the corneal astigmatism.

 

Results

Of 325 charts reviewed during the study period, 34 patients were excluded due to lack of postoperative refraction within the designated follow-up period, 5 for worse than 20/40 postoperative BCVA (4 had preexisting ocular disease), 2 for complications, and 1 for missing data. We included 283 eyes from 283 patients in the final study. Resident ophthalmologists were the primary surgeons in 87.6% (248/283) of the cases.

The median postoperative BCVA was 20/20, and 92% of patients had a postoperative BCVA of 20/25 or better. The prediction outcomes of the toric SN6AT IOLs are shown in Table 2. The Barrett toric formula had a lower MAE than the Holladay 2 formula, but this difference was not statistically significant. The Barrett toric formula also predicted a higher percentage of eyes with postoperative refraction within ≥ 0.25 D (53.2%), ≥ 0.5 D (77.3%), and ≥ 1.0 D (96.1%). For both formulae, > 95% of eyes had prediction errors that fell within 1.0 D.

While the Barrett formula demonstrated a lower MAE in all 3 AL groups, no statistically significant differences were found between the Barrett and Holladay formulae (P = .94, P = .49, and P = .08 for short, medium, and long eyes, respectively). Both formulae produced the lowest MAE in the long AL group: Barrett had a MAE of 0.221 D and Holladay 2 had one of 0.329 D. The Barrett formula produced its highest percentage of eyes with prediction errors falling within 0.25 D and 0.5 D in the long AL group. In comparison, both formulae had the highest MAEs in the short AL group (Barrett toric, 0.598 D; Holladay 2, 0.613 D) and produced the lowest percentage of eyes with prediction errors falling within ≥ 0.25 D and ≥ 0.5 D in the short AL group.

A cumulative histogram of the preoperative corneal and postoperative refractive astigmatism magnitude is shown in Figure 1. The same data are presented as double-angle plots in the Appendix, which shows that the centroid values for preoperative corneal astigmatism were greatlyreduced when compared with the postoperative refractive astigmatism (mean absolute value of 1.77 D ≥ 0.73 D to 0.5 D ≥ 0.50 D).

Preoperative corneal astigmatism and postoperative refractive astigmatism were compared since preoperative refractive astigmatism has noncorneal contributions, including lenticular astigmatism, and there is minimal expected change between preoperative and postoperative corneal astigmatism.¹⁴ For comparison, double-angle plots of postoperative refractive astigmatism prediction errors for the Holladay and Barrett formulae are shown in Figure 2.

    

Discussion

To our knowledge, this is the largest study of resident-performed cataract surgery using toric IOLs, the largest study that compared the performance of the Barrett toric and Holladay 2 formulae, and the first that compared these formulae in a teaching hospital setting. This study found no significant difference in the predictive accuracy of the Barrett and Holladay 2 biometric formulae for cataract surgery using toric IOLs. In addition, our refractive outcomes were consistent with the results of previous toric IOL outcome studies conducted in teaching and nonteaching hospital settings.^6,10-13

 

In 4 previous studies that compared the MAE of the Barrett and Holladay formulae for toric IOLs, the Barrett formula produced a lower MAE than the Holladay 2 formula.^7,14-16 However, this difference was significant in only 2 of the studies, which had sample sizes of only 68 and 107 eyes.^14,16 Furthermore, the Barrett toric formula produced the lower MAE for the entire AL range, though this was not statistically significant at our sample size. In addition, both formulae produced the lowest MAE in the long AL group and the highest MAE in the short AL group. The unique anatomy and high IOL power needed in short eyes may explain the challenges in attaining accurate IOL power predictions in this AL group.^19,25

Limitations

The sample size of this study may have prevented us from detecting statistically significant differences in the performance of the Barrett and Holladay formulae. However, our findings are consistent with studies that compare the accuracy of these formulae in teaching and nonteaching hospital settings. Second, the study was conducted at a VA hospital, and a high proportion of patients were male; thus, our findings may not be generalizable to patients who receive cataract surgery with toric IOLs in other settings.

Conclusions

In a single VA teaching hospital, the Barrett and Holladay 2 biometric formulae provide similar refractive predictions for cataract surgery using toric IOLs. Larger studies would be necessary to detect smaller differences in the relative performance of the biometric formulae.

The nature of combat and associated injuries in Operation Iraqi Freedom (OIF), Operation Enduring Freedom (OEF), Operation New Dawn (OND), and Afghanistan War is different from previous conflicts. Multiple protracted deployments with infrequent breaks after September 11, 2001 (9/11) have further compounded the problem.

Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are the signature wounds of recent wars, with a higher incidence among the veterans of OEF and OIF compared with those from previous conflicts.^1,2 More than 2.7 million who served in Iraq and Afghanistan suffer from PTSD.^3,4 Symptoms of PTSD may appear within the first 3 months after exposure to a traumatic event or after many months and, in some cases, after a delay of many years and continue for life.⁵ Although delayed onset of PTSD in the absence of prior symptoms is rare,^6,7 its incidence rises with increasing frequency of exposure to traumatic events^8,9 and over time.¹⁰

According to the Brain Injury Association of America, TBI is “an alteration in brain function, or other evidence of brain pathology, caused by an external force.”⁸ TBI is often associated with increased risk of PTSD, depression, and posttraumatic headache,^11-13 which may lead to broader cognitive, somatic, neurobiological, and psychosocial dysfunctions.^14-17 According to Veterans Health Administration (VHA) data, 201,435 veterans from all eras enrolled with the US Department of Veterans Affairs (VA) have a diagnosis associated with TBI and 56,695 OEF/OIF veterans have been evaluated for a TBI-related condition.² According to the Defense and Veterans Brain Injury Center (DVBIC), > 361,000 veterans have been diagnosed with TBI, with a peak of 32,000 cases in 2011.^1,18 Moreover, the reported incidence and prevalence of PTSD and TBI among US veterans are not consistent. The incidence of PTSD has been estimated at 15% to 20% in recent wars^3,19 compared with 10% to 30% in previous wars.^3,19,20

When PTSD or TBI is deemed “related” to military service, the veteran may receive a service-connected disability rating ranging from 0% (no life-interfering symptoms due to injury) to 100% (totally disabling injury). The percentage of service connection associated with an injury is a quantifiable measure of the debilitating effect of injury on the individual. A significant majority (94%) of those who seek mental health services and treatment at VHA clinics apply for PTSD-related disability benefits.²¹ The estimated cost related to PTSD/TBI service-connected pensions is $20.28 billion per year and approximately $514 billion over 50 years.²² The cost of VA and Social Security disability payments combined with health care costs and treatment of PTSD is estimated to exceed $1 trillion over the next 30 years.²²

The National Vietnam Veterans Readjustment Study (NVVRS) provided valuable information on prevalence rates of PTSD and other postwar psychological problems.²³ Meanwhile, there have been no recent large-scale studies to compare the demographics of veterans diagnosed with PTSD and TBI who served prior to and after 9/11. A better understanding of demographic changes is considered essential for designing and tailoring therapeutic interventions to manage the rising cost.²²

The present study focused on identifying changing trends in the demographics of veterans who served prior to and after 9/11 and who received a VA inpatient or outpatient diagnosis of PTSD and/or TBI. Specifically, this study addressed the changes in demographics of veterans with PTSD, TBI, or PTSD+TBI seen at the VHA clinics between December 1,1998 and May 31, 2014 (before and after September 11, 2001) for diagnosis, treatment and health care policy issues.

 

Methods

This study was approved by the Kansas City VA Medical Center Institutional Review Board. VHA data from the Corporate Data Warehouse (CDW) and the National Patient Care Database were extracted using the VA Informatics and Computing Infrastructure (VINCI) workspace. CDW uses a unique identifier to identify veterans across treatment episodes at more than 1,400 VHA centers organized under 21 Veterans Integrated Service Networks (VISNs). These sources of VA data are widely used for retrospective longitudinal studies.

Study Population

The study population consisted of 1,339,937 veterans with a VA inpatient/outpatient diagnosis of PTSD or TBI using International Statistical Classification of Diseases and Related Health Problems, Ninth Revision (ICD-9) codes between December 1, 1998 and May 31, 2014. Demographic (gender classification, race, ethnicity, marital status, age at date of data extraction, and date of death if indicated), service-connection disability rating, and geographic distribution within VISN data on each veteran were then extracted.

Veterans in the cohort were assigned to 1 of 4 US military services period groups. The pre-9/11 group included veterans who entered and left the military prior to September 11, 2001. This group mostly included veterans from World War II, Korean War, Vietnam War, and the first Gulf War (1990-1991). The post-9/11 group included veterans who first entered military services after September 11, 2001. The overlap group included veterans who entered military services prior to 9/11, remained in service and left after September 11, 2001. The reentered group included veterans who entered and left service prior to September 11, 2001, and then reentered military service after September 11, 2001 (Figure 1). Using ICD-9 codes, veterans also were placed into the following categories: PTSD alone (ICD-9 309.81 only), TBI alone (ICD-9 850.0-859.9, V15.52), and PTSD+TBI (any combination of ICD-9 codes from the other categories).

Statistical Analysis 

Descriptive statistics were applied using proportions and means. Relationships between variables were examined using χ² tests, t tests, analysis of variance, and nonparametric tests. All hypotheses were 2-sided at 95% CI. Results are presented as absolute numbers.

Results

PTSD only (n = 1,132,356, 85%) was the predominant diagnosis category followed by PTSD+TBI (n = 106,792, 8%) and TBI only (n = 100,789, 7%) (Figure 2). Most of the veterans in the study served pre-9/11 (77%), followed by post-9/11 (15%); 7% were in the overlap group, and 1% in the reentered group (Table 1). It is notable that the proportion of veterans diagnosed with PTSD decreased from pre-9/11 (88%) to post-9/11 (71%), overlap (77%), and reentered (74%) service periods. Increases were noted in those with PTSD+TBI diagnosis category from pre-9/11 (4%) to post-9/11 (23%), overlap (17%), and reentered (22%) service periods (Figure 3). In general, the relative distribution of diagnostic categories in all the service periods showed a similar trend, with the majority of veterans diagnosed with PTSD only. Across all service periods, significantly smaller proportions of veterans were diagnosed with TBI only (P < .001).

   

Distribution by Gender and Age

The cohort was 92% male (n = 1,239,295), but there was a marked increase in the percentage of nonmale veterans in post-9/11 groups. Study population ages ranged from 18 to 99 years based on date of birth to the date data were obtained; or date of birth to date of death, for those who were reported deceased at the time the data were obtained. The average (SD) ages for veterans in the pre-9/11 group were significantly older (66.3 [11.2] years) compared with the ages of veterans in the post-9/11 group (36.1 [8.7] years), the overlap group (41.4 [8.2] years), and the reentered group (46.9 [9.2] years), respectively.

 

Distribution by Race and Marital Status

The cohort identified as 65.7% white and 18.2% African American with much smaller percentages of Asians, American Indian/Alaska Natives (AI/AN) and Native Hawaiian/Pacific Islanders (Table 2). The relative proportion of AI/AN and Native Hawaiian/Pacific Islanders remained constant across all groups, whereas the number of Asians diagnosed with PTSD, TBI, or PTSD+TBI increased in the post-9/11 group. The number of African Americans diagnosed with PTSD, TBI, or both markedly increased in the overlap and reentered groups when compared with the pre-9/11 group, yet it went down in the post-9/11/group.

Half the cohort identified themselves as married (n = 675,145) (Table 3). A slightly larger proportion of those diagnosed with PTSD alone were married (51.7%), compared with those diagnosed with TBI only (40.3%), or PTSD+TBI (45.8%). Veterans in the post-9/11 group were less likely to identify as married (45.2%) compared with the pre-9/11 (51.2%), overlap (52.6%), or reentered (53.2%) groups. Divorce rates among pre-9/11 group, overlap group, and reentered group were higher compared with that of the post-9/11 group in all diagnosis categories.

Geographic Distribution

Veterans diagnosed with PTSD, TBI, or both were not evenly distributed across the VISNs VISNs 7, 8, 10, and 22 treated the most veterans, whereas VISN 9 and 15 treated the fewest. Taken together, the top 3 VISNs accounted for 27% to 28% of the total while lowest 3 accounted for 8% to 9% of the total cohort.

Service-Connected Disability

Of 1,339,937 veterans in the cohort, 1,067,691 had a service-connected disability rating for PTSD and/or TBI. Most were diagnosed with PTSD (n = 923,523, 86.5%) followed by both PTSD+TBI (n = 94,051, 8.8%). Three-quarters of the veterans with a service-connected disability were in the pre-9/11 group. Nearly 80% of veterans with a service-connected disability rating had a rating of > 50%. The average (SD) age of veterans with PTSD+TBI and a > 50% service-connected disability was 66.3 (11.2) years in the pre-9/11 group compared with 36.1 (8.7) years in the post-9/11 group.

Discussion

The demographic profile of veterans diagnosed with PTSD+TBI has changed across the service periods covered in this study. Compared with pre-9/11 veterans, the post-9/11 cohort: (1) higher percentage were diagnosed with PTSD+TBI; (2) higher proportion were nonmale veterans; (3) included more young veterans with > 50% service-connected disability; (4) were more racially diverse; and (5) were less likely to be married and divorced and more likely to be self-identified as single. Additionally, data revealed that veterans tended to locate more to some geographic regions than to others.

The nature of the warfare has changed remarkably over the past few decades. Gunshot wounds accounted for 65% of all injuries in World War I, 35% during Vietnam War, and 16% to 23% in the First Gulf War.²⁴ In post-9/11 military conflicts, 81% of injuries were explosion related.^24,25 Although improvements in personal protective gear and battlefield trauma care led to increased survival, several factors may have contributed to increased reporting of TBI, which peaked in 2011 at 32,000 cases.^24-26

 

Increases in PTSD Diagnosis

Increasing media awareness, mandatory battlefield concussion screening programs instituted by the US Department of Defense (DoD), and stressful conditions that exacerbate mild TBI (mTBI) may have all contributed to the increase in numbers of veterans seeking evaluations and being diagnosed with PTSD and/or TBI in the post-9/11 groups. Additionally, the 2007 National Defense Authorization Act requested the Secretary of Defense to develop a comprehensive, systematic approach for the identification, treatment, disposition, and documentation of TBI in combat and peacetime. By a conservative estimate, significant numbers of veterans will continue to be seen for mTBI at about 20,000 new cases per year.^25-27

More frequent diagnosis of mTBI may have contributed to the increase in veterans diagnosed with PTSD+TBI in the post-9/11 groups. A recent study found that almost 44% of US Army infantry soldiers in Iraq did not lose consciousness but reported symptoms consistent with TBI.¹⁴ Compared with veterans of previous wars, veterans of the post-9/11 conflicts (OIF, OED, and OND) have experienced multiple, protracted deployments with infrequent breaks that can have a cumulative effect on the development of PTSD.^8-10

The findings from the NVVRS study led to creation of specialized PTSD programs in the late 1980s. Since then, there has been an explosion of knowledge and awareness about PTSD, TBI, and the associated service-connected disability ratings and benefits, leading to an increased number of veterans seeking care for PTSD. For example, media coverage of the 50th anniversary of the D-day celebrations resulted in a surge of World War II veterans seeking treatment for PTSD and a surge of Vietnam veterans sought treatment for PTSD during the wars in Iraq and Afghanistan.²⁸ An increased number of veterans reporting PTSD symptoms prompted the DoD to increase screening for PTSD, and to encourage service members to seek treatment when appropriate.

The VA has instituted training programs for clinicians and psychologists to screen and provide care for PTSD. Beginning in 2007, the VA implemented mandatory TBI screening for all veterans who served in combat operations and separated from active-duty service after September 11, 2001. The 4-question screen identifies veterans who are at increased risk of TBI and who experience symptoms that may be related to specific event(s).²⁹ A positive screen does not diagnose TBI but rather indicates a need for further evaluation, which may or may not be responsible for inflated reporting of TBI. Renewed research also has led providers to recognize and study PTSD resulting from noncombat trauma and moral injury. The possibility of delayed onset also drives up the number of veterans diagnosed with PTSD.^5-7

Prevalence

A wide variability exists in the reported prevalence of PTSD among US war veterans with estimates ranging from 15% to 20% of veterans from recent conflicts^3,20 and 10% to 30% of veterans from previous wars.^3,19 These rates are higher than estimates from allied forces from other countries.¹⁹ Meta-analyses suggest that the prevalence of PTSD is 2% to 15% among Vietnam War veterans, 1% to 13% among first (pre-9/11) Gulf War veterans, 4% to 17% among OEF/OIF/OND veterans; these veterans have a lifetime prevalence of 6% to 31%.^{3,11,19,30-38} The prevalence of PTSD is 2 to 4 times higher among the US veterans^19,39 when compared with that of civilians.^40,41 According to one study, concomitant PTSD and TBI appears to be much higher in US war veterans (4%-17%) compared with United Kingdom Iraq War veterans (3%-6%).¹⁹

 

This study’s finding of an increase in nonmale soldiers with PTSD and/or TBI was not surprising. There is a paucity of data on the effect of war zone exposure on women veterans. Recently, women have been more actively involved in combat roles with 41,000 women deployed to a combat zone. Results of this study indicate a 2- to 3-fold increase in veterans identifying themselves as nonmale in post-9/11 groups with a higher proportion diagnosed with either PTSD alone or PTSD and TBI. Women are at a higher risk for PTSD than are men due in part to exposure to abuse/trauma prior to deployment, experience of higher rates of discrimination, and/or sexual assault.^31-33 One study involving First Gulf War female veterans reported higher precombat psychiatric histories as well as higher rates of physical and sexual abuse when compared with that of men.³¹

In this study, the average age of veterans adjudicated and compensated for PTSD and/or TBI pre-9/11, was 66 years compared with 36 years for post-9/11 veterans. Sixty-six percent of veterans from the post-9/11 group had ≥ 50% service-connected disability at age 36 years; 75% of veterans from the overlap group had ≥ 50% service-connected disability at age 41 years; and 76% veterans from the reentered group had ≥ 50% service-connected disability at age 46 years. Younger age at diagnosis and higher rates of disability not only pose unique challenges for veterans and family members, but also suggest implications for career prospects, family earnings, loss of productivity, and disease-adjusted life years. Also noted in the results, this younger cohort has a higher percentage of single/unmarried veterans, suggesting familial support systems may be more parental than spousal. Treatment for this younger cohort will likely need to focus on early and sustained rehabilitation that can be integrated with career plans.

For treatment to be effective, there must be evidence for veterans enrolling, remaining, and reporting benefits from the treatment. Limited research has shown currently advocated evidence-based therapies to have low enrollment rates, high drop-out rates, and mixed outcomes.⁴²

Results showing a gradual increase in the proportion of nonwhite, non-African American veterans diagnosed with PTSD alone, TBI alone, or both, likely reflect the changing demographic profile of the US as well as the Army. However, the reason that more African Americans were diagnosed with PTSD and/or TBI in the overlap and reentered groups when compared with the pre-9/11 group could not be ascertained. It is possible that more veterans identified themselves as African Americans as evident from a decrease in the number of veterans in the unknown category post-9/11 when compared with the pre-9/11 group. In 2016, the American Community Survey showed that Hispanic and African American veterans were more likely to use VA health care and other benefits than were any other racial group.⁴⁰ Improved screening for PTSD and TBI diagnoses, increased awareness, and education about the availability of VA services and benefits may have contributed to the increased use of VA benefits in these groups.

Data from this study are concordant with data from the National Center for Veterans Analysis and Statistics reporting on the younger age of diagnosis and higher rates of initial service-connected disability in veterans with PTSD and PTSD+TBI.⁴³ One study analyzing records from 1999 to 2004 showed that the number of PTSD cases grew by 79.5%, resulting in 148.7% increase in benefits payment from $1.7 billion to $4.3 billion per year.⁴⁴ In contrast, the compensation cost for all other disability categories increased by only 41.7% over this period. This study also revealed that while veterans with PTSD represented only 8.7% of compensation recipients, they received 20.5% of all compensation payments, driven in large part by an increase in > 50% service-connected disability ratings.⁴⁴

Thus, from financial as well as treatment points of view, the change in the demographic profile of the veteran must be considered when developing PTSD treatment strategies. While treatment in the past focused solely on addressing trauma-associated psychiatric issues, TBI and PTSD association will likely shift the focus to concurrent psychiatric and physical symptomology. Similarly, PTSD/TBI treatment modalities must consider that the profile of post-9/11 service members includes more women, younger age, and a greater racial diversity. For instance, younger age for a disabled veteran brings additional challenges, including reliance on parental or buddy support systems vs a spousal support system, integrating career with treatment, selecting geographic locations that can support both career and treatment, sustaining rehabilitation over time. The treatment needs of a 35-year-old soldier with PTSD and/or TBI, whether male or female, Asian or African American are likely to be very different from the treatment needs of a 65-year-old white male. Newer treatment approaches will have to address the needs of all soldiers.

 

Limitations

Our study may underestimate the actual PTSD and/or TBI disease burden because of the social stigma associated with diagnosis, military culture, limitations in data collection.^45-50 In addition, in this retrospective database cohort study, we considered and tried to minimize the impact of any of the usual potential limitations, including (1) accuracy of data quality and linkage; (2) identifying cohort appropriately (study groups); (3) defining endpoints clearly to avoid misclassifications; and (4) incorporating all important confounders. We identified veterans utilizing medical services at VA hospitals during a defined period and diagnosed with PTSD and TBI using ICD-9 codes and divided in 4 well-defined groups. In addition, another limitation of our study is to not accurately capture the veterans who have alternative health coverage and may choose not to enroll and/or participate in VA health care. In addition, some service members leaving war zones may not disclose or downplay the mental health symptoms to avoid any delay in their return home.

Conclusions

This study highlights the changing profile of the soldier diagnosed with PTSD and/or TBI who served pre-9/11 compared with that of those who served post-9/11. Treatment modalities must address the changes in warfare and demographics of US service members. Future treatment will need to focus more on concurrent PTSD/TBI therapies, the needs of younger soldiers, the needs of women injured in combat, and the needs of a more racially and ethnically diverse population. Severe injuries at a younger age will require early detection and rehabilitation for return to optimum functioning over a lifetime. The current study underscores a need for identifying the gaps in ongoing programs and services, developing alternatives, and implementing improved systems of care. More studies are needed to identify the cost implications and the effectiveness of current therapies for PTSD and/or TBI.

Acknowledgments

This study was supported by VA Medical Center and Midwest BioMedical Research Foundation (MBRF), Kansas City, Missouri. The manuscript received support, in part, from NIH-RO1 DK107490. These agencies did not participate in the design/conduct of the study or, in the interpretation of the data.

The nature of combat and associated injuries in Operation Iraqi Freedom (OIF), Operation Enduring Freedom (OEF), Operation New Dawn (OND), and Afghanistan War is different from previous conflicts. Multiple protracted deployments with infrequent breaks after September 11, 2001 (9/11) have further compounded the problem.

Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are the signature wounds of recent wars, with a higher incidence among the veterans of OEF and OIF compared with those from previous conflicts.^1,2 More than 2.7 million who served in Iraq and Afghanistan suffer from PTSD.^3,4 Symptoms of PTSD may appear within the first 3 months after exposure to a traumatic event or after many months and, in some cases, after a delay of many years and continue for life.⁵ Although delayed onset of PTSD in the absence of prior symptoms is rare,^6,7 its incidence rises with increasing frequency of exposure to traumatic events^8,9 and over time.¹⁰

According to the Brain Injury Association of America, TBI is “an alteration in brain function, or other evidence of brain pathology, caused by an external force.”⁸ TBI is often associated with increased risk of PTSD, depression, and posttraumatic headache,^11-13 which may lead to broader cognitive, somatic, neurobiological, and psychosocial dysfunctions.^14-17 According to Veterans Health Administration (VHA) data, 201,435 veterans from all eras enrolled with the US Department of Veterans Affairs (VA) have a diagnosis associated with TBI and 56,695 OEF/OIF veterans have been evaluated for a TBI-related condition.² According to the Defense and Veterans Brain Injury Center (DVBIC), > 361,000 veterans have been diagnosed with TBI, with a peak of 32,000 cases in 2011.^1,18 Moreover, the reported incidence and prevalence of PTSD and TBI among US veterans are not consistent. The incidence of PTSD has been estimated at 15% to 20% in recent wars^3,19 compared with 10% to 30% in previous wars.^3,19,20

When PTSD or TBI is deemed “related” to military service, the veteran may receive a service-connected disability rating ranging from 0% (no life-interfering symptoms due to injury) to 100% (totally disabling injury). The percentage of service connection associated with an injury is a quantifiable measure of the debilitating effect of injury on the individual. A significant majority (94%) of those who seek mental health services and treatment at VHA clinics apply for PTSD-related disability benefits.²¹ The estimated cost related to PTSD/TBI service-connected pensions is $20.28 billion per year and approximately $514 billion over 50 years.²² The cost of VA and Social Security disability payments combined with health care costs and treatment of PTSD is estimated to exceed $1 trillion over the next 30 years.²²

The National Vietnam Veterans Readjustment Study (NVVRS) provided valuable information on prevalence rates of PTSD and other postwar psychological problems.²³ Meanwhile, there have been no recent large-scale studies to compare the demographics of veterans diagnosed with PTSD and TBI who served prior to and after 9/11. A better understanding of demographic changes is considered essential for designing and tailoring therapeutic interventions to manage the rising cost.²²

The present study focused on identifying changing trends in the demographics of veterans who served prior to and after 9/11 and who received a VA inpatient or outpatient diagnosis of PTSD and/or TBI. Specifically, this study addressed the changes in demographics of veterans with PTSD, TBI, or PTSD+TBI seen at the VHA clinics between December 1,1998 and May 31, 2014 (before and after September 11, 2001) for diagnosis, treatment and health care policy issues.

 

Methods

This study was approved by the Kansas City VA Medical Center Institutional Review Board. VHA data from the Corporate Data Warehouse (CDW) and the National Patient Care Database were extracted using the VA Informatics and Computing Infrastructure (VINCI) workspace. CDW uses a unique identifier to identify veterans across treatment episodes at more than 1,400 VHA centers organized under 21 Veterans Integrated Service Networks (VISNs). These sources of VA data are widely used for retrospective longitudinal studies.

Study Population

The study population consisted of 1,339,937 veterans with a VA inpatient/outpatient diagnosis of PTSD or TBI using International Statistical Classification of Diseases and Related Health Problems, Ninth Revision (ICD-9) codes between December 1, 1998 and May 31, 2014. Demographic (gender classification, race, ethnicity, marital status, age at date of data extraction, and date of death if indicated), service-connection disability rating, and geographic distribution within VISN data on each veteran were then extracted.

Veterans in the cohort were assigned to 1 of 4 US military services period groups. The pre-9/11 group included veterans who entered and left the military prior to September 11, 2001. This group mostly included veterans from World War II, Korean War, Vietnam War, and the first Gulf War (1990-1991). The post-9/11 group included veterans who first entered military services after September 11, 2001. The overlap group included veterans who entered military services prior to 9/11, remained in service and left after September 11, 2001. The reentered group included veterans who entered and left service prior to September 11, 2001, and then reentered military service after September 11, 2001 (Figure 1). Using ICD-9 codes, veterans also were placed into the following categories: PTSD alone (ICD-9 309.81 only), TBI alone (ICD-9 850.0-859.9, V15.52), and PTSD+TBI (any combination of ICD-9 codes from the other categories).

Statistical Analysis 

Descriptive statistics were applied using proportions and means. Relationships between variables were examined using χ² tests, t tests, analysis of variance, and nonparametric tests. All hypotheses were 2-sided at 95% CI. Results are presented as absolute numbers.

Results

PTSD only (n = 1,132,356, 85%) was the predominant diagnosis category followed by PTSD+TBI (n = 106,792, 8%) and TBI only (n = 100,789, 7%) (Figure 2). Most of the veterans in the study served pre-9/11 (77%), followed by post-9/11 (15%); 7% were in the overlap group, and 1% in the reentered group (Table 1). It is notable that the proportion of veterans diagnosed with PTSD decreased from pre-9/11 (88%) to post-9/11 (71%), overlap (77%), and reentered (74%) service periods. Increases were noted in those with PTSD+TBI diagnosis category from pre-9/11 (4%) to post-9/11 (23%), overlap (17%), and reentered (22%) service periods (Figure 3). In general, the relative distribution of diagnostic categories in all the service periods showed a similar trend, with the majority of veterans diagnosed with PTSD only. Across all service periods, significantly smaller proportions of veterans were diagnosed with TBI only (P < .001).

   

Distribution by Gender and Age

The cohort was 92% male (n = 1,239,295), but there was a marked increase in the percentage of nonmale veterans in post-9/11 groups. Study population ages ranged from 18 to 99 years based on date of birth to the date data were obtained; or date of birth to date of death, for those who were reported deceased at the time the data were obtained. The average (SD) ages for veterans in the pre-9/11 group were significantly older (66.3 [11.2] years) compared with the ages of veterans in the post-9/11 group (36.1 [8.7] years), the overlap group (41.4 [8.2] years), and the reentered group (46.9 [9.2] years), respectively.

 

Distribution by Race and Marital Status

The cohort identified as 65.7% white and 18.2% African American with much smaller percentages of Asians, American Indian/Alaska Natives (AI/AN) and Native Hawaiian/Pacific Islanders (Table 2). The relative proportion of AI/AN and Native Hawaiian/Pacific Islanders remained constant across all groups, whereas the number of Asians diagnosed with PTSD, TBI, or PTSD+TBI increased in the post-9/11 group. The number of African Americans diagnosed with PTSD, TBI, or both markedly increased in the overlap and reentered groups when compared with the pre-9/11 group, yet it went down in the post-9/11/group.

Half the cohort identified themselves as married (n = 675,145) (Table 3). A slightly larger proportion of those diagnosed with PTSD alone were married (51.7%), compared with those diagnosed with TBI only (40.3%), or PTSD+TBI (45.8%). Veterans in the post-9/11 group were less likely to identify as married (45.2%) compared with the pre-9/11 (51.2%), overlap (52.6%), or reentered (53.2%) groups. Divorce rates among pre-9/11 group, overlap group, and reentered group were higher compared with that of the post-9/11 group in all diagnosis categories.

Geographic Distribution

Veterans diagnosed with PTSD, TBI, or both were not evenly distributed across the VISNs VISNs 7, 8, 10, and 22 treated the most veterans, whereas VISN 9 and 15 treated the fewest. Taken together, the top 3 VISNs accounted for 27% to 28% of the total while lowest 3 accounted for 8% to 9% of the total cohort.

Service-Connected Disability

Of 1,339,937 veterans in the cohort, 1,067,691 had a service-connected disability rating for PTSD and/or TBI. Most were diagnosed with PTSD (n = 923,523, 86.5%) followed by both PTSD+TBI (n = 94,051, 8.8%). Three-quarters of the veterans with a service-connected disability were in the pre-9/11 group. Nearly 80% of veterans with a service-connected disability rating had a rating of > 50%. The average (SD) age of veterans with PTSD+TBI and a > 50% service-connected disability was 66.3 (11.2) years in the pre-9/11 group compared with 36.1 (8.7) years in the post-9/11 group.

Discussion

The demographic profile of veterans diagnosed with PTSD+TBI has changed across the service periods covered in this study. Compared with pre-9/11 veterans, the post-9/11 cohort: (1) higher percentage were diagnosed with PTSD+TBI; (2) higher proportion were nonmale veterans; (3) included more young veterans with > 50% service-connected disability; (4) were more racially diverse; and (5) were less likely to be married and divorced and more likely to be self-identified as single. Additionally, data revealed that veterans tended to locate more to some geographic regions than to others.

The nature of the warfare has changed remarkably over the past few decades. Gunshot wounds accounted for 65% of all injuries in World War I, 35% during Vietnam War, and 16% to 23% in the First Gulf War.²⁴ In post-9/11 military conflicts, 81% of injuries were explosion related.^24,25 Although improvements in personal protective gear and battlefield trauma care led to increased survival, several factors may have contributed to increased reporting of TBI, which peaked in 2011 at 32,000 cases.^24-26

 

Increases in PTSD Diagnosis

Increasing media awareness, mandatory battlefield concussion screening programs instituted by the US Department of Defense (DoD), and stressful conditions that exacerbate mild TBI (mTBI) may have all contributed to the increase in numbers of veterans seeking evaluations and being diagnosed with PTSD and/or TBI in the post-9/11 groups. Additionally, the 2007 National Defense Authorization Act requested the Secretary of Defense to develop a comprehensive, systematic approach for the identification, treatment, disposition, and documentation of TBI in combat and peacetime. By a conservative estimate, significant numbers of veterans will continue to be seen for mTBI at about 20,000 new cases per year.^25-27

More frequent diagnosis of mTBI may have contributed to the increase in veterans diagnosed with PTSD+TBI in the post-9/11 groups. A recent study found that almost 44% of US Army infantry soldiers in Iraq did not lose consciousness but reported symptoms consistent with TBI.¹⁴ Compared with veterans of previous wars, veterans of the post-9/11 conflicts (OIF, OED, and OND) have experienced multiple, protracted deployments with infrequent breaks that can have a cumulative effect on the development of PTSD.^8-10

The findings from the NVVRS study led to creation of specialized PTSD programs in the late 1980s. Since then, there has been an explosion of knowledge and awareness about PTSD, TBI, and the associated service-connected disability ratings and benefits, leading to an increased number of veterans seeking care for PTSD. For example, media coverage of the 50th anniversary of the D-day celebrations resulted in a surge of World War II veterans seeking treatment for PTSD and a surge of Vietnam veterans sought treatment for PTSD during the wars in Iraq and Afghanistan.²⁸ An increased number of veterans reporting PTSD symptoms prompted the DoD to increase screening for PTSD, and to encourage service members to seek treatment when appropriate.

The VA has instituted training programs for clinicians and psychologists to screen and provide care for PTSD. Beginning in 2007, the VA implemented mandatory TBI screening for all veterans who served in combat operations and separated from active-duty service after September 11, 2001. The 4-question screen identifies veterans who are at increased risk of TBI and who experience symptoms that may be related to specific event(s).²⁹ A positive screen does not diagnose TBI but rather indicates a need for further evaluation, which may or may not be responsible for inflated reporting of TBI. Renewed research also has led providers to recognize and study PTSD resulting from noncombat trauma and moral injury. The possibility of delayed onset also drives up the number of veterans diagnosed with PTSD.^5-7

Prevalence

A wide variability exists in the reported prevalence of PTSD among US war veterans with estimates ranging from 15% to 20% of veterans from recent conflicts^3,20 and 10% to 30% of veterans from previous wars.^3,19 These rates are higher than estimates from allied forces from other countries.¹⁹ Meta-analyses suggest that the prevalence of PTSD is 2% to 15% among Vietnam War veterans, 1% to 13% among first (pre-9/11) Gulf War veterans, 4% to 17% among OEF/OIF/OND veterans; these veterans have a lifetime prevalence of 6% to 31%.^{3,11,19,30-38} The prevalence of PTSD is 2 to 4 times higher among the US veterans^19,39 when compared with that of civilians.^40,41 According to one study, concomitant PTSD and TBI appears to be much higher in US war veterans (4%-17%) compared with United Kingdom Iraq War veterans (3%-6%).¹⁹

 

This study’s finding of an increase in nonmale soldiers with PTSD and/or TBI was not surprising. There is a paucity of data on the effect of war zone exposure on women veterans. Recently, women have been more actively involved in combat roles with 41,000 women deployed to a combat zone. Results of this study indicate a 2- to 3-fold increase in veterans identifying themselves as nonmale in post-9/11 groups with a higher proportion diagnosed with either PTSD alone or PTSD and TBI. Women are at a higher risk for PTSD than are men due in part to exposure to abuse/trauma prior to deployment, experience of higher rates of discrimination, and/or sexual assault.^31-33 One study involving First Gulf War female veterans reported higher precombat psychiatric histories as well as higher rates of physical and sexual abuse when compared with that of men.³¹

In this study, the average age of veterans adjudicated and compensated for PTSD and/or TBI pre-9/11, was 66 years compared with 36 years for post-9/11 veterans. Sixty-six percent of veterans from the post-9/11 group had ≥ 50% service-connected disability at age 36 years; 75% of veterans from the overlap group had ≥ 50% service-connected disability at age 41 years; and 76% veterans from the reentered group had ≥ 50% service-connected disability at age 46 years. Younger age at diagnosis and higher rates of disability not only pose unique challenges for veterans and family members, but also suggest implications for career prospects, family earnings, loss of productivity, and disease-adjusted life years. Also noted in the results, this younger cohort has a higher percentage of single/unmarried veterans, suggesting familial support systems may be more parental than spousal. Treatment for this younger cohort will likely need to focus on early and sustained rehabilitation that can be integrated with career plans.

For treatment to be effective, there must be evidence for veterans enrolling, remaining, and reporting benefits from the treatment. Limited research has shown currently advocated evidence-based therapies to have low enrollment rates, high drop-out rates, and mixed outcomes.⁴²

Results showing a gradual increase in the proportion of nonwhite, non-African American veterans diagnosed with PTSD alone, TBI alone, or both, likely reflect the changing demographic profile of the US as well as the Army. However, the reason that more African Americans were diagnosed with PTSD and/or TBI in the overlap and reentered groups when compared with the pre-9/11 group could not be ascertained. It is possible that more veterans identified themselves as African Americans as evident from a decrease in the number of veterans in the unknown category post-9/11 when compared with the pre-9/11 group. In 2016, the American Community Survey showed that Hispanic and African American veterans were more likely to use VA health care and other benefits than were any other racial group.⁴⁰ Improved screening for PTSD and TBI diagnoses, increased awareness, and education about the availability of VA services and benefits may have contributed to the increased use of VA benefits in these groups.

Data from this study are concordant with data from the National Center for Veterans Analysis and Statistics reporting on the younger age of diagnosis and higher rates of initial service-connected disability in veterans with PTSD and PTSD+TBI.⁴³ One study analyzing records from 1999 to 2004 showed that the number of PTSD cases grew by 79.5%, resulting in 148.7% increase in benefits payment from $1.7 billion to $4.3 billion per year.⁴⁴ In contrast, the compensation cost for all other disability categories increased by only 41.7% over this period. This study also revealed that while veterans with PTSD represented only 8.7% of compensation recipients, they received 20.5% of all compensation payments, driven in large part by an increase in > 50% service-connected disability ratings.⁴⁴

Thus, from financial as well as treatment points of view, the change in the demographic profile of the veteran must be considered when developing PTSD treatment strategies. While treatment in the past focused solely on addressing trauma-associated psychiatric issues, TBI and PTSD association will likely shift the focus to concurrent psychiatric and physical symptomology. Similarly, PTSD/TBI treatment modalities must consider that the profile of post-9/11 service members includes more women, younger age, and a greater racial diversity. For instance, younger age for a disabled veteran brings additional challenges, including reliance on parental or buddy support systems vs a spousal support system, integrating career with treatment, selecting geographic locations that can support both career and treatment, sustaining rehabilitation over time. The treatment needs of a 35-year-old soldier with PTSD and/or TBI, whether male or female, Asian or African American are likely to be very different from the treatment needs of a 65-year-old white male. Newer treatment approaches will have to address the needs of all soldiers.

 

Limitations

Our study may underestimate the actual PTSD and/or TBI disease burden because of the social stigma associated with diagnosis, military culture, limitations in data collection.^45-50 In addition, in this retrospective database cohort study, we considered and tried to minimize the impact of any of the usual potential limitations, including (1) accuracy of data quality and linkage; (2) identifying cohort appropriately (study groups); (3) defining endpoints clearly to avoid misclassifications; and (4) incorporating all important confounders. We identified veterans utilizing medical services at VA hospitals during a defined period and diagnosed with PTSD and TBI using ICD-9 codes and divided in 4 well-defined groups. In addition, another limitation of our study is to not accurately capture the veterans who have alternative health coverage and may choose not to enroll and/or participate in VA health care. In addition, some service members leaving war zones may not disclose or downplay the mental health symptoms to avoid any delay in their return home.

Conclusions

This study highlights the changing profile of the soldier diagnosed with PTSD and/or TBI who served pre-9/11 compared with that of those who served post-9/11. Treatment modalities must address the changes in warfare and demographics of US service members. Future treatment will need to focus more on concurrent PTSD/TBI therapies, the needs of younger soldiers, the needs of women injured in combat, and the needs of a more racially and ethnically diverse population. Severe injuries at a younger age will require early detection and rehabilitation for return to optimum functioning over a lifetime. The current study underscores a need for identifying the gaps in ongoing programs and services, developing alternatives, and implementing improved systems of care. More studies are needed to identify the cost implications and the effectiveness of current therapies for PTSD and/or TBI.

Acknowledgments

This study was supported by VA Medical Center and Midwest BioMedical Research Foundation (MBRF), Kansas City, Missouri. The manuscript received support, in part, from NIH-RO1 DK107490. These agencies did not participate in the design/conduct of the study or, in the interpretation of the data.

The nature of combat and associated injuries in Operation Iraqi Freedom (OIF), Operation Enduring Freedom (OEF), Operation New Dawn (OND), and Afghanistan War is different from previous conflicts. Multiple protracted deployments with infrequent breaks after September 11, 2001 (9/11) have further compounded the problem.

Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI) are the signature wounds of recent wars, with a higher incidence among the veterans of OEF and OIF compared with those from previous conflicts.^1,2 More than 2.7 million who served in Iraq and Afghanistan suffer from PTSD.^3,4 Symptoms of PTSD may appear within the first 3 months after exposure to a traumatic event or after many months and, in some cases, after a delay of many years and continue for life.⁵ Although delayed onset of PTSD in the absence of prior symptoms is rare,^6,7 its incidence rises with increasing frequency of exposure to traumatic events^8,9 and over time.¹⁰

According to the Brain Injury Association of America, TBI is “an alteration in brain function, or other evidence of brain pathology, caused by an external force.”⁸ TBI is often associated with increased risk of PTSD, depression, and posttraumatic headache,^11-13 which may lead to broader cognitive, somatic, neurobiological, and psychosocial dysfunctions.^14-17 According to Veterans Health Administration (VHA) data, 201,435 veterans from all eras enrolled with the US Department of Veterans Affairs (VA) have a diagnosis associated with TBI and 56,695 OEF/OIF veterans have been evaluated for a TBI-related condition.² According to the Defense and Veterans Brain Injury Center (DVBIC), > 361,000 veterans have been diagnosed with TBI, with a peak of 32,000 cases in 2011.^1,18 Moreover, the reported incidence and prevalence of PTSD and TBI among US veterans are not consistent. The incidence of PTSD has been estimated at 15% to 20% in recent wars^3,19 compared with 10% to 30% in previous wars.^3,19,20

When PTSD or TBI is deemed “related” to military service, the veteran may receive a service-connected disability rating ranging from 0% (no life-interfering symptoms due to injury) to 100% (totally disabling injury). The percentage of service connection associated with an injury is a quantifiable measure of the debilitating effect of injury on the individual. A significant majority (94%) of those who seek mental health services and treatment at VHA clinics apply for PTSD-related disability benefits.²¹ The estimated cost related to PTSD/TBI service-connected pensions is $20.28 billion per year and approximately $514 billion over 50 years.²² The cost of VA and Social Security disability payments combined with health care costs and treatment of PTSD is estimated to exceed $1 trillion over the next 30 years.²²

The National Vietnam Veterans Readjustment Study (NVVRS) provided valuable information on prevalence rates of PTSD and other postwar psychological problems.²³ Meanwhile, there have been no recent large-scale studies to compare the demographics of veterans diagnosed with PTSD and TBI who served prior to and after 9/11. A better understanding of demographic changes is considered essential for designing and tailoring therapeutic interventions to manage the rising cost.²²

The present study focused on identifying changing trends in the demographics of veterans who served prior to and after 9/11 and who received a VA inpatient or outpatient diagnosis of PTSD and/or TBI. Specifically, this study addressed the changes in demographics of veterans with PTSD, TBI, or PTSD+TBI seen at the VHA clinics between December 1,1998 and May 31, 2014 (before and after September 11, 2001) for diagnosis, treatment and health care policy issues.

 

Methods

This study was approved by the Kansas City VA Medical Center Institutional Review Board. VHA data from the Corporate Data Warehouse (CDW) and the National Patient Care Database were extracted using the VA Informatics and Computing Infrastructure (VINCI) workspace. CDW uses a unique identifier to identify veterans across treatment episodes at more than 1,400 VHA centers organized under 21 Veterans Integrated Service Networks (VISNs). These sources of VA data are widely used for retrospective longitudinal studies.

Study Population

The study population consisted of 1,339,937 veterans with a VA inpatient/outpatient diagnosis of PTSD or TBI using International Statistical Classification of Diseases and Related Health Problems, Ninth Revision (ICD-9) codes between December 1, 1998 and May 31, 2014. Demographic (gender classification, race, ethnicity, marital status, age at date of data extraction, and date of death if indicated), service-connection disability rating, and geographic distribution within VISN data on each veteran were then extracted.

Veterans in the cohort were assigned to 1 of 4 US military services period groups. The pre-9/11 group included veterans who entered and left the military prior to September 11, 2001. This group mostly included veterans from World War II, Korean War, Vietnam War, and the first Gulf War (1990-1991). The post-9/11 group included veterans who first entered military services after September 11, 2001. The overlap group included veterans who entered military services prior to 9/11, remained in service and left after September 11, 2001. The reentered group included veterans who entered and left service prior to September 11, 2001, and then reentered military service after September 11, 2001 (Figure 1). Using ICD-9 codes, veterans also were placed into the following categories: PTSD alone (ICD-9 309.81 only), TBI alone (ICD-9 850.0-859.9, V15.52), and PTSD+TBI (any combination of ICD-9 codes from the other categories).

Statistical Analysis 

Descriptive statistics were applied using proportions and means. Relationships between variables were examined using χ² tests, t tests, analysis of variance, and nonparametric tests. All hypotheses were 2-sided at 95% CI. Results are presented as absolute numbers.

Results

PTSD only (n = 1,132,356, 85%) was the predominant diagnosis category followed by PTSD+TBI (n = 106,792, 8%) and TBI only (n = 100,789, 7%) (Figure 2). Most of the veterans in the study served pre-9/11 (77%), followed by post-9/11 (15%); 7% were in the overlap group, and 1% in the reentered group (Table 1). It is notable that the proportion of veterans diagnosed with PTSD decreased from pre-9/11 (88%) to post-9/11 (71%), overlap (77%), and reentered (74%) service periods. Increases were noted in those with PTSD+TBI diagnosis category from pre-9/11 (4%) to post-9/11 (23%), overlap (17%), and reentered (22%) service periods (Figure 3). In general, the relative distribution of diagnostic categories in all the service periods showed a similar trend, with the majority of veterans diagnosed with PTSD only. Across all service periods, significantly smaller proportions of veterans were diagnosed with TBI only (P < .001).

   

Distribution by Gender and Age

The cohort was 92% male (n = 1,239,295), but there was a marked increase in the percentage of nonmale veterans in post-9/11 groups. Study population ages ranged from 18 to 99 years based on date of birth to the date data were obtained; or date of birth to date of death, for those who were reported deceased at the time the data were obtained. The average (SD) ages for veterans in the pre-9/11 group were significantly older (66.3 [11.2] years) compared with the ages of veterans in the post-9/11 group (36.1 [8.7] years), the overlap group (41.4 [8.2] years), and the reentered group (46.9 [9.2] years), respectively.

 

Distribution by Race and Marital Status

The cohort identified as 65.7% white and 18.2% African American with much smaller percentages of Asians, American Indian/Alaska Natives (AI/AN) and Native Hawaiian/Pacific Islanders (Table 2). The relative proportion of AI/AN and Native Hawaiian/Pacific Islanders remained constant across all groups, whereas the number of Asians diagnosed with PTSD, TBI, or PTSD+TBI increased in the post-9/11 group. The number of African Americans diagnosed with PTSD, TBI, or both markedly increased in the overlap and reentered groups when compared with the pre-9/11 group, yet it went down in the post-9/11/group.

Half the cohort identified themselves as married (n = 675,145) (Table 3). A slightly larger proportion of those diagnosed with PTSD alone were married (51.7%), compared with those diagnosed with TBI only (40.3%), or PTSD+TBI (45.8%). Veterans in the post-9/11 group were less likely to identify as married (45.2%) compared with the pre-9/11 (51.2%), overlap (52.6%), or reentered (53.2%) groups. Divorce rates among pre-9/11 group, overlap group, and reentered group were higher compared with that of the post-9/11 group in all diagnosis categories.

Geographic Distribution

Veterans diagnosed with PTSD, TBI, or both were not evenly distributed across the VISNs VISNs 7, 8, 10, and 22 treated the most veterans, whereas VISN 9 and 15 treated the fewest. Taken together, the top 3 VISNs accounted for 27% to 28% of the total while lowest 3 accounted for 8% to 9% of the total cohort.

Service-Connected Disability

Of 1,339,937 veterans in the cohort, 1,067,691 had a service-connected disability rating for PTSD and/or TBI. Most were diagnosed with PTSD (n = 923,523, 86.5%) followed by both PTSD+TBI (n = 94,051, 8.8%). Three-quarters of the veterans with a service-connected disability were in the pre-9/11 group. Nearly 80% of veterans with a service-connected disability rating had a rating of > 50%. The average (SD) age of veterans with PTSD+TBI and a > 50% service-connected disability was 66.3 (11.2) years in the pre-9/11 group compared with 36.1 (8.7) years in the post-9/11 group.

Discussion

The demographic profile of veterans diagnosed with PTSD+TBI has changed across the service periods covered in this study. Compared with pre-9/11 veterans, the post-9/11 cohort: (1) higher percentage were diagnosed with PTSD+TBI; (2) higher proportion were nonmale veterans; (3) included more young veterans with > 50% service-connected disability; (4) were more racially diverse; and (5) were less likely to be married and divorced and more likely to be self-identified as single. Additionally, data revealed that veterans tended to locate more to some geographic regions than to others.

The nature of the warfare has changed remarkably over the past few decades. Gunshot wounds accounted for 65% of all injuries in World War I, 35% during Vietnam War, and 16% to 23% in the First Gulf War.²⁴ In post-9/11 military conflicts, 81% of injuries were explosion related.^24,25 Although improvements in personal protective gear and battlefield trauma care led to increased survival, several factors may have contributed to increased reporting of TBI, which peaked in 2011 at 32,000 cases.^24-26

 

Increases in PTSD Diagnosis

Increasing media awareness, mandatory battlefield concussion screening programs instituted by the US Department of Defense (DoD), and stressful conditions that exacerbate mild TBI (mTBI) may have all contributed to the increase in numbers of veterans seeking evaluations and being diagnosed with PTSD and/or TBI in the post-9/11 groups. Additionally, the 2007 National Defense Authorization Act requested the Secretary of Defense to develop a comprehensive, systematic approach for the identification, treatment, disposition, and documentation of TBI in combat and peacetime. By a conservative estimate, significant numbers of veterans will continue to be seen for mTBI at about 20,000 new cases per year.^25-27

More frequent diagnosis of mTBI may have contributed to the increase in veterans diagnosed with PTSD+TBI in the post-9/11 groups. A recent study found that almost 44% of US Army infantry soldiers in Iraq did not lose consciousness but reported symptoms consistent with TBI.¹⁴ Compared with veterans of previous wars, veterans of the post-9/11 conflicts (OIF, OED, and OND) have experienced multiple, protracted deployments with infrequent breaks that can have a cumulative effect on the development of PTSD.^8-10

The findings from the NVVRS study led to creation of specialized PTSD programs in the late 1980s. Since then, there has been an explosion of knowledge and awareness about PTSD, TBI, and the associated service-connected disability ratings and benefits, leading to an increased number of veterans seeking care for PTSD. For example, media coverage of the 50th anniversary of the D-day celebrations resulted in a surge of World War II veterans seeking treatment for PTSD and a surge of Vietnam veterans sought treatment for PTSD during the wars in Iraq and Afghanistan.²⁸ An increased number of veterans reporting PTSD symptoms prompted the DoD to increase screening for PTSD, and to encourage service members to seek treatment when appropriate.

The VA has instituted training programs for clinicians and psychologists to screen and provide care for PTSD. Beginning in 2007, the VA implemented mandatory TBI screening for all veterans who served in combat operations and separated from active-duty service after September 11, 2001. The 4-question screen identifies veterans who are at increased risk of TBI and who experience symptoms that may be related to specific event(s).²⁹ A positive screen does not diagnose TBI but rather indicates a need for further evaluation, which may or may not be responsible for inflated reporting of TBI. Renewed research also has led providers to recognize and study PTSD resulting from noncombat trauma and moral injury. The possibility of delayed onset also drives up the number of veterans diagnosed with PTSD.^5-7

Prevalence

A wide variability exists in the reported prevalence of PTSD among US war veterans with estimates ranging from 15% to 20% of veterans from recent conflicts^3,20 and 10% to 30% of veterans from previous wars.^3,19 These rates are higher than estimates from allied forces from other countries.¹⁹ Meta-analyses suggest that the prevalence of PTSD is 2% to 15% among Vietnam War veterans, 1% to 13% among first (pre-9/11) Gulf War veterans, 4% to 17% among OEF/OIF/OND veterans; these veterans have a lifetime prevalence of 6% to 31%.^{3,11,19,30-38} The prevalence of PTSD is 2 to 4 times higher among the US veterans^19,39 when compared with that of civilians.^40,41 According to one study, concomitant PTSD and TBI appears to be much higher in US war veterans (4%-17%) compared with United Kingdom Iraq War veterans (3%-6%).¹⁹

 

This study’s finding of an increase in nonmale soldiers with PTSD and/or TBI was not surprising. There is a paucity of data on the effect of war zone exposure on women veterans. Recently, women have been more actively involved in combat roles with 41,000 women deployed to a combat zone. Results of this study indicate a 2- to 3-fold increase in veterans identifying themselves as nonmale in post-9/11 groups with a higher proportion diagnosed with either PTSD alone or PTSD and TBI. Women are at a higher risk for PTSD than are men due in part to exposure to abuse/trauma prior to deployment, experience of higher rates of discrimination, and/or sexual assault.^31-33 One study involving First Gulf War female veterans reported higher precombat psychiatric histories as well as higher rates of physical and sexual abuse when compared with that of men.³¹

In this study, the average age of veterans adjudicated and compensated for PTSD and/or TBI pre-9/11, was 66 years compared with 36 years for post-9/11 veterans. Sixty-six percent of veterans from the post-9/11 group had ≥ 50% service-connected disability at age 36 years; 75% of veterans from the overlap group had ≥ 50% service-connected disability at age 41 years; and 76% veterans from the reentered group had ≥ 50% service-connected disability at age 46 years. Younger age at diagnosis and higher rates of disability not only pose unique challenges for veterans and family members, but also suggest implications for career prospects, family earnings, loss of productivity, and disease-adjusted life years. Also noted in the results, this younger cohort has a higher percentage of single/unmarried veterans, suggesting familial support systems may be more parental than spousal. Treatment for this younger cohort will likely need to focus on early and sustained rehabilitation that can be integrated with career plans.

For treatment to be effective, there must be evidence for veterans enrolling, remaining, and reporting benefits from the treatment. Limited research has shown currently advocated evidence-based therapies to have low enrollment rates, high drop-out rates, and mixed outcomes.⁴²

Results showing a gradual increase in the proportion of nonwhite, non-African American veterans diagnosed with PTSD alone, TBI alone, or both, likely reflect the changing demographic profile of the US as well as the Army. However, the reason that more African Americans were diagnosed with PTSD and/or TBI in the overlap and reentered groups when compared with the pre-9/11 group could not be ascertained. It is possible that more veterans identified themselves as African Americans as evident from a decrease in the number of veterans in the unknown category post-9/11 when compared with the pre-9/11 group. In 2016, the American Community Survey showed that Hispanic and African American veterans were more likely to use VA health care and other benefits than were any other racial group.⁴⁰ Improved screening for PTSD and TBI diagnoses, increased awareness, and education about the availability of VA services and benefits may have contributed to the increased use of VA benefits in these groups.

Data from this study are concordant with data from the National Center for Veterans Analysis and Statistics reporting on the younger age of diagnosis and higher rates of initial service-connected disability in veterans with PTSD and PTSD+TBI.⁴³ One study analyzing records from 1999 to 2004 showed that the number of PTSD cases grew by 79.5%, resulting in 148.7% increase in benefits payment from $1.7 billion to $4.3 billion per year.⁴⁴ In contrast, the compensation cost for all other disability categories increased by only 41.7% over this period. This study also revealed that while veterans with PTSD represented only 8.7% of compensation recipients, they received 20.5% of all compensation payments, driven in large part by an increase in > 50% service-connected disability ratings.⁴⁴

Thus, from financial as well as treatment points of view, the change in the demographic profile of the veteran must be considered when developing PTSD treatment strategies. While treatment in the past focused solely on addressing trauma-associated psychiatric issues, TBI and PTSD association will likely shift the focus to concurrent psychiatric and physical symptomology. Similarly, PTSD/TBI treatment modalities must consider that the profile of post-9/11 service members includes more women, younger age, and a greater racial diversity. For instance, younger age for a disabled veteran brings additional challenges, including reliance on parental or buddy support systems vs a spousal support system, integrating career with treatment, selecting geographic locations that can support both career and treatment, sustaining rehabilitation over time. The treatment needs of a 35-year-old soldier with PTSD and/or TBI, whether male or female, Asian or African American are likely to be very different from the treatment needs of a 65-year-old white male. Newer treatment approaches will have to address the needs of all soldiers.

 

Limitations

Our study may underestimate the actual PTSD and/or TBI disease burden because of the social stigma associated with diagnosis, military culture, limitations in data collection.^45-50 In addition, in this retrospective database cohort study, we considered and tried to minimize the impact of any of the usual potential limitations, including (1) accuracy of data quality and linkage; (2) identifying cohort appropriately (study groups); (3) defining endpoints clearly to avoid misclassifications; and (4) incorporating all important confounders. We identified veterans utilizing medical services at VA hospitals during a defined period and diagnosed with PTSD and TBI using ICD-9 codes and divided in 4 well-defined groups. In addition, another limitation of our study is to not accurately capture the veterans who have alternative health coverage and may choose not to enroll and/or participate in VA health care. In addition, some service members leaving war zones may not disclose or downplay the mental health symptoms to avoid any delay in their return home.

Conclusions

This study highlights the changing profile of the soldier diagnosed with PTSD and/or TBI who served pre-9/11 compared with that of those who served post-9/11. Treatment modalities must address the changes in warfare and demographics of US service members. Future treatment will need to focus more on concurrent PTSD/TBI therapies, the needs of younger soldiers, the needs of women injured in combat, and the needs of a more racially and ethnically diverse population. Severe injuries at a younger age will require early detection and rehabilitation for return to optimum functioning over a lifetime. The current study underscores a need for identifying the gaps in ongoing programs and services, developing alternatives, and implementing improved systems of care. More studies are needed to identify the cost implications and the effectiveness of current therapies for PTSD and/or TBI.

Acknowledgments

This study was supported by VA Medical Center and Midwest BioMedical Research Foundation (MBRF), Kansas City, Missouri. The manuscript received support, in part, from NIH-RO1 DK107490. These agencies did not participate in the design/conduct of the study or, in the interpretation of the data.

Diabetic foot ulcers (DFUs) are devastating, common, and costly. This burden is borne disproportionately by veterans who have high prevalence of type 2 diabetes mellitus (T2DM) and other precipitating risk factors.¹ The mortality of veterans following a DFU is sobering, and ulceration is recognized as a significant marker of disease severity.

A 2017 study by Brennan and colleagues reported a 19% mortality rate within 1 year, and only 29% survive past 5 years.² DFUs are often complicated by peripheral arterial disease (PAD) and diabetic immune dysfunction, contributing to chronic wounds and infection.^3,4 About 60% of all foot ulcers become infected, and > 20% of patients with a diabetic foot infection require amputation.^5,6

A 2010 retrospective study reports that > 3,400 veterans have a diabetes-related lower extremity amputation annually, vastly surpassing the rate of amputation secondary to trauma in the Veterans Health Administration (VHA).^7,8 The inpatient costs for each amputation exceeded $60,000 in fiscal year 2010, and these amputation-related costs represent only 1 component of the total expense to the VHA attributable to diabetic foot complications.⁷ A recent systematic review by Chan and colleagues estimated mean annual costs in the year following a foot ulcer to be $44,200 to the public payer.⁹ This implies that direct expenditures for treatment of DFUs within the VHA exceeds $3 billion annually.

 

Diabetic Foot Ulcer Prevention

Given the dramatic impact of diabetic foot complications to the veteran and the US health care system, the VHA has long recognized the importance of preventive care for those at risk. In 2017 US Department of Veterans Affairs (VA) and Department of Defense issued a clinical practice guideline for the management of T2DM that recommended prophylactic foot care for early identification of any deformity or skin breakdown.¹⁰ The guidelines note that a “person who has had a foot ulcer is at lifelong risk of further ulceration,” reflecting the high rate of recurrence among all patients, including veterans. Multiple studies suggest that as many as 40% of patients experience recidivism in the first year after healing from a wound.^11-16

The VA is well equipped to deliver quality preventive care because of its innovative and long-standing PAVE (Prevention of Amputations for Veterans Everywhere) program.¹⁷ PAVE provides screening, education, appropriate footwear, and stratified care guidelines for veterans at risk for diabetes-related foot complications (Table 1). The practices encouraged by PAVE are evidence-based and synergistic with the objectives of the VA’s patient aligned care team (PACT) delivery approach.¹⁸ The granular data collected through PAVE are used to guide best practices and provide benchmarks for diabetic foot outcomes.

Unfortunately, despite PAVE guidelines requiring annual specialist foot care for at-risk veterans, a 2013 report by the VA Office of the Inspector General (OIG) found that one-third of all patients had no documentation of this minimal requirement of preventive foot care.¹⁹ Although the VA has worked to address this issue, the data hint at the missed opportunities for prevention of complications and the challenges of ensuring that a large at-risk veteran population has systematic and routine screening with access to specialist foot care.

Given the large proportion of veterans at high risk of chronic wound formation and the challenges of ensuring that this cohort receives good preventive foot care, expanding telemedicine has been suggested. Telemedicine solutions have the potential to reduce the impact of chronic wounds on overburdened clinic resources, schedules, and local and federal budgets.²⁰ Interestingly, the only preventive practice for the diabetic foot that has been proven effective through multiple randomized controlled trials and national and international clinical guidance documents is once-daily foot temperature monitoring.^21-26 Daily monitoring has the potential to reduce the burden of DFUs to veterans, improve veteran access to needed preventive care, and reduce costs incurred by the VHA treating diabetic foot complications. Yet despite a recent national guidance document detailing its appropriate use in PAVE 3 veterans, it remains underutilized.²⁷

The purpose of this review is to: (1) discuss the evidence supporting once-daily remote temperature monitoring (RTM), a telemedicine approach critical to improving both veteran access to care and diabetic foot outcomes; (2) summarize a 2017 study that presented an advanced clinical understanding of RTM use among veterans; (3) provide previously unpublished data from this study comparing high-risk VA and non-VA cohorts, highlighting the opportunity for additional focus on foot ulcer prevention within the VA; and (4) report on recent VA utilization of a RTM technology based on this research, emphasizing lessons learned and best practices.

 

Remote Temperature Monitoring

The objective of daily foot temperature monitoring is to identify impending inflammatory foot conditions, such as DFUs, infection, and acute Charcot neuroarthropathy episodes. The patient and care team then act to resolve the cause of detected inflammation before clinical presentation (prevention) and begin treatment earlier than would otherwise be possible to avoid expensive complications, such as infection (early detection). Preventive therapies are low risk to the patient and inexpensive.

RTM is recommended by multiple clinical practice guidelines, including those of the International Working Group on the Diabetic Foot, the American College of Foot and Ankle Surgeons, and the Wound Healing Society.^24-26 Its use is supported by evidence from 3 National Institutes of Health-funded and well-designed randomized controlled trials, 1 of which was additionally supported by a VA Health Services Research and Development Service Merit Award.^21-23,28 Conducted between 2004 and 2007, these studies demonstrated the potential to reduce foot ulcer incidence by as much as 85% using a dermal thermometer to identify inflammation and prompt decreased ambulation. Investigators established a clinical monitoring protocol comparing the temperatures between 6 matched locations on the left and right feet. Persistent differences in contralateral temperatures exceeding 2.2°C (4.0°F) were used as a marker for elevated risk and to initiate preventive care. Based on the encouraging results from these studies, a 2017 effectiveness review prepared for the Agency for Healthcare Research and Quality concluded that “home monitoring of foot skin temperature is effective for reducing foot ulcer incidence and recurrence.”²⁹

Accuracy of RTM

A 2017 longitudinal study (NCT02647346) has provided novel data to advance understanding of RTM for the prediction and prevention of DFUs.³⁰ This study was the first to systematically analyze the accuracy of RTM over different monitoring thresholds. The results enable practitioners to deliver risk-stratified preventive care. Policy makers can use the data from this study to weigh the cost and benefits of RTM for population health.

The multicenter trials had 129 participants from 4 VA health care systems: VA Long Beach Healthcare System in California, Miami VA Healthcare System in Florida, Phoenix VA Healthcare System in Arizona, and VA West Los Angeles Healthcare System in California. Each participant was followed for 34 weeks under standard preventive foot care and was instructed to step on a telemedicine SmartMat (Podimetrics, Inc) RTM mat for 20 seconds daily. Participants and investigators were blinded to the temperature data so that the accuracy of temperature monitoring could be assessed. All participants had a history of T2DM and healed DFU. Principal exclusion criteria included unhealed plantar wound, history of proximal lower extremity amputation (ie, above ankle), active Charcot foot disease, and comorbidities that could potentially inhibit an inflammatory response, such as end-stage renal disease, active malignancy, and immunosuppressive diseases.

The investigators reported that RTM with the study mat detected 97% of nonacute plantar DFUs using the most commonly studied threshold (sustained 2.2°C temperature difference). The lead time averaged 37 days before clinical identification of the wound under standard care. Although the false-positive rate of 57% was high, corresponding to approximately 3.0 notifications per patient per year on average in the research setting, it is important to note that this study only considered the prediction of plantar DFUs. Thus, detection of foot inflammation secondary to other conditions, such as preulcerative lesion, dorsal wound, Charcot neuroarthropathy, or foot infection, were reported as a false positive per the study’s definitions. Further, Crisologo and Lavery noted in a translational medicine summary of this research, because the intervention is noninvasive and minimally impactful to the patient and the health care system, “the potential to arrest re-ulceration is worth the perceived inconvenience to the patient.”³¹

Secondary outcomes related to adherence and ease of use were encouraging. Eighty-eight percent of participants reported that the mat was “very easy to use,” the highest possible score, and 98% were able to set up the mat for home use without difficulty. At the end of the 34-week study, more than 74% of participants remained engaged in routine use of the mat under a per-protocol assessment of adherence. These results are especially impressive given the documented poor adherence of at-risk patients to routine use of therapeutic footwear, which has been reported to be as low as 15%.³²

 

New Research

The data collected during this study has led to new research and advancements in RTM. A recent publication by Gordon and colleagues investigated whether RTM is less accurate in cohorts with perceived challenges.³³ They include patients with recently healed wounds and those with a history of partial foot amputation. There was no difference in the accuracy or lead time for either cohort relative to the entire cohort, suggesting that RTM is appropriate for monitoring patients with recently healed DFUs or partial foot amputations.

In another recent study, the data were used to derive a novel approach to monitor a single at-risk foot.³⁴ The practice of RTM has traditionally required comparing temperatures between contralaterally matched plantar locations on the feet, thus limiting its use in patients with a history of major lower extremity amputation and patients being treated for a wound, which may be bandaged or in an off-loading cast or boot. Because the risk factors for DFUs exist in both limbs, these patients are at high risk for developing complications to the contralateral foot and may benefit from preventive once-daily foot temperature monitoring. The investigators empirically derived a novel monitoring approach for patients without a contralateral control. This approach was found to predict 91% of impending plantar DFUs on average 41 days before clinical presentation with a false positive rate of 54%.

Additional Focus on Prevention

Table 2 shows previously unpublished data from a subgroup analysis between veteran and nonveteran participants in the study.²⁵ These descriptive statistics reinforce some widely held assumptions regarding the high-risk veteran population and challenge others. For example, compared with the nonveteran participants, the veteran cohort unsurprisingly had a larger ratio of male participants (P < .01), had a higher rate of cigarette use (P < .01), and was more likely to live alone (although not at a statistically significant level). Veterans in the study had body mass index, rates of alcohol use, frequency of exercise, and glucose control comparable to that of nonveterans.

The potential impact of the PAVE program is clear in several of these comparisons. Although as few as 15% of patients use therapeutic shoes routinely, PAVE ensures that the majority of veterans receive them. Nearly 95% of veterans have therapeutic shoes compared with about 80% of nonveteran participants (P < .05). Veterans also had higher ankle-brachial index results (P < .05), although on average both cohorts were within normal clinical parameters. Veterans had a significantly longer duration since healing from the most recent wound, and fewer veteran participants had a wound that healed in the 3 months prior to the study. Despite this, during the study veterans had annualized DFU incidence equal to that of nonveterans. Furthermore, veterans also had significantly higher rates of amputation prior to participation. That these critical outcomes for veterans are no better than those observed in other care environments despite PAVE suggests that approaches recommended via PAVE alone are insufficient to significantly arrest DFU recurrence, and even more focus on prevention in the VA may be warranted.

 

From Research to Practice

Since the publication of the 2017 study, the VHA has been at the vanguard of translating the evidence and research underlying RTM into clinical practice. A clinical guidance document governing appropriate use of RTM with the study mat was recently published by the VA Prosthetic and Sensory Aids Service in collaboration with the National Podiatry Program office.²⁷ This guidance document recommends once-daily RTM for at-risk veterans designated PAVE level 3. It defines roles and responsibilities required for the successful implementation of a RTM program with the study device. The document additionally presents various clinical monitoring protocols for veterans, although the protocol and thresholds used are at the discretion of the prescribing clinician and should reflect the risk profile of the veteran in question.

A staged response to inflammation has proven popular, whereby an initial high-sensitivity threshold is chosen for monitoring. The initial response is telephone outreach by a designee supplied by the clinic or device manufacturer, typically a trained registered nurse, to the veteran to collect subjective history and instruct off-loading and reduced ambulation, with a target of 50% baseline reduction in step count. Should the inflammation persist despite off-loading, an examination may be necessary to identify and resolve its cause. For recalcitrant inflammation, more targeted pressure off-loading of the affected area may be accomplished with custom orthotics, accommodative insoles, removable cast walkers, and total contact casting. After 2 to 4 weeks without signs of inflammation, the cause is deemed to have been resolved and lowered the acute risk for developing further diabetic foot complications.

More than 600 veterans have been monitored for > 1,000 patient-years—13 VA medical centers are practicing RTM with the study mat as of this writing. The monitoring program has been integrated into many veteran daily routines as evidenced by > 70% retaining full engagement after having been monitored for > 1 year. The total number of alerts/patient-years across these veterans has been 1.4, significantly lower than the 3.0 alerts/patient-year observed in the study. This is potentially due to successful interventions in response to detected inflammation, resolving inflammation, and avoiding unnecessary alerts occurring in the research setting, which did not employ interventions that resolved inflammation episodes. In the past 6 months, 68% of all inflammation detected resolved via off-loading alone without requiring further clinical intervention. In the cases that required an examination, 76% of patients reported clinically meaningful preventive care (eg, preulcerative callus was debrided, a subungual hemorrhage was treated, a foot ulcer was identified).

Organizational Best Practices

Several best practices have been cultivated related to initiating a RTM program at a new site, for promoting the success of a RTM program, and provisioning excellent preventive care to support the RTM program. Although we advise adhering to the recommendations in the VA guidance document,²⁷ the authors have observed several additional organizational best practices that are not explicitly addressed.

Partnering with PACT. Collaboration between PAVE and PACT has the potential not only to improve outcomes for patients at risk for diabetic foot complications, but also can help identify appropriate high-risk veteran candidates for preventive care with RTM who may not be followed for routine care from a specialty provider, such as a podiatrist, as highlighted by the 2013 OIG report.

Prescreening eligible patients. Several programs have used PAVE data or appointment schedules to identify and target high-risk veterans proactively. This approach has several benefits. It simplifies clinical coordination and streamlines workflow for patient identification and onboarding. It also allows those veterans at highest risk to receive needed and recommended preventive care at their next scheduled appointment. Finally, if PAVE data are used to identify eligible patients, it has the added benefit of ensuring a baseline level of telemedicine preventive foot care for veterans who have become lost to follow-up and have not been seen recently for a routine foot examination.

Implementing foot monitoring during wound treatment. Recent research has expanded the reach of once-daily RTM with the mat to patients being treated for a wound to only 1 foot. This practice has 2 benefits: The patient is able to establish a preventive routine before healing, an important advantage because research strongly suggests that recurrence is most likely in the first months after healing. Second, 48% of patients with a history of DFUs will develop new wounds to the contralateral foot because risk factors, such as neuropathy and peripheral arterial disease, exist in both limbs.³⁵ Furthermore, ongoing treatment for a wound to 1 foot may result in gait deviation and elevated pressure to the sound foot, additionally predisposing the veteran to complications, resulting in a high rate of wounds occurring to the unwounded foot during treatment (0.2 DFU/DFU-year).³⁴ Thus, there is potential benefit in monitoring the sound foot while undergoing treatment for a wound; further, the patient will have immediate access to the device for prevention of recurrence once the wound has resolved.

Utilizing foot monitoring as an extension of telemedicine. Many VA facilities have large geographic catchment areas, making routine follow-up difficult for veterans living in rural areas. RTM serves as an extension of the patient’s daily self-examination and the clinician’s ability to monitor patients with objective information daily. The veterans using the system become more invested and feel as though they are taking an active role in their health care.

Investing in ongoing medical education. Multidisciplinary education sessions reviewing supporting clinical data and resultant clinical practice guidelines raise awareness for those providers and trainees unaware of preventive best practices for the diabetic foot, including those related to foot RTM. These sessions also are helpful for those familiar with foot temperature monitoring or who are responsible for administration of an ongoing program to remain current with contemporary best practices and to discuss improvements for patient care. Familiarity also can help address clinical inertia when benefits and evidence are clearly communicated with health care providers (HCPs).

 

Clinical Best Practices

Treating preulcerative lesions urgently and aggressively. Callus and other preulcerative lesions often cause progressive tissue damage and poor outcomes. When identified, these lesions should be promptly treated to ensure best outcomes.²⁴

Recognizing the limits of patient self-examinations. Comorbidities such as visual impairment and reduced joint mobility often preclude patients from completing rigorous self-examinations of the foot, which is especially critical while collecting subjective history from the patient during triage of inflammation. A caregiver or spouse can help inspect the foot during outreach and provide additional context.³⁶

Interpreting a benign foot on examination. Because RTM has been demonstrated to detect inflammation preceding a foot ulcer as many as 5 weeks before presentation to the clinic, some veterans may have few signs or symptoms of acute risk during examination. Often, the damage is to subcutaneous tissue resulting from repetitive microtrauma. Research suggests that clinical examination in these cases is often unreliable for identifying the earliest signs of risk, such as palpation to identify subtle temperature changes secondary to inflammation.³⁷ If a patient has refractory inflammation requiring examination and presents with an otherwise unremarkable foot, it is an opportunity to evaluate whether the patient’s shoewear remains appropriate or has worn out, to communicate the veteran’s ongoing elevated risk, and to educate on the importance of diligence in daily foot self-examinations, daily use of the foot temperature monitoring, and continued off-loading until the inflammation resolves.

Communicating the distinction between healing and remission. Although healing is the goal of wound care, patients should be educated that the underlying disease remains after epithelialization. In some cases, tissue deep to the skin has not completed remodeling, and the patient is at acute risk of recurrence. Remission is a powerful metaphor that better describes the patient’s ongoing risk to encourage continued healthy routines and diligent self-care.³⁸Considering the entirety of both feet for recurrence. Critical risk factors for diabetic foot complications, such as peripheral neuropathy and PAD, exist in both limbs, and patients with a history of wounds often develop new complications to different ipsilateral locations, or in as many as 48% of cases, to the contralateral foot.³⁵ For best outcomes, detected inflammation should be treated aggressively independent of whether the location coincides with an area of previous concern.

Encouraging adherence, routine, and empowerment. Advanced diabetes mellitus and neuropathy may impact a patient’s executive function, and multiple studies have reported that patients at risk for inflammatory foot diseases exhibit fatalism toward their foot care and outcomes.^39-41 Consistent education, encouragement, empowerment, and establishment of positive routines are needed to ensure high adherence with all preventive care regimens, including RTM.

Case Presentations

The following case series illustrates many of these clinical best practices and characterizes the potential benefits of RTM to veterans within the VA.

Case 1: Prevention After Healing

A veteran underwent a Chopart amputation and was recommended to use the mat after healing was perceived. Immediately on use of the study mat, the patient was found to have inflammation to the surgical incision (Figure 1). Clinical staff was alerted to the findings, and the patient was instructed to limit further walking and continue off-loading in his removable cast walker, per protocol. The inflammation of the operative foot quickly reduced, and the patient continued healing successfully, potentially avoiding incisional dehiscence and possible postoperative infection.

 

This case illustrates that patients’ wounds or surgical incisions may not be completely healed on epithelialization. In the immediate phase after closure, HCPs should consider additional protection to avoid complications. This case demonstrates that RTM can provide objective data to help guide care in that critical period.

Case 2: Identifying Preulcerative Lesions

An 88-year-old veteran had a chronic callus under the second metatarsal head. In addition to routine foot care and therapeutic shoes, he was followed with once-daily RTM. Inflammation was noted, and the veteran was seen in the podiatry clinic where debridement of the callus was performed. The difference in temperatures between feet detected by thermography prior to the clinic visits rapidly resolved after callus debridement, indicating that the underlying inflammation had subsided. RTM was used by the clinical staff to determine the appropriate time interval between clinic visits to avoid callus breakdown and subsequent ulceration.

Case 3: Extending the Clinic Into the Home

An 80-year-old veteran with T2DM and neuropathy was deemed a high-risk patient due to recurrent ulcerations to the left great toe. He was issued a RTM mat and was adherent with routine use. After nearly a year without hot-spot development, inflammation was noted (Figure 2).

Unfortunately, the patient had missed several routine foot care visits and likely that was the reason for the noted inflammation. The patient was called and became reengaged in regular visits for routine foot care. On debridement of his callus, a superficial, noninfected ulceration was discovered. Had remote monitoring not detected the inflammation and impending ulceration, the patient likely would not have been seen in the regular clinic and may have developed a wound infection, potentially resulting in a worse and more costly outcome.

Paradigm Shift to Prevention

Given the exceedingly high burden of diabetic foot complications in the VA, a paradigm shift is needed among HCPs from a culture of treatment to one of prevention. Bus and colleagues reported that in Europe, for every euro spent on ulcer prevention, 10 are spent on ulcer healing, and for every randomized clinical trial conducted on prevention, 10 are conducted on treatment.^42-44 Hicks and colleagues showed that the cost of curative care for DFUs is 5 to 30 times greater than the cost of preventive care.⁴⁵ For RTM in high-risk cohorts (ie, PAVE level 3), the number-needed-to-treat for DFU prevention may be as low as 6, assuming that a 70% reduction in incidence is possible, consistent with previous research. In the year following a DFU, costs exceed $44,000.⁹ Thus, it seems natural that future direction in diabetic foot care should emphasize prevention strategies.

Foot ulcers that become infected often lead to hospitalization and result in an increased burden to an already overburdened VA health care system. Research suggests that about two-thirds of all diabetic foot costs are attributable to inpatient management.⁴⁶ The impact of diabetic foot complications on hospital resource utilization is staggering. A 2017 study by Skrepnik analyzed the risk of hospitalization for various diseases.⁴⁷ The investigators found that the inpatient admission odds ratio (OR) for congestive heart failure was 2.6, surpassed only by DFUs (OR, 3.4) and diabetic foot infection (OR, 6.7). A 2019 point-prevalence study found that > 10% of hospital admissions have a foot-related condition as the primary or secondary reason, and the majority of these are due to foot diseases, such as ulcers, infections, and Charcot neuroarthropathy.⁴⁸

It is therefore incumbent on VA HCPs to avert wound recurrence in the interest of avoiding veteran hospitalizations and for administrators to encourage and incentivize best practices for managing the diabetic foot, with an emphasis on prevention therapies. In evaluating the financial impact of prevention with foot RTM, administrators should consider that the cost benefit is likely to be realized across the medical center, with budgets related to inpatient management likely to receive the largest returns.

Prevention has the potential to rein in costs as well as reduce strain on the hospital and clinic by preventing outcomes that require frequent visits for treatment or hospitalization. Wound treatment is very burdensome to the clinic; patients require frequent (in many cases, weekly) examinations, and chronic wounds often require hospitalization, necessitating rounding and additional coordination in care. Thus, preventing wounds or reducing their severity at presentation substantially reduces burden on the clinic, even after accounting for the modest clinical resources needed to administer preventative care. For example, a brief examination may be necessary if the inflammation detected by the study mat is secondary to a callus that must be debrided. However, if the patient was not seen until the callus had progressed to a wound, weekly follow-up and substantial clinical and budgetary resources may be required to heal the wound. Preventive care allows for substantially better patient outcomes, and the minimal time invested prevents the clinical burden of extensive wound treatment.

The success of preventive efforts relies on multidisciplinary management of this high-risk patient cohort. Often, it is the responsibility of the primary care provider to follow diabetic foot clinical reminders and appropriately refer to specialty care. Successful, open communication between PACT, PAVE, and the Podiatry Service has been shown to reduce poor outcomes, including lower extremity amputations. Traditionally, the model of preventive care has included podiatrist-driven interventions, including integrated routine foot care and comprehensive diabetic foot education. Collaboration between routine evaluation and prompt referral of at-risk patients for specialist foot care, therapeutic footwear recommendations, daily self-foot examinations, and in-home temperature monitoring are critically effective when performed consistently.

When trying to translate research science to effective clinical practice for preventing lower extremity complication, there are several important concepts. First, given the frequency of examination for patients being treated for a wound, provision of good preventive care, such as RTM, can reduce overall burden to resource-constrained clinics and improve access for patients needing to be seen. Additionally, preventive efforts extend clinical practice into the home and may reduce the need for in-clinic examinations and routine follow-up visits. Finally, there may be a sense of trust established between the clinician and patient with a positive record of adherence with preventive practices. This may translate into more productive communication and less frequent routine visits to better accommodate urgent visits and ensure podiatric care is accessible to veterans.

 

Conclusions

There is a significant opportunity to shift diabetic foot care from treatment to prevention, improving veteran outcomes and reducing resource utilization. RTM is an evidence-based and recommended but underused telemedicine solution that can catalyze this needed paradigm shift. The VA has been at the forefront of preventive foot care through the PAVE program and more recently through research and clinical application of RTM for veterans. However, as the data presented suggest, more can be done to improve veteran outcomes. More widespread adoption of evidence-based preventive technologies for the diabetic foot, such as RTM, has the potential to dramatically improve the quality of and access to care and reduce costs and burden on resource-constrained clinics.

Diabetic foot ulcers (DFUs) are devastating, common, and costly. This burden is borne disproportionately by veterans who have high prevalence of type 2 diabetes mellitus (T2DM) and other precipitating risk factors.¹ The mortality of veterans following a DFU is sobering, and ulceration is recognized as a significant marker of disease severity.

A 2017 study by Brennan and colleagues reported a 19% mortality rate within 1 year, and only 29% survive past 5 years.² DFUs are often complicated by peripheral arterial disease (PAD) and diabetic immune dysfunction, contributing to chronic wounds and infection.^3,4 About 60% of all foot ulcers become infected, and > 20% of patients with a diabetic foot infection require amputation.^5,6

A 2010 retrospective study reports that > 3,400 veterans have a diabetes-related lower extremity amputation annually, vastly surpassing the rate of amputation secondary to trauma in the Veterans Health Administration (VHA).^7,8 The inpatient costs for each amputation exceeded $60,000 in fiscal year 2010, and these amputation-related costs represent only 1 component of the total expense to the VHA attributable to diabetic foot complications.⁷ A recent systematic review by Chan and colleagues estimated mean annual costs in the year following a foot ulcer to be $44,200 to the public payer.⁹ This implies that direct expenditures for treatment of DFUs within the VHA exceeds $3 billion annually.

 

Diabetic Foot Ulcer Prevention

Given the dramatic impact of diabetic foot complications to the veteran and the US health care system, the VHA has long recognized the importance of preventive care for those at risk. In 2017 US Department of Veterans Affairs (VA) and Department of Defense issued a clinical practice guideline for the management of T2DM that recommended prophylactic foot care for early identification of any deformity or skin breakdown.¹⁰ The guidelines note that a “person who has had a foot ulcer is at lifelong risk of further ulceration,” reflecting the high rate of recurrence among all patients, including veterans. Multiple studies suggest that as many as 40% of patients experience recidivism in the first year after healing from a wound.^11-16

The VA is well equipped to deliver quality preventive care because of its innovative and long-standing PAVE (Prevention of Amputations for Veterans Everywhere) program.¹⁷ PAVE provides screening, education, appropriate footwear, and stratified care guidelines for veterans at risk for diabetes-related foot complications (Table 1). The practices encouraged by PAVE are evidence-based and synergistic with the objectives of the VA’s patient aligned care team (PACT) delivery approach.¹⁸ The granular data collected through PAVE are used to guide best practices and provide benchmarks for diabetic foot outcomes.

Unfortunately, despite PAVE guidelines requiring annual specialist foot care for at-risk veterans, a 2013 report by the VA Office of the Inspector General (OIG) found that one-third of all patients had no documentation of this minimal requirement of preventive foot care.¹⁹ Although the VA has worked to address this issue, the data hint at the missed opportunities for prevention of complications and the challenges of ensuring that a large at-risk veteran population has systematic and routine screening with access to specialist foot care.

Given the large proportion of veterans at high risk of chronic wound formation and the challenges of ensuring that this cohort receives good preventive foot care, expanding telemedicine has been suggested. Telemedicine solutions have the potential to reduce the impact of chronic wounds on overburdened clinic resources, schedules, and local and federal budgets.²⁰ Interestingly, the only preventive practice for the diabetic foot that has been proven effective through multiple randomized controlled trials and national and international clinical guidance documents is once-daily foot temperature monitoring.^21-26 Daily monitoring has the potential to reduce the burden of DFUs to veterans, improve veteran access to needed preventive care, and reduce costs incurred by the VHA treating diabetic foot complications. Yet despite a recent national guidance document detailing its appropriate use in PAVE 3 veterans, it remains underutilized.²⁷

The purpose of this review is to: (1) discuss the evidence supporting once-daily remote temperature monitoring (RTM), a telemedicine approach critical to improving both veteran access to care and diabetic foot outcomes; (2) summarize a 2017 study that presented an advanced clinical understanding of RTM use among veterans; (3) provide previously unpublished data from this study comparing high-risk VA and non-VA cohorts, highlighting the opportunity for additional focus on foot ulcer prevention within the VA; and (4) report on recent VA utilization of a RTM technology based on this research, emphasizing lessons learned and best practices.

 

Remote Temperature Monitoring

The objective of daily foot temperature monitoring is to identify impending inflammatory foot conditions, such as DFUs, infection, and acute Charcot neuroarthropathy episodes. The patient and care team then act to resolve the cause of detected inflammation before clinical presentation (prevention) and begin treatment earlier than would otherwise be possible to avoid expensive complications, such as infection (early detection). Preventive therapies are low risk to the patient and inexpensive.

RTM is recommended by multiple clinical practice guidelines, including those of the International Working Group on the Diabetic Foot, the American College of Foot and Ankle Surgeons, and the Wound Healing Society.^24-26 Its use is supported by evidence from 3 National Institutes of Health-funded and well-designed randomized controlled trials, 1 of which was additionally supported by a VA Health Services Research and Development Service Merit Award.^21-23,28 Conducted between 2004 and 2007, these studies demonstrated the potential to reduce foot ulcer incidence by as much as 85% using a dermal thermometer to identify inflammation and prompt decreased ambulation. Investigators established a clinical monitoring protocol comparing the temperatures between 6 matched locations on the left and right feet. Persistent differences in contralateral temperatures exceeding 2.2°C (4.0°F) were used as a marker for elevated risk and to initiate preventive care. Based on the encouraging results from these studies, a 2017 effectiveness review prepared for the Agency for Healthcare Research and Quality concluded that “home monitoring of foot skin temperature is effective for reducing foot ulcer incidence and recurrence.”²⁹

Accuracy of RTM

A 2017 longitudinal study (NCT02647346) has provided novel data to advance understanding of RTM for the prediction and prevention of DFUs.³⁰ This study was the first to systematically analyze the accuracy of RTM over different monitoring thresholds. The results enable practitioners to deliver risk-stratified preventive care. Policy makers can use the data from this study to weigh the cost and benefits of RTM for population health.

The multicenter trials had 129 participants from 4 VA health care systems: VA Long Beach Healthcare System in California, Miami VA Healthcare System in Florida, Phoenix VA Healthcare System in Arizona, and VA West Los Angeles Healthcare System in California. Each participant was followed for 34 weeks under standard preventive foot care and was instructed to step on a telemedicine SmartMat (Podimetrics, Inc) RTM mat for 20 seconds daily. Participants and investigators were blinded to the temperature data so that the accuracy of temperature monitoring could be assessed. All participants had a history of T2DM and healed DFU. Principal exclusion criteria included unhealed plantar wound, history of proximal lower extremity amputation (ie, above ankle), active Charcot foot disease, and comorbidities that could potentially inhibit an inflammatory response, such as end-stage renal disease, active malignancy, and immunosuppressive diseases.

The investigators reported that RTM with the study mat detected 97% of nonacute plantar DFUs using the most commonly studied threshold (sustained 2.2°C temperature difference). The lead time averaged 37 days before clinical identification of the wound under standard care. Although the false-positive rate of 57% was high, corresponding to approximately 3.0 notifications per patient per year on average in the research setting, it is important to note that this study only considered the prediction of plantar DFUs. Thus, detection of foot inflammation secondary to other conditions, such as preulcerative lesion, dorsal wound, Charcot neuroarthropathy, or foot infection, were reported as a false positive per the study’s definitions. Further, Crisologo and Lavery noted in a translational medicine summary of this research, because the intervention is noninvasive and minimally impactful to the patient and the health care system, “the potential to arrest re-ulceration is worth the perceived inconvenience to the patient.”³¹

Secondary outcomes related to adherence and ease of use were encouraging. Eighty-eight percent of participants reported that the mat was “very easy to use,” the highest possible score, and 98% were able to set up the mat for home use without difficulty. At the end of the 34-week study, more than 74% of participants remained engaged in routine use of the mat under a per-protocol assessment of adherence. These results are especially impressive given the documented poor adherence of at-risk patients to routine use of therapeutic footwear, which has been reported to be as low as 15%.³²

 

New Research

The data collected during this study has led to new research and advancements in RTM. A recent publication by Gordon and colleagues investigated whether RTM is less accurate in cohorts with perceived challenges.³³ They include patients with recently healed wounds and those with a history of partial foot amputation. There was no difference in the accuracy or lead time for either cohort relative to the entire cohort, suggesting that RTM is appropriate for monitoring patients with recently healed DFUs or partial foot amputations.

In another recent study, the data were used to derive a novel approach to monitor a single at-risk foot.³⁴ The practice of RTM has traditionally required comparing temperatures between contralaterally matched plantar locations on the feet, thus limiting its use in patients with a history of major lower extremity amputation and patients being treated for a wound, which may be bandaged or in an off-loading cast or boot. Because the risk factors for DFUs exist in both limbs, these patients are at high risk for developing complications to the contralateral foot and may benefit from preventive once-daily foot temperature monitoring. The investigators empirically derived a novel monitoring approach for patients without a contralateral control. This approach was found to predict 91% of impending plantar DFUs on average 41 days before clinical presentation with a false positive rate of 54%.

Additional Focus on Prevention

Table 2 shows previously unpublished data from a subgroup analysis between veteran and nonveteran participants in the study.²⁵ These descriptive statistics reinforce some widely held assumptions regarding the high-risk veteran population and challenge others. For example, compared with the nonveteran participants, the veteran cohort unsurprisingly had a larger ratio of male participants (P < .01), had a higher rate of cigarette use (P < .01), and was more likely to live alone (although not at a statistically significant level). Veterans in the study had body mass index, rates of alcohol use, frequency of exercise, and glucose control comparable to that of nonveterans.

The potential impact of the PAVE program is clear in several of these comparisons. Although as few as 15% of patients use therapeutic shoes routinely, PAVE ensures that the majority of veterans receive them. Nearly 95% of veterans have therapeutic shoes compared with about 80% of nonveteran participants (P < .05). Veterans also had higher ankle-brachial index results (P < .05), although on average both cohorts were within normal clinical parameters. Veterans had a significantly longer duration since healing from the most recent wound, and fewer veteran participants had a wound that healed in the 3 months prior to the study. Despite this, during the study veterans had annualized DFU incidence equal to that of nonveterans. Furthermore, veterans also had significantly higher rates of amputation prior to participation. That these critical outcomes for veterans are no better than those observed in other care environments despite PAVE suggests that approaches recommended via PAVE alone are insufficient to significantly arrest DFU recurrence, and even more focus on prevention in the VA may be warranted.

 

From Research to Practice

Since the publication of the 2017 study, the VHA has been at the vanguard of translating the evidence and research underlying RTM into clinical practice. A clinical guidance document governing appropriate use of RTM with the study mat was recently published by the VA Prosthetic and Sensory Aids Service in collaboration with the National Podiatry Program office.²⁷ This guidance document recommends once-daily RTM for at-risk veterans designated PAVE level 3. It defines roles and responsibilities required for the successful implementation of a RTM program with the study device. The document additionally presents various clinical monitoring protocols for veterans, although the protocol and thresholds used are at the discretion of the prescribing clinician and should reflect the risk profile of the veteran in question.

A staged response to inflammation has proven popular, whereby an initial high-sensitivity threshold is chosen for monitoring. The initial response is telephone outreach by a designee supplied by the clinic or device manufacturer, typically a trained registered nurse, to the veteran to collect subjective history and instruct off-loading and reduced ambulation, with a target of 50% baseline reduction in step count. Should the inflammation persist despite off-loading, an examination may be necessary to identify and resolve its cause. For recalcitrant inflammation, more targeted pressure off-loading of the affected area may be accomplished with custom orthotics, accommodative insoles, removable cast walkers, and total contact casting. After 2 to 4 weeks without signs of inflammation, the cause is deemed to have been resolved and lowered the acute risk for developing further diabetic foot complications.

More than 600 veterans have been monitored for > 1,000 patient-years—13 VA medical centers are practicing RTM with the study mat as of this writing. The monitoring program has been integrated into many veteran daily routines as evidenced by > 70% retaining full engagement after having been monitored for > 1 year. The total number of alerts/patient-years across these veterans has been 1.4, significantly lower than the 3.0 alerts/patient-year observed in the study. This is potentially due to successful interventions in response to detected inflammation, resolving inflammation, and avoiding unnecessary alerts occurring in the research setting, which did not employ interventions that resolved inflammation episodes. In the past 6 months, 68% of all inflammation detected resolved via off-loading alone without requiring further clinical intervention. In the cases that required an examination, 76% of patients reported clinically meaningful preventive care (eg, preulcerative callus was debrided, a subungual hemorrhage was treated, a foot ulcer was identified).

Organizational Best Practices

Several best practices have been cultivated related to initiating a RTM program at a new site, for promoting the success of a RTM program, and provisioning excellent preventive care to support the RTM program. Although we advise adhering to the recommendations in the VA guidance document,²⁷ the authors have observed several additional organizational best practices that are not explicitly addressed.

Partnering with PACT. Collaboration between PAVE and PACT has the potential not only to improve outcomes for patients at risk for diabetic foot complications, but also can help identify appropriate high-risk veteran candidates for preventive care with RTM who may not be followed for routine care from a specialty provider, such as a podiatrist, as highlighted by the 2013 OIG report.

Prescreening eligible patients. Several programs have used PAVE data or appointment schedules to identify and target high-risk veterans proactively. This approach has several benefits. It simplifies clinical coordination and streamlines workflow for patient identification and onboarding. It also allows those veterans at highest risk to receive needed and recommended preventive care at their next scheduled appointment. Finally, if PAVE data are used to identify eligible patients, it has the added benefit of ensuring a baseline level of telemedicine preventive foot care for veterans who have become lost to follow-up and have not been seen recently for a routine foot examination.

Implementing foot monitoring during wound treatment. Recent research has expanded the reach of once-daily RTM with the mat to patients being treated for a wound to only 1 foot. This practice has 2 benefits: The patient is able to establish a preventive routine before healing, an important advantage because research strongly suggests that recurrence is most likely in the first months after healing. Second, 48% of patients with a history of DFUs will develop new wounds to the contralateral foot because risk factors, such as neuropathy and peripheral arterial disease, exist in both limbs.³⁵ Furthermore, ongoing treatment for a wound to 1 foot may result in gait deviation and elevated pressure to the sound foot, additionally predisposing the veteran to complications, resulting in a high rate of wounds occurring to the unwounded foot during treatment (0.2 DFU/DFU-year).³⁴ Thus, there is potential benefit in monitoring the sound foot while undergoing treatment for a wound; further, the patient will have immediate access to the device for prevention of recurrence once the wound has resolved.

Utilizing foot monitoring as an extension of telemedicine. Many VA facilities have large geographic catchment areas, making routine follow-up difficult for veterans living in rural areas. RTM serves as an extension of the patient’s daily self-examination and the clinician’s ability to monitor patients with objective information daily. The veterans using the system become more invested and feel as though they are taking an active role in their health care.

Investing in ongoing medical education. Multidisciplinary education sessions reviewing supporting clinical data and resultant clinical practice guidelines raise awareness for those providers and trainees unaware of preventive best practices for the diabetic foot, including those related to foot RTM. These sessions also are helpful for those familiar with foot temperature monitoring or who are responsible for administration of an ongoing program to remain current with contemporary best practices and to discuss improvements for patient care. Familiarity also can help address clinical inertia when benefits and evidence are clearly communicated with health care providers (HCPs).

 

Clinical Best Practices

Treating preulcerative lesions urgently and aggressively. Callus and other preulcerative lesions often cause progressive tissue damage and poor outcomes. When identified, these lesions should be promptly treated to ensure best outcomes.²⁴

Recognizing the limits of patient self-examinations. Comorbidities such as visual impairment and reduced joint mobility often preclude patients from completing rigorous self-examinations of the foot, which is especially critical while collecting subjective history from the patient during triage of inflammation. A caregiver or spouse can help inspect the foot during outreach and provide additional context.³⁶

Interpreting a benign foot on examination. Because RTM has been demonstrated to detect inflammation preceding a foot ulcer as many as 5 weeks before presentation to the clinic, some veterans may have few signs or symptoms of acute risk during examination. Often, the damage is to subcutaneous tissue resulting from repetitive microtrauma. Research suggests that clinical examination in these cases is often unreliable for identifying the earliest signs of risk, such as palpation to identify subtle temperature changes secondary to inflammation.³⁷ If a patient has refractory inflammation requiring examination and presents with an otherwise unremarkable foot, it is an opportunity to evaluate whether the patient’s shoewear remains appropriate or has worn out, to communicate the veteran’s ongoing elevated risk, and to educate on the importance of diligence in daily foot self-examinations, daily use of the foot temperature monitoring, and continued off-loading until the inflammation resolves.

Communicating the distinction between healing and remission. Although healing is the goal of wound care, patients should be educated that the underlying disease remains after epithelialization. In some cases, tissue deep to the skin has not completed remodeling, and the patient is at acute risk of recurrence. Remission is a powerful metaphor that better describes the patient’s ongoing risk to encourage continued healthy routines and diligent self-care.³⁸Considering the entirety of both feet for recurrence. Critical risk factors for diabetic foot complications, such as peripheral neuropathy and PAD, exist in both limbs, and patients with a history of wounds often develop new complications to different ipsilateral locations, or in as many as 48% of cases, to the contralateral foot.³⁵ For best outcomes, detected inflammation should be treated aggressively independent of whether the location coincides with an area of previous concern.

Encouraging adherence, routine, and empowerment. Advanced diabetes mellitus and neuropathy may impact a patient’s executive function, and multiple studies have reported that patients at risk for inflammatory foot diseases exhibit fatalism toward their foot care and outcomes.^39-41 Consistent education, encouragement, empowerment, and establishment of positive routines are needed to ensure high adherence with all preventive care regimens, including RTM.

Case Presentations

The following case series illustrates many of these clinical best practices and characterizes the potential benefits of RTM to veterans within the VA.

Case 1: Prevention After Healing

A veteran underwent a Chopart amputation and was recommended to use the mat after healing was perceived. Immediately on use of the study mat, the patient was found to have inflammation to the surgical incision (Figure 1). Clinical staff was alerted to the findings, and the patient was instructed to limit further walking and continue off-loading in his removable cast walker, per protocol. The inflammation of the operative foot quickly reduced, and the patient continued healing successfully, potentially avoiding incisional dehiscence and possible postoperative infection.

 

This case illustrates that patients’ wounds or surgical incisions may not be completely healed on epithelialization. In the immediate phase after closure, HCPs should consider additional protection to avoid complications. This case demonstrates that RTM can provide objective data to help guide care in that critical period.

Case 2: Identifying Preulcerative Lesions

An 88-year-old veteran had a chronic callus under the second metatarsal head. In addition to routine foot care and therapeutic shoes, he was followed with once-daily RTM. Inflammation was noted, and the veteran was seen in the podiatry clinic where debridement of the callus was performed. The difference in temperatures between feet detected by thermography prior to the clinic visits rapidly resolved after callus debridement, indicating that the underlying inflammation had subsided. RTM was used by the clinical staff to determine the appropriate time interval between clinic visits to avoid callus breakdown and subsequent ulceration.

Case 3: Extending the Clinic Into the Home

An 80-year-old veteran with T2DM and neuropathy was deemed a high-risk patient due to recurrent ulcerations to the left great toe. He was issued a RTM mat and was adherent with routine use. After nearly a year without hot-spot development, inflammation was noted (Figure 2).

Unfortunately, the patient had missed several routine foot care visits and likely that was the reason for the noted inflammation. The patient was called and became reengaged in regular visits for routine foot care. On debridement of his callus, a superficial, noninfected ulceration was discovered. Had remote monitoring not detected the inflammation and impending ulceration, the patient likely would not have been seen in the regular clinic and may have developed a wound infection, potentially resulting in a worse and more costly outcome.

Paradigm Shift to Prevention

Given the exceedingly high burden of diabetic foot complications in the VA, a paradigm shift is needed among HCPs from a culture of treatment to one of prevention. Bus and colleagues reported that in Europe, for every euro spent on ulcer prevention, 10 are spent on ulcer healing, and for every randomized clinical trial conducted on prevention, 10 are conducted on treatment.^42-44 Hicks and colleagues showed that the cost of curative care for DFUs is 5 to 30 times greater than the cost of preventive care.⁴⁵ For RTM in high-risk cohorts (ie, PAVE level 3), the number-needed-to-treat for DFU prevention may be as low as 6, assuming that a 70% reduction in incidence is possible, consistent with previous research. In the year following a DFU, costs exceed $44,000.⁹ Thus, it seems natural that future direction in diabetic foot care should emphasize prevention strategies.

Foot ulcers that become infected often lead to hospitalization and result in an increased burden to an already overburdened VA health care system. Research suggests that about two-thirds of all diabetic foot costs are attributable to inpatient management.⁴⁶ The impact of diabetic foot complications on hospital resource utilization is staggering. A 2017 study by Skrepnik analyzed the risk of hospitalization for various diseases.⁴⁷ The investigators found that the inpatient admission odds ratio (OR) for congestive heart failure was 2.6, surpassed only by DFUs (OR, 3.4) and diabetic foot infection (OR, 6.7). A 2019 point-prevalence study found that > 10% of hospital admissions have a foot-related condition as the primary or secondary reason, and the majority of these are due to foot diseases, such as ulcers, infections, and Charcot neuroarthropathy.⁴⁸

It is therefore incumbent on VA HCPs to avert wound recurrence in the interest of avoiding veteran hospitalizations and for administrators to encourage and incentivize best practices for managing the diabetic foot, with an emphasis on prevention therapies. In evaluating the financial impact of prevention with foot RTM, administrators should consider that the cost benefit is likely to be realized across the medical center, with budgets related to inpatient management likely to receive the largest returns.

Prevention has the potential to rein in costs as well as reduce strain on the hospital and clinic by preventing outcomes that require frequent visits for treatment or hospitalization. Wound treatment is very burdensome to the clinic; patients require frequent (in many cases, weekly) examinations, and chronic wounds often require hospitalization, necessitating rounding and additional coordination in care. Thus, preventing wounds or reducing their severity at presentation substantially reduces burden on the clinic, even after accounting for the modest clinical resources needed to administer preventative care. For example, a brief examination may be necessary if the inflammation detected by the study mat is secondary to a callus that must be debrided. However, if the patient was not seen until the callus had progressed to a wound, weekly follow-up and substantial clinical and budgetary resources may be required to heal the wound. Preventive care allows for substantially better patient outcomes, and the minimal time invested prevents the clinical burden of extensive wound treatment.

The success of preventive efforts relies on multidisciplinary management of this high-risk patient cohort. Often, it is the responsibility of the primary care provider to follow diabetic foot clinical reminders and appropriately refer to specialty care. Successful, open communication between PACT, PAVE, and the Podiatry Service has been shown to reduce poor outcomes, including lower extremity amputations. Traditionally, the model of preventive care has included podiatrist-driven interventions, including integrated routine foot care and comprehensive diabetic foot education. Collaboration between routine evaluation and prompt referral of at-risk patients for specialist foot care, therapeutic footwear recommendations, daily self-foot examinations, and in-home temperature monitoring are critically effective when performed consistently.

When trying to translate research science to effective clinical practice for preventing lower extremity complication, there are several important concepts. First, given the frequency of examination for patients being treated for a wound, provision of good preventive care, such as RTM, can reduce overall burden to resource-constrained clinics and improve access for patients needing to be seen. Additionally, preventive efforts extend clinical practice into the home and may reduce the need for in-clinic examinations and routine follow-up visits. Finally, there may be a sense of trust established between the clinician and patient with a positive record of adherence with preventive practices. This may translate into more productive communication and less frequent routine visits to better accommodate urgent visits and ensure podiatric care is accessible to veterans.

 

Conclusions

There is a significant opportunity to shift diabetic foot care from treatment to prevention, improving veteran outcomes and reducing resource utilization. RTM is an evidence-based and recommended but underused telemedicine solution that can catalyze this needed paradigm shift. The VA has been at the forefront of preventive foot care through the PAVE program and more recently through research and clinical application of RTM for veterans. However, as the data presented suggest, more can be done to improve veteran outcomes. More widespread adoption of evidence-based preventive technologies for the diabetic foot, such as RTM, has the potential to dramatically improve the quality of and access to care and reduce costs and burden on resource-constrained clinics.

Diabetic foot ulcers (DFUs) are devastating, common, and costly. This burden is borne disproportionately by veterans who have high prevalence of type 2 diabetes mellitus (T2DM) and other precipitating risk factors.¹ The mortality of veterans following a DFU is sobering, and ulceration is recognized as a significant marker of disease severity.

A 2017 study by Brennan and colleagues reported a 19% mortality rate within 1 year, and only 29% survive past 5 years.² DFUs are often complicated by peripheral arterial disease (PAD) and diabetic immune dysfunction, contributing to chronic wounds and infection.^3,4 About 60% of all foot ulcers become infected, and > 20% of patients with a diabetic foot infection require amputation.^5,6

A 2010 retrospective study reports that > 3,400 veterans have a diabetes-related lower extremity amputation annually, vastly surpassing the rate of amputation secondary to trauma in the Veterans Health Administration (VHA).^7,8 The inpatient costs for each amputation exceeded $60,000 in fiscal year 2010, and these amputation-related costs represent only 1 component of the total expense to the VHA attributable to diabetic foot complications.⁷ A recent systematic review by Chan and colleagues estimated mean annual costs in the year following a foot ulcer to be $44,200 to the public payer.⁹ This implies that direct expenditures for treatment of DFUs within the VHA exceeds $3 billion annually.

 

Diabetic Foot Ulcer Prevention

Given the dramatic impact of diabetic foot complications to the veteran and the US health care system, the VHA has long recognized the importance of preventive care for those at risk. In 2017 US Department of Veterans Affairs (VA) and Department of Defense issued a clinical practice guideline for the management of T2DM that recommended prophylactic foot care for early identification of any deformity or skin breakdown.¹⁰ The guidelines note that a “person who has had a foot ulcer is at lifelong risk of further ulceration,” reflecting the high rate of recurrence among all patients, including veterans. Multiple studies suggest that as many as 40% of patients experience recidivism in the first year after healing from a wound.^11-16

The VA is well equipped to deliver quality preventive care because of its innovative and long-standing PAVE (Prevention of Amputations for Veterans Everywhere) program.¹⁷ PAVE provides screening, education, appropriate footwear, and stratified care guidelines for veterans at risk for diabetes-related foot complications (Table 1). The practices encouraged by PAVE are evidence-based and synergistic with the objectives of the VA’s patient aligned care team (PACT) delivery approach.¹⁸ The granular data collected through PAVE are used to guide best practices and provide benchmarks for diabetic foot outcomes.

Unfortunately, despite PAVE guidelines requiring annual specialist foot care for at-risk veterans, a 2013 report by the VA Office of the Inspector General (OIG) found that one-third of all patients had no documentation of this minimal requirement of preventive foot care.¹⁹ Although the VA has worked to address this issue, the data hint at the missed opportunities for prevention of complications and the challenges of ensuring that a large at-risk veteran population has systematic and routine screening with access to specialist foot care.

Given the large proportion of veterans at high risk of chronic wound formation and the challenges of ensuring that this cohort receives good preventive foot care, expanding telemedicine has been suggested. Telemedicine solutions have the potential to reduce the impact of chronic wounds on overburdened clinic resources, schedules, and local and federal budgets.²⁰ Interestingly, the only preventive practice for the diabetic foot that has been proven effective through multiple randomized controlled trials and national and international clinical guidance documents is once-daily foot temperature monitoring.^21-26 Daily monitoring has the potential to reduce the burden of DFUs to veterans, improve veteran access to needed preventive care, and reduce costs incurred by the VHA treating diabetic foot complications. Yet despite a recent national guidance document detailing its appropriate use in PAVE 3 veterans, it remains underutilized.²⁷

The purpose of this review is to: (1) discuss the evidence supporting once-daily remote temperature monitoring (RTM), a telemedicine approach critical to improving both veteran access to care and diabetic foot outcomes; (2) summarize a 2017 study that presented an advanced clinical understanding of RTM use among veterans; (3) provide previously unpublished data from this study comparing high-risk VA and non-VA cohorts, highlighting the opportunity for additional focus on foot ulcer prevention within the VA; and (4) report on recent VA utilization of a RTM technology based on this research, emphasizing lessons learned and best practices.

 

Remote Temperature Monitoring

The objective of daily foot temperature monitoring is to identify impending inflammatory foot conditions, such as DFUs, infection, and acute Charcot neuroarthropathy episodes. The patient and care team then act to resolve the cause of detected inflammation before clinical presentation (prevention) and begin treatment earlier than would otherwise be possible to avoid expensive complications, such as infection (early detection). Preventive therapies are low risk to the patient and inexpensive.

RTM is recommended by multiple clinical practice guidelines, including those of the International Working Group on the Diabetic Foot, the American College of Foot and Ankle Surgeons, and the Wound Healing Society.^24-26 Its use is supported by evidence from 3 National Institutes of Health-funded and well-designed randomized controlled trials, 1 of which was additionally supported by a VA Health Services Research and Development Service Merit Award.^21-23,28 Conducted between 2004 and 2007, these studies demonstrated the potential to reduce foot ulcer incidence by as much as 85% using a dermal thermometer to identify inflammation and prompt decreased ambulation. Investigators established a clinical monitoring protocol comparing the temperatures between 6 matched locations on the left and right feet. Persistent differences in contralateral temperatures exceeding 2.2°C (4.0°F) were used as a marker for elevated risk and to initiate preventive care. Based on the encouraging results from these studies, a 2017 effectiveness review prepared for the Agency for Healthcare Research and Quality concluded that “home monitoring of foot skin temperature is effective for reducing foot ulcer incidence and recurrence.”²⁹

Accuracy of RTM

A 2017 longitudinal study (NCT02647346) has provided novel data to advance understanding of RTM for the prediction and prevention of DFUs.³⁰ This study was the first to systematically analyze the accuracy of RTM over different monitoring thresholds. The results enable practitioners to deliver risk-stratified preventive care. Policy makers can use the data from this study to weigh the cost and benefits of RTM for population health.

The multicenter trials had 129 participants from 4 VA health care systems: VA Long Beach Healthcare System in California, Miami VA Healthcare System in Florida, Phoenix VA Healthcare System in Arizona, and VA West Los Angeles Healthcare System in California. Each participant was followed for 34 weeks under standard preventive foot care and was instructed to step on a telemedicine SmartMat (Podimetrics, Inc) RTM mat for 20 seconds daily. Participants and investigators were blinded to the temperature data so that the accuracy of temperature monitoring could be assessed. All participants had a history of T2DM and healed DFU. Principal exclusion criteria included unhealed plantar wound, history of proximal lower extremity amputation (ie, above ankle), active Charcot foot disease, and comorbidities that could potentially inhibit an inflammatory response, such as end-stage renal disease, active malignancy, and immunosuppressive diseases.

The investigators reported that RTM with the study mat detected 97% of nonacute plantar DFUs using the most commonly studied threshold (sustained 2.2°C temperature difference). The lead time averaged 37 days before clinical identification of the wound under standard care. Although the false-positive rate of 57% was high, corresponding to approximately 3.0 notifications per patient per year on average in the research setting, it is important to note that this study only considered the prediction of plantar DFUs. Thus, detection of foot inflammation secondary to other conditions, such as preulcerative lesion, dorsal wound, Charcot neuroarthropathy, or foot infection, were reported as a false positive per the study’s definitions. Further, Crisologo and Lavery noted in a translational medicine summary of this research, because the intervention is noninvasive and minimally impactful to the patient and the health care system, “the potential to arrest re-ulceration is worth the perceived inconvenience to the patient.”³¹

Secondary outcomes related to adherence and ease of use were encouraging. Eighty-eight percent of participants reported that the mat was “very easy to use,” the highest possible score, and 98% were able to set up the mat for home use without difficulty. At the end of the 34-week study, more than 74% of participants remained engaged in routine use of the mat under a per-protocol assessment of adherence. These results are especially impressive given the documented poor adherence of at-risk patients to routine use of therapeutic footwear, which has been reported to be as low as 15%.³²

 

New Research

The data collected during this study has led to new research and advancements in RTM. A recent publication by Gordon and colleagues investigated whether RTM is less accurate in cohorts with perceived challenges.³³ They include patients with recently healed wounds and those with a history of partial foot amputation. There was no difference in the accuracy or lead time for either cohort relative to the entire cohort, suggesting that RTM is appropriate for monitoring patients with recently healed DFUs or partial foot amputations.

In another recent study, the data were used to derive a novel approach to monitor a single at-risk foot.³⁴ The practice of RTM has traditionally required comparing temperatures between contralaterally matched plantar locations on the feet, thus limiting its use in patients with a history of major lower extremity amputation and patients being treated for a wound, which may be bandaged or in an off-loading cast or boot. Because the risk factors for DFUs exist in both limbs, these patients are at high risk for developing complications to the contralateral foot and may benefit from preventive once-daily foot temperature monitoring. The investigators empirically derived a novel monitoring approach for patients without a contralateral control. This approach was found to predict 91% of impending plantar DFUs on average 41 days before clinical presentation with a false positive rate of 54%.

Additional Focus on Prevention

Table 2 shows previously unpublished data from a subgroup analysis between veteran and nonveteran participants in the study.²⁵ These descriptive statistics reinforce some widely held assumptions regarding the high-risk veteran population and challenge others. For example, compared with the nonveteran participants, the veteran cohort unsurprisingly had a larger ratio of male participants (P < .01), had a higher rate of cigarette use (P < .01), and was more likely to live alone (although not at a statistically significant level). Veterans in the study had body mass index, rates of alcohol use, frequency of exercise, and glucose control comparable to that of nonveterans.

The potential impact of the PAVE program is clear in several of these comparisons. Although as few as 15% of patients use therapeutic shoes routinely, PAVE ensures that the majority of veterans receive them. Nearly 95% of veterans have therapeutic shoes compared with about 80% of nonveteran participants (P < .05). Veterans also had higher ankle-brachial index results (P < .05), although on average both cohorts were within normal clinical parameters. Veterans had a significantly longer duration since healing from the most recent wound, and fewer veteran participants had a wound that healed in the 3 months prior to the study. Despite this, during the study veterans had annualized DFU incidence equal to that of nonveterans. Furthermore, veterans also had significantly higher rates of amputation prior to participation. That these critical outcomes for veterans are no better than those observed in other care environments despite PAVE suggests that approaches recommended via PAVE alone are insufficient to significantly arrest DFU recurrence, and even more focus on prevention in the VA may be warranted.

 

From Research to Practice

Since the publication of the 2017 study, the VHA has been at the vanguard of translating the evidence and research underlying RTM into clinical practice. A clinical guidance document governing appropriate use of RTM with the study mat was recently published by the VA Prosthetic and Sensory Aids Service in collaboration with the National Podiatry Program office.²⁷ This guidance document recommends once-daily RTM for at-risk veterans designated PAVE level 3. It defines roles and responsibilities required for the successful implementation of a RTM program with the study device. The document additionally presents various clinical monitoring protocols for veterans, although the protocol and thresholds used are at the discretion of the prescribing clinician and should reflect the risk profile of the veteran in question.

A staged response to inflammation has proven popular, whereby an initial high-sensitivity threshold is chosen for monitoring. The initial response is telephone outreach by a designee supplied by the clinic or device manufacturer, typically a trained registered nurse, to the veteran to collect subjective history and instruct off-loading and reduced ambulation, with a target of 50% baseline reduction in step count. Should the inflammation persist despite off-loading, an examination may be necessary to identify and resolve its cause. For recalcitrant inflammation, more targeted pressure off-loading of the affected area may be accomplished with custom orthotics, accommodative insoles, removable cast walkers, and total contact casting. After 2 to 4 weeks without signs of inflammation, the cause is deemed to have been resolved and lowered the acute risk for developing further diabetic foot complications.

More than 600 veterans have been monitored for > 1,000 patient-years—13 VA medical centers are practicing RTM with the study mat as of this writing. The monitoring program has been integrated into many veteran daily routines as evidenced by > 70% retaining full engagement after having been monitored for > 1 year. The total number of alerts/patient-years across these veterans has been 1.4, significantly lower than the 3.0 alerts/patient-year observed in the study. This is potentially due to successful interventions in response to detected inflammation, resolving inflammation, and avoiding unnecessary alerts occurring in the research setting, which did not employ interventions that resolved inflammation episodes. In the past 6 months, 68% of all inflammation detected resolved via off-loading alone without requiring further clinical intervention. In the cases that required an examination, 76% of patients reported clinically meaningful preventive care (eg, preulcerative callus was debrided, a subungual hemorrhage was treated, a foot ulcer was identified).

Organizational Best Practices

Several best practices have been cultivated related to initiating a RTM program at a new site, for promoting the success of a RTM program, and provisioning excellent preventive care to support the RTM program. Although we advise adhering to the recommendations in the VA guidance document,²⁷ the authors have observed several additional organizational best practices that are not explicitly addressed.

Partnering with PACT. Collaboration between PAVE and PACT has the potential not only to improve outcomes for patients at risk for diabetic foot complications, but also can help identify appropriate high-risk veteran candidates for preventive care with RTM who may not be followed for routine care from a specialty provider, such as a podiatrist, as highlighted by the 2013 OIG report.

Prescreening eligible patients. Several programs have used PAVE data or appointment schedules to identify and target high-risk veterans proactively. This approach has several benefits. It simplifies clinical coordination and streamlines workflow for patient identification and onboarding. It also allows those veterans at highest risk to receive needed and recommended preventive care at their next scheduled appointment. Finally, if PAVE data are used to identify eligible patients, it has the added benefit of ensuring a baseline level of telemedicine preventive foot care for veterans who have become lost to follow-up and have not been seen recently for a routine foot examination.

Implementing foot monitoring during wound treatment. Recent research has expanded the reach of once-daily RTM with the mat to patients being treated for a wound to only 1 foot. This practice has 2 benefits: The patient is able to establish a preventive routine before healing, an important advantage because research strongly suggests that recurrence is most likely in the first months after healing. Second, 48% of patients with a history of DFUs will develop new wounds to the contralateral foot because risk factors, such as neuropathy and peripheral arterial disease, exist in both limbs.³⁵ Furthermore, ongoing treatment for a wound to 1 foot may result in gait deviation and elevated pressure to the sound foot, additionally predisposing the veteran to complications, resulting in a high rate of wounds occurring to the unwounded foot during treatment (0.2 DFU/DFU-year).³⁴ Thus, there is potential benefit in monitoring the sound foot while undergoing treatment for a wound; further, the patient will have immediate access to the device for prevention of recurrence once the wound has resolved.

Utilizing foot monitoring as an extension of telemedicine. Many VA facilities have large geographic catchment areas, making routine follow-up difficult for veterans living in rural areas. RTM serves as an extension of the patient’s daily self-examination and the clinician’s ability to monitor patients with objective information daily. The veterans using the system become more invested and feel as though they are taking an active role in their health care.

Investing in ongoing medical education. Multidisciplinary education sessions reviewing supporting clinical data and resultant clinical practice guidelines raise awareness for those providers and trainees unaware of preventive best practices for the diabetic foot, including those related to foot RTM. These sessions also are helpful for those familiar with foot temperature monitoring or who are responsible for administration of an ongoing program to remain current with contemporary best practices and to discuss improvements for patient care. Familiarity also can help address clinical inertia when benefits and evidence are clearly communicated with health care providers (HCPs).

 

Clinical Best Practices

Treating preulcerative lesions urgently and aggressively. Callus and other preulcerative lesions often cause progressive tissue damage and poor outcomes. When identified, these lesions should be promptly treated to ensure best outcomes.²⁴

Recognizing the limits of patient self-examinations. Comorbidities such as visual impairment and reduced joint mobility often preclude patients from completing rigorous self-examinations of the foot, which is especially critical while collecting subjective history from the patient during triage of inflammation. A caregiver or spouse can help inspect the foot during outreach and provide additional context.³⁶

Interpreting a benign foot on examination. Because RTM has been demonstrated to detect inflammation preceding a foot ulcer as many as 5 weeks before presentation to the clinic, some veterans may have few signs or symptoms of acute risk during examination. Often, the damage is to subcutaneous tissue resulting from repetitive microtrauma. Research suggests that clinical examination in these cases is often unreliable for identifying the earliest signs of risk, such as palpation to identify subtle temperature changes secondary to inflammation.³⁷ If a patient has refractory inflammation requiring examination and presents with an otherwise unremarkable foot, it is an opportunity to evaluate whether the patient’s shoewear remains appropriate or has worn out, to communicate the veteran’s ongoing elevated risk, and to educate on the importance of diligence in daily foot self-examinations, daily use of the foot temperature monitoring, and continued off-loading until the inflammation resolves.

Communicating the distinction between healing and remission. Although healing is the goal of wound care, patients should be educated that the underlying disease remains after epithelialization. In some cases, tissue deep to the skin has not completed remodeling, and the patient is at acute risk of recurrence. Remission is a powerful metaphor that better describes the patient’s ongoing risk to encourage continued healthy routines and diligent self-care.³⁸Considering the entirety of both feet for recurrence. Critical risk factors for diabetic foot complications, such as peripheral neuropathy and PAD, exist in both limbs, and patients with a history of wounds often develop new complications to different ipsilateral locations, or in as many as 48% of cases, to the contralateral foot.³⁵ For best outcomes, detected inflammation should be treated aggressively independent of whether the location coincides with an area of previous concern.

Encouraging adherence, routine, and empowerment. Advanced diabetes mellitus and neuropathy may impact a patient’s executive function, and multiple studies have reported that patients at risk for inflammatory foot diseases exhibit fatalism toward their foot care and outcomes.^39-41 Consistent education, encouragement, empowerment, and establishment of positive routines are needed to ensure high adherence with all preventive care regimens, including RTM.

Case Presentations

The following case series illustrates many of these clinical best practices and characterizes the potential benefits of RTM to veterans within the VA.

Case 1: Prevention After Healing

A veteran underwent a Chopart amputation and was recommended to use the mat after healing was perceived. Immediately on use of the study mat, the patient was found to have inflammation to the surgical incision (Figure 1). Clinical staff was alerted to the findings, and the patient was instructed to limit further walking and continue off-loading in his removable cast walker, per protocol. The inflammation of the operative foot quickly reduced, and the patient continued healing successfully, potentially avoiding incisional dehiscence and possible postoperative infection.

 

This case illustrates that patients’ wounds or surgical incisions may not be completely healed on epithelialization. In the immediate phase after closure, HCPs should consider additional protection to avoid complications. This case demonstrates that RTM can provide objective data to help guide care in that critical period.

Case 2: Identifying Preulcerative Lesions

An 88-year-old veteran had a chronic callus under the second metatarsal head. In addition to routine foot care and therapeutic shoes, he was followed with once-daily RTM. Inflammation was noted, and the veteran was seen in the podiatry clinic where debridement of the callus was performed. The difference in temperatures between feet detected by thermography prior to the clinic visits rapidly resolved after callus debridement, indicating that the underlying inflammation had subsided. RTM was used by the clinical staff to determine the appropriate time interval between clinic visits to avoid callus breakdown and subsequent ulceration.

Case 3: Extending the Clinic Into the Home

An 80-year-old veteran with T2DM and neuropathy was deemed a high-risk patient due to recurrent ulcerations to the left great toe. He was issued a RTM mat and was adherent with routine use. After nearly a year without hot-spot development, inflammation was noted (Figure 2).

Unfortunately, the patient had missed several routine foot care visits and likely that was the reason for the noted inflammation. The patient was called and became reengaged in regular visits for routine foot care. On debridement of his callus, a superficial, noninfected ulceration was discovered. Had remote monitoring not detected the inflammation and impending ulceration, the patient likely would not have been seen in the regular clinic and may have developed a wound infection, potentially resulting in a worse and more costly outcome.

Paradigm Shift to Prevention

Given the exceedingly high burden of diabetic foot complications in the VA, a paradigm shift is needed among HCPs from a culture of treatment to one of prevention. Bus and colleagues reported that in Europe, for every euro spent on ulcer prevention, 10 are spent on ulcer healing, and for every randomized clinical trial conducted on prevention, 10 are conducted on treatment.^42-44 Hicks and colleagues showed that the cost of curative care for DFUs is 5 to 30 times greater than the cost of preventive care.⁴⁵ For RTM in high-risk cohorts (ie, PAVE level 3), the number-needed-to-treat for DFU prevention may be as low as 6, assuming that a 70% reduction in incidence is possible, consistent with previous research. In the year following a DFU, costs exceed $44,000.⁹ Thus, it seems natural that future direction in diabetic foot care should emphasize prevention strategies.

Foot ulcers that become infected often lead to hospitalization and result in an increased burden to an already overburdened VA health care system. Research suggests that about two-thirds of all diabetic foot costs are attributable to inpatient management.⁴⁶ The impact of diabetic foot complications on hospital resource utilization is staggering. A 2017 study by Skrepnik analyzed the risk of hospitalization for various diseases.⁴⁷ The investigators found that the inpatient admission odds ratio (OR) for congestive heart failure was 2.6, surpassed only by DFUs (OR, 3.4) and diabetic foot infection (OR, 6.7). A 2019 point-prevalence study found that > 10% of hospital admissions have a foot-related condition as the primary or secondary reason, and the majority of these are due to foot diseases, such as ulcers, infections, and Charcot neuroarthropathy.⁴⁸

It is therefore incumbent on VA HCPs to avert wound recurrence in the interest of avoiding veteran hospitalizations and for administrators to encourage and incentivize best practices for managing the diabetic foot, with an emphasis on prevention therapies. In evaluating the financial impact of prevention with foot RTM, administrators should consider that the cost benefit is likely to be realized across the medical center, with budgets related to inpatient management likely to receive the largest returns.

Prevention has the potential to rein in costs as well as reduce strain on the hospital and clinic by preventing outcomes that require frequent visits for treatment or hospitalization. Wound treatment is very burdensome to the clinic; patients require frequent (in many cases, weekly) examinations, and chronic wounds often require hospitalization, necessitating rounding and additional coordination in care. Thus, preventing wounds or reducing their severity at presentation substantially reduces burden on the clinic, even after accounting for the modest clinical resources needed to administer preventative care. For example, a brief examination may be necessary if the inflammation detected by the study mat is secondary to a callus that must be debrided. However, if the patient was not seen until the callus had progressed to a wound, weekly follow-up and substantial clinical and budgetary resources may be required to heal the wound. Preventive care allows for substantially better patient outcomes, and the minimal time invested prevents the clinical burden of extensive wound treatment.

The success of preventive efforts relies on multidisciplinary management of this high-risk patient cohort. Often, it is the responsibility of the primary care provider to follow diabetic foot clinical reminders and appropriately refer to specialty care. Successful, open communication between PACT, PAVE, and the Podiatry Service has been shown to reduce poor outcomes, including lower extremity amputations. Traditionally, the model of preventive care has included podiatrist-driven interventions, including integrated routine foot care and comprehensive diabetic foot education. Collaboration between routine evaluation and prompt referral of at-risk patients for specialist foot care, therapeutic footwear recommendations, daily self-foot examinations, and in-home temperature monitoring are critically effective when performed consistently.

When trying to translate research science to effective clinical practice for preventing lower extremity complication, there are several important concepts. First, given the frequency of examination for patients being treated for a wound, provision of good preventive care, such as RTM, can reduce overall burden to resource-constrained clinics and improve access for patients needing to be seen. Additionally, preventive efforts extend clinical practice into the home and may reduce the need for in-clinic examinations and routine follow-up visits. Finally, there may be a sense of trust established between the clinician and patient with a positive record of adherence with preventive practices. This may translate into more productive communication and less frequent routine visits to better accommodate urgent visits and ensure podiatric care is accessible to veterans.

 

Conclusions

There is a significant opportunity to shift diabetic foot care from treatment to prevention, improving veteran outcomes and reducing resource utilization. RTM is an evidence-based and recommended but underused telemedicine solution that can catalyze this needed paradigm shift. The VA has been at the forefront of preventive foot care through the PAVE program and more recently through research and clinical application of RTM for veterans. However, as the data presented suggest, more can be done to improve veteran outcomes. More widespread adoption of evidence-based preventive technologies for the diabetic foot, such as RTM, has the potential to dramatically improve the quality of and access to care and reduce costs and burden on resource-constrained clinics.

To the Editor:

Nail biopsy is an important surgical procedure for diagnosis of nail pathology. YouTube has become a potential instrument for physicians and patients to learn about medical procedures.^1,2 However, the sources, content, and quality of the information available have not been fully studied or characterized. Our objective was to analyze the efficiency of information and quality of YouTube videos on nail biopsies. We hypothesized that the quality of patient education and physician training videos would be unrepresentative on YouTube.

The term nail biopsy was searched on January 29, 2019, and filtered by relevance and rating using the default YouTube algorithm. Data were collected from the top 40 hits for the search term and filter coupling. All videos were viewed and sorted for nail biopsy procedures, and then those videos were categorized as being produced by a physician or other health care provider. The US medical board status of each physician videographer was determined using the American Board of Medical Specialties database.³ DISCERN criteria for assessing consumer health care information⁴ were used to interpret the videos by researchers (S.I. and S.R.L.) in this study.

From the queried search term collection, only 10 videos (1,023,423 combined views) were analyzed in this study (eTable). Although the other resulting videos were tagged as nail biopsy, they were excluded due to irrelevant content (eg, patient blogs, PowerPoints, nail avulsions). The mean age of the videos was 4 years (range, 4 days to 11 years), with a mean video length of 3.30 minutes (range, 49 seconds to 9.03 minutes). Four of 10 videos were performed for longitudinal melanonychia, and 5 of 10 videos were performed for melanonychia, clinically consistent with subungual hematoma. Dermatologists, plastic surgeons, and podiatrists produced the majority of the nail biopsy videos. The overall mean DISCERN rating was 1.60/5.00 (range, 1–3), meaning that the quality of content on nail biopsies was poor. This low DISCERN score signifies poor consumer health information. Video 2 (published in 2015) received a DISCERN score of 2 and received almost 1 million views, which is likely because the specific channel has a well-established subscriber pool (4.9 million subscribers). The highest DISCERN score of 3, demonstrating a tangential shave biopsy, was given to video 4 (published in 2010) and only received about 17,400 views (56 subscribers). Additionally, many videos lacked important information about the procedure. For instance, only 3 of 10 videos demonstrated the anesthetic technique and only 5 videos showed repair methods.

YouTube is an electronic learning source for general information; however, the content and quality of information on nail biopsy is not updated, reliable, or abundant. Patients undergoing nail biopsies are unlikely to find reliable and comprehensible information on YouTube; thus, there is a strong need for patient education in this area. In addition, physicians who did not learn to perform a nail biopsy during training are unlikely to learn this procedure from YouTube. Therefore, there is an unmet need for an outlet that will provide updated reliable content on nail biopsies geared toward both patients and physicians.

To the Editor:

Nail biopsy is an important surgical procedure for diagnosis of nail pathology. YouTube has become a potential instrument for physicians and patients to learn about medical procedures.^1,2 However, the sources, content, and quality of the information available have not been fully studied or characterized. Our objective was to analyze the efficiency of information and quality of YouTube videos on nail biopsies. We hypothesized that the quality of patient education and physician training videos would be unrepresentative on YouTube.

The term nail biopsy was searched on January 29, 2019, and filtered by relevance and rating using the default YouTube algorithm. Data were collected from the top 40 hits for the search term and filter coupling. All videos were viewed and sorted for nail biopsy procedures, and then those videos were categorized as being produced by a physician or other health care provider. The US medical board status of each physician videographer was determined using the American Board of Medical Specialties database.³ DISCERN criteria for assessing consumer health care information⁴ were used to interpret the videos by researchers (S.I. and S.R.L.) in this study.

From the queried search term collection, only 10 videos (1,023,423 combined views) were analyzed in this study (eTable). Although the other resulting videos were tagged as nail biopsy, they were excluded due to irrelevant content (eg, patient blogs, PowerPoints, nail avulsions). The mean age of the videos was 4 years (range, 4 days to 11 years), with a mean video length of 3.30 minutes (range, 49 seconds to 9.03 minutes). Four of 10 videos were performed for longitudinal melanonychia, and 5 of 10 videos were performed for melanonychia, clinically consistent with subungual hematoma. Dermatologists, plastic surgeons, and podiatrists produced the majority of the nail biopsy videos. The overall mean DISCERN rating was 1.60/5.00 (range, 1–3), meaning that the quality of content on nail biopsies was poor. This low DISCERN score signifies poor consumer health information. Video 2 (published in 2015) received a DISCERN score of 2 and received almost 1 million views, which is likely because the specific channel has a well-established subscriber pool (4.9 million subscribers). The highest DISCERN score of 3, demonstrating a tangential shave biopsy, was given to video 4 (published in 2010) and only received about 17,400 views (56 subscribers). Additionally, many videos lacked important information about the procedure. For instance, only 3 of 10 videos demonstrated the anesthetic technique and only 5 videos showed repair methods.

YouTube is an electronic learning source for general information; however, the content and quality of information on nail biopsy is not updated, reliable, or abundant. Patients undergoing nail biopsies are unlikely to find reliable and comprehensible information on YouTube; thus, there is a strong need for patient education in this area. In addition, physicians who did not learn to perform a nail biopsy during training are unlikely to learn this procedure from YouTube. Therefore, there is an unmet need for an outlet that will provide updated reliable content on nail biopsies geared toward both patients and physicians.

To the Editor:

Nail biopsy is an important surgical procedure for diagnosis of nail pathology. YouTube has become a potential instrument for physicians and patients to learn about medical procedures.^1,2 However, the sources, content, and quality of the information available have not been fully studied or characterized. Our objective was to analyze the efficiency of information and quality of YouTube videos on nail biopsies. We hypothesized that the quality of patient education and physician training videos would be unrepresentative on YouTube.

The term nail biopsy was searched on January 29, 2019, and filtered by relevance and rating using the default YouTube algorithm. Data were collected from the top 40 hits for the search term and filter coupling. All videos were viewed and sorted for nail biopsy procedures, and then those videos were categorized as being produced by a physician or other health care provider. The US medical board status of each physician videographer was determined using the American Board of Medical Specialties database.³ DISCERN criteria for assessing consumer health care information⁴ were used to interpret the videos by researchers (S.I. and S.R.L.) in this study.

From the queried search term collection, only 10 videos (1,023,423 combined views) were analyzed in this study (eTable). Although the other resulting videos were tagged as nail biopsy, they were excluded due to irrelevant content (eg, patient blogs, PowerPoints, nail avulsions). The mean age of the videos was 4 years (range, 4 days to 11 years), with a mean video length of 3.30 minutes (range, 49 seconds to 9.03 minutes). Four of 10 videos were performed for longitudinal melanonychia, and 5 of 10 videos were performed for melanonychia, clinically consistent with subungual hematoma. Dermatologists, plastic surgeons, and podiatrists produced the majority of the nail biopsy videos. The overall mean DISCERN rating was 1.60/5.00 (range, 1–3), meaning that the quality of content on nail biopsies was poor. This low DISCERN score signifies poor consumer health information. Video 2 (published in 2015) received a DISCERN score of 2 and received almost 1 million views, which is likely because the specific channel has a well-established subscriber pool (4.9 million subscribers). The highest DISCERN score of 3, demonstrating a tangential shave biopsy, was given to video 4 (published in 2010) and only received about 17,400 views (56 subscribers). Additionally, many videos lacked important information about the procedure. For instance, only 3 of 10 videos demonstrated the anesthetic technique and only 5 videos showed repair methods.

YouTube is an electronic learning source for general information; however, the content and quality of information on nail biopsy is not updated, reliable, or abundant. Patients undergoing nail biopsies are unlikely to find reliable and comprehensible information on YouTube; thus, there is a strong need for patient education in this area. In addition, physicians who did not learn to perform a nail biopsy during training are unlikely to learn this procedure from YouTube. Therefore, there is an unmet need for an outlet that will provide updated reliable content on nail biopsies geared toward both patients and physicians.

Psoriasis is a common chronic inflammatory disease affecting a diverse patient population, yet epidemiological and clinical data related to psoriasis in patients with skin of color are sparse. The Hispanic ethnic group includes a broad range of skin types and cultures. Prevalence of psoriasis in a Hispanic population has been reported as lower than in a white population¹; however, these data may be influenced by the finding that Hispanic patients are less likely to see a dermatologist when they have skin problems.² In addition, socioeconomic disparities and cultural variations among racial/ethnic groups may contribute to differences in access to care and thresholds for seeking care,³ leading to a tendency for more severe disease in skin of color and Hispanic ethnic groups.^4,5 Greater impairments in health-related quality of life have been reported in patients with skin of color and Hispanic racial/ethnic groups compared to white patients, independent of psoriasis severity.^4,6 Postinflammatory pigment alteration at the sites of resolving lesions, a common clinical feature in skin of color, may contribute to the impact of psoriasis on quality of life in patients with skin of color. Psoriasis in darker skin types also can present diagnostic challenges due to overlapping features with other papulosquamous disorders and less conspicuous erythema.⁷

We present a post hoc analysis of the treatment of moderate to severe psoriasis with a novel fixed-combination halobetasol propionate (HP) 0.01%–tazarotene (TAZ) 0.045% lotion in a Hispanic patient population. Historically, clinical trials for psoriasis have enrolled low proportions of Hispanic patients and other patients with skin of color; in this analysis, the Hispanic population (115/418) represented 28% of the total study population and provided valuable insights.

Methods

Study Design
Two phase 3 randomized controlled trials were conducted to demonstrate the efficacy and safety of HP/TAZ lotion. Patients with a clinical diagnosis of moderate or severe localized psoriasis (N=418) were randomized to receive HP/TAZ lotion or vehicle (2:1 ratio) once daily for 8 weeks with a 4-week posttreatment follow-up.^8,9 A post hoc analysis was conducted on data of the self-identified Hispanic population.

Assessments
Efficacy assessments included treatment success (at least a 2-grade improvement from baseline in the investigator global assessment [IGA] and a score of clear or almost clear) and impact on individual signs of psoriasis (at least a 2-grade improvement in erythema, plaque elevation, and scaling) at the target lesion. In addition, reduction in body surface area (BSA) was recorded, and an IGA×BSA score was calculated by multiplying IGA by BSA at each timepoint for each individual patient. A clinically meaningful improvement in disease severity (percentage of patients achieving a 75% reduction in IGA×BSA [IGA×BSA-75]) also was calculated.

Information on reported and observed adverse events (AEs) was obtained at each visit. The safety population included 112 participants (76 in the HP/TAZ group and 36 in the vehicle group).

Statistical Analysis
The statistical and analytical plan is detailed elsewhere⁹ and relevant to this post hoc analysis. No statistical analysis was carried out to compare data in the Hispanic population with either the overall study population or the non-Hispanic population.

Results

Overall, 115 Hispanic patients (27.5%) were enrolled (eFigure). Patients had a mean (standard deviation [SD]) age of 46.7 (13.12) years, and more than two-thirds were male (n=80, 69.6%).

Overall completion rates (80.0%) for Hispanic patients were similar to those in the overall study population, though there were more discontinuations in the vehicle group. The main reasons for treatment discontinuation among Hispanic patients were participant request (n=8, 7.0%), lost to follow-up (n=8, 7.0%), and AEs (n=4, 3.5%). Hispanic patients in this study had more severe disease—18.3% (n=21) had an IGA score of 4 compared to 13.5% (n=41) of non-Hispanic patients—and more severe erythema (19.1% vs 9.6%), plaque elevation (20.0% vs 10.2%), and scaling (15.7% vs 12.9%) compared to the non-Hispanic populations (Table).

 

Efficacy of HP/TAZ lotion in Hispanic patients was similar to the overall study populations,⁹ though maintenance of effect posttreatment appeared to be better. The incidence of treatment-related AEs also was lower.

Halobetasol propionate 0.01%–TAZ 0.045% lotion demonstrated statistically significant superiority based on treatment success compared to vehicle as early as week 4 (P=.034). By week 8, 39.3% of participants treated with HP/TAZ lotion achieved treatment success compared to 9.3% of participants in the vehicle group (P=.002)(Figure 1). Treatment success was maintained over the 4-week posttreatment period, whereby 40.5% of the HP/TAZ-treated participants were treatment successes at week 12 compared to only 4.1% of participants in the vehicle group (P<.001).

Improvements in psoriasis signs and symptoms at the target lesion were statistically significant compared to vehicle from week 2 (plaque elevation, P=.018) or week 4 (erythema, P=.004; scaling, P<.001)(Figure 2). By week 8, 46.8%, 58.1%, and 63.2% of participants showed at least a 2-grade improvement from baseline and were therefore treatment successes for erythema, plaque elevation, and scaling, respectively (all statistically significant [P<.001] compared to vehicle). The number of participants who achieved at least a 2-grade improvement in erythema with HP/TAZ lotion increased posttreatment from 46.8% to 53.0%.

Mean (SD) baseline BSA was 6.2 (3.07), and the mean (SD) size of the target lesion was 36.3 (21.85) cm². Overall, BSA also was significantly reduced in participants treated with HP/TAZ lotion compared to vehicle. At week 8, the mean percentage change from baseline was —40.7% compared to an increase (+10.1%) in the vehicle group (P=.002)(Figure 3). Improvements in BSA were maintained posttreatment, whereas in the vehicle group, mean (SD) BSA had increased to 6.1 (4.64).

Halobetasol propionate 0.01%–TAZ 0.045% lotion achieved a 50.5% reduction from baseline IGA×BSA by week 8 compared to an 8.5% increase with vehicle (P<.001)(Figure 4). Differences in treatment groups were significant from week 2 (P=.016). Efficacy was maintained posttreatment, with a 50.6% reduction from baseline IGA×BSA at week 12 compared to an increase of 13.6% in the vehicle group (P<.001). Again, although results were similar to the overall study population at week 8 (50.5% vs 51.9%), maintenance of effect was better posttreatment (50.6% vs 46.6%).¹⁰

A clinically meaningful effect (IGA×BSA-75) was achieved in 39.7% of Hispanic participants treated with HP/TAZ lotion compared to 8.1% of participants treated with vehicle (P<.001) at week 8. The benefits were significantly different from week 4 and more participants maintained a clinically meaningful effect posttreatment (43.1% vs 7.1%, P<.001)(Figure 5).

 

 

 

 

For Hispanic participants overall, 34 participants reported AEs: 26 (34.2%) treated with HP/TAZ lotion and 8 (22.2%) treated with vehicle (eTable). There was 1 (1.3%) serious AE in the HP/TAZ group. Most of the AEs were mild or moderate, with approximately half being related to study treatment. The most common treatment-related AEs in Hispanic participants treated with HP/TAZ lotion were contact dermatitis (n=3, 3.9%) and skin atrophy (n=3, 3.9%) compared to contact dermatitis (n=14, 7.2%) and application-site pain (n=7, 3.6%) in the non-Hispanic population. Pruritus was the most common AE in Hispanic participants treated with vehicle.

Comment

The large number of Hispanic patients in the 2 phase 3 trials^8,9 allowed for this valuable subgroup analysis on the topical treatment of Hispanic patients with plaque psoriasis. Validation of observed differences in maintenance of effect and tolerability warrant further study. Prior clinical studies in psoriasis have tended to enroll a small proportion of Hispanic patients without any post hoc analysis. For example, in a pooled analysis of 4 phase 3 trials with secukinumab, Hispanic patients accounted for only 16% of the overall population.¹¹ In our analysis, the Hispanic cohort represented 28% of the overall study population of 2 phase 3 studies investigating the efficacy, safety, and tolerability of HP/TAZ lotion in patients with moderate to severe psoriasis.^8,9 In addition, proportionately more Hispanic patients had severe disease (IGA of 4) or severe signs and symptoms of psoriasis (erythema, plaque elevation, and scaling) than the non-Hispanic population. This finding supports other studies that have suggested Hispanic patients with psoriasis tend to have more severe disease but also may reflect thresholds for seeking care.^3-5

Halobetasol propionate 0.01%–TAZ 0.045% lotion was significantly more effective than vehicle for all efficacy assessments. In general, efficacy results with HP/TAZ lotion were similar to those reported in the overall phase 3 study populations over the 8-week treatment period. The only noticeable difference was in the posttreatment period. In the overall study population, efficacy was maintained over the 4-week posttreatment period in the HP/TAZ group. In the Hispanic subpopulation, there appeared to be continued improvement in the number of participants achieving treatment success (IGA and erythema), clinically meaningful success, and further reductions in BSA. Although there is a paucity of studies evaluating psoriasis therapies in Hispanic populations, data on etanercept and secukinumab have been published.^6,11

Onset of effect also is an important aspect of treatment. In patients with skin of color, including patients of Hispanic ethnicity and higher Fitzpatrick skin phototypes, early clearance of lesions may help limit the severity and duration of postinflammatory pigment alteration. Improvements in IGA×BSA scores were significant compared to vehicle from week 2 (P=.016), and a clinically meaningful improvement with HP/TAZ lotion (IGA×BSA-75) was seen by week 4 (P=.024).

Halobetasol propionate 0.01%–TAZ 0.045% lotion was well tolerated, both in the 2 phase 3 studies and in the post hoc analysis of the Hispanic subpopulation. The incidence of skin atrophy (n=3, 3.9%) was more common vs the non-Hispanic population (n=2, 1.0%). Other common AEs—contact dermatitis, pruritus, and application-site pain—were more common in the non-Hispanic population.

A limitation of our analysis was that it was a post hoc analysis of the Hispanic participants. The phase 3 studies were not designed to specifically study the impact of treatment on ethnicity/race, though the number of Hispanic participants enrolled in the 2 studies was relatively high. The absence of Fitzpatrick skin phototypes in this data set is another limitation of this study.

Conclusion

Halobetasol propionate 0.01%–TAZ 0.045% lotion was associated with significant, rapid, and sustained reductions in disease severity in a Hispanic population with moderate to severe psoriasis that continued to show improvement posttreatment with good tolerability and safety.



Acknowledgments
We thank Brian Bulley, MSc (Konic Limited, United Kingdom), for assistance with the preparation of the manuscript. Ortho Dermatologics funded Konic’s activities pertaining to this manuscript.

Psoriasis is a common chronic inflammatory disease affecting a diverse patient population, yet epidemiological and clinical data related to psoriasis in patients with skin of color are sparse. The Hispanic ethnic group includes a broad range of skin types and cultures. Prevalence of psoriasis in a Hispanic population has been reported as lower than in a white population¹; however, these data may be influenced by the finding that Hispanic patients are less likely to see a dermatologist when they have skin problems.² In addition, socioeconomic disparities and cultural variations among racial/ethnic groups may contribute to differences in access to care and thresholds for seeking care,³ leading to a tendency for more severe disease in skin of color and Hispanic ethnic groups.^4,5 Greater impairments in health-related quality of life have been reported in patients with skin of color and Hispanic racial/ethnic groups compared to white patients, independent of psoriasis severity.^4,6 Postinflammatory pigment alteration at the sites of resolving lesions, a common clinical feature in skin of color, may contribute to the impact of psoriasis on quality of life in patients with skin of color. Psoriasis in darker skin types also can present diagnostic challenges due to overlapping features with other papulosquamous disorders and less conspicuous erythema.⁷

We present a post hoc analysis of the treatment of moderate to severe psoriasis with a novel fixed-combination halobetasol propionate (HP) 0.01%–tazarotene (TAZ) 0.045% lotion in a Hispanic patient population. Historically, clinical trials for psoriasis have enrolled low proportions of Hispanic patients and other patients with skin of color; in this analysis, the Hispanic population (115/418) represented 28% of the total study population and provided valuable insights.

Methods

Study Design
Two phase 3 randomized controlled trials were conducted to demonstrate the efficacy and safety of HP/TAZ lotion. Patients with a clinical diagnosis of moderate or severe localized psoriasis (N=418) were randomized to receive HP/TAZ lotion or vehicle (2:1 ratio) once daily for 8 weeks with a 4-week posttreatment follow-up.^8,9 A post hoc analysis was conducted on data of the self-identified Hispanic population.

Assessments
Efficacy assessments included treatment success (at least a 2-grade improvement from baseline in the investigator global assessment [IGA] and a score of clear or almost clear) and impact on individual signs of psoriasis (at least a 2-grade improvement in erythema, plaque elevation, and scaling) at the target lesion. In addition, reduction in body surface area (BSA) was recorded, and an IGA×BSA score was calculated by multiplying IGA by BSA at each timepoint for each individual patient. A clinically meaningful improvement in disease severity (percentage of patients achieving a 75% reduction in IGA×BSA [IGA×BSA-75]) also was calculated.

Information on reported and observed adverse events (AEs) was obtained at each visit. The safety population included 112 participants (76 in the HP/TAZ group and 36 in the vehicle group).

Statistical Analysis
The statistical and analytical plan is detailed elsewhere⁹ and relevant to this post hoc analysis. No statistical analysis was carried out to compare data in the Hispanic population with either the overall study population or the non-Hispanic population.

Results

Overall, 115 Hispanic patients (27.5%) were enrolled (eFigure). Patients had a mean (standard deviation [SD]) age of 46.7 (13.12) years, and more than two-thirds were male (n=80, 69.6%).

Overall completion rates (80.0%) for Hispanic patients were similar to those in the overall study population, though there were more discontinuations in the vehicle group. The main reasons for treatment discontinuation among Hispanic patients were participant request (n=8, 7.0%), lost to follow-up (n=8, 7.0%), and AEs (n=4, 3.5%). Hispanic patients in this study had more severe disease—18.3% (n=21) had an IGA score of 4 compared to 13.5% (n=41) of non-Hispanic patients—and more severe erythema (19.1% vs 9.6%), plaque elevation (20.0% vs 10.2%), and scaling (15.7% vs 12.9%) compared to the non-Hispanic populations (Table).

 

Efficacy of HP/TAZ lotion in Hispanic patients was similar to the overall study populations,⁹ though maintenance of effect posttreatment appeared to be better. The incidence of treatment-related AEs also was lower.

Halobetasol propionate 0.01%–TAZ 0.045% lotion demonstrated statistically significant superiority based on treatment success compared to vehicle as early as week 4 (P=.034). By week 8, 39.3% of participants treated with HP/TAZ lotion achieved treatment success compared to 9.3% of participants in the vehicle group (P=.002)(Figure 1). Treatment success was maintained over the 4-week posttreatment period, whereby 40.5% of the HP/TAZ-treated participants were treatment successes at week 12 compared to only 4.1% of participants in the vehicle group (P<.001).

Improvements in psoriasis signs and symptoms at the target lesion were statistically significant compared to vehicle from week 2 (plaque elevation, P=.018) or week 4 (erythema, P=.004; scaling, P<.001)(Figure 2). By week 8, 46.8%, 58.1%, and 63.2% of participants showed at least a 2-grade improvement from baseline and were therefore treatment successes for erythema, plaque elevation, and scaling, respectively (all statistically significant [P<.001] compared to vehicle). The number of participants who achieved at least a 2-grade improvement in erythema with HP/TAZ lotion increased posttreatment from 46.8% to 53.0%.

Mean (SD) baseline BSA was 6.2 (3.07), and the mean (SD) size of the target lesion was 36.3 (21.85) cm². Overall, BSA also was significantly reduced in participants treated with HP/TAZ lotion compared to vehicle. At week 8, the mean percentage change from baseline was —40.7% compared to an increase (+10.1%) in the vehicle group (P=.002)(Figure 3). Improvements in BSA were maintained posttreatment, whereas in the vehicle group, mean (SD) BSA had increased to 6.1 (4.64).

Halobetasol propionate 0.01%–TAZ 0.045% lotion achieved a 50.5% reduction from baseline IGA×BSA by week 8 compared to an 8.5% increase with vehicle (P<.001)(Figure 4). Differences in treatment groups were significant from week 2 (P=.016). Efficacy was maintained posttreatment, with a 50.6% reduction from baseline IGA×BSA at week 12 compared to an increase of 13.6% in the vehicle group (P<.001). Again, although results were similar to the overall study population at week 8 (50.5% vs 51.9%), maintenance of effect was better posttreatment (50.6% vs 46.6%).¹⁰

A clinically meaningful effect (IGA×BSA-75) was achieved in 39.7% of Hispanic participants treated with HP/TAZ lotion compared to 8.1% of participants treated with vehicle (P<.001) at week 8. The benefits were significantly different from week 4 and more participants maintained a clinically meaningful effect posttreatment (43.1% vs 7.1%, P<.001)(Figure 5).

 

 

 

 

For Hispanic participants overall, 34 participants reported AEs: 26 (34.2%) treated with HP/TAZ lotion and 8 (22.2%) treated with vehicle (eTable). There was 1 (1.3%) serious AE in the HP/TAZ group. Most of the AEs were mild or moderate, with approximately half being related to study treatment. The most common treatment-related AEs in Hispanic participants treated with HP/TAZ lotion were contact dermatitis (n=3, 3.9%) and skin atrophy (n=3, 3.9%) compared to contact dermatitis (n=14, 7.2%) and application-site pain (n=7, 3.6%) in the non-Hispanic population. Pruritus was the most common AE in Hispanic participants treated with vehicle.

Comment

The large number of Hispanic patients in the 2 phase 3 trials^8,9 allowed for this valuable subgroup analysis on the topical treatment of Hispanic patients with plaque psoriasis. Validation of observed differences in maintenance of effect and tolerability warrant further study. Prior clinical studies in psoriasis have tended to enroll a small proportion of Hispanic patients without any post hoc analysis. For example, in a pooled analysis of 4 phase 3 trials with secukinumab, Hispanic patients accounted for only 16% of the overall population.¹¹ In our analysis, the Hispanic cohort represented 28% of the overall study population of 2 phase 3 studies investigating the efficacy, safety, and tolerability of HP/TAZ lotion in patients with moderate to severe psoriasis.^8,9 In addition, proportionately more Hispanic patients had severe disease (IGA of 4) or severe signs and symptoms of psoriasis (erythema, plaque elevation, and scaling) than the non-Hispanic population. This finding supports other studies that have suggested Hispanic patients with psoriasis tend to have more severe disease but also may reflect thresholds for seeking care.^3-5

Halobetasol propionate 0.01%–TAZ 0.045% lotion was significantly more effective than vehicle for all efficacy assessments. In general, efficacy results with HP/TAZ lotion were similar to those reported in the overall phase 3 study populations over the 8-week treatment period. The only noticeable difference was in the posttreatment period. In the overall study population, efficacy was maintained over the 4-week posttreatment period in the HP/TAZ group. In the Hispanic subpopulation, there appeared to be continued improvement in the number of participants achieving treatment success (IGA and erythema), clinically meaningful success, and further reductions in BSA. Although there is a paucity of studies evaluating psoriasis therapies in Hispanic populations, data on etanercept and secukinumab have been published.^6,11

Onset of effect also is an important aspect of treatment. In patients with skin of color, including patients of Hispanic ethnicity and higher Fitzpatrick skin phototypes, early clearance of lesions may help limit the severity and duration of postinflammatory pigment alteration. Improvements in IGA×BSA scores were significant compared to vehicle from week 2 (P=.016), and a clinically meaningful improvement with HP/TAZ lotion (IGA×BSA-75) was seen by week 4 (P=.024).

Halobetasol propionate 0.01%–TAZ 0.045% lotion was well tolerated, both in the 2 phase 3 studies and in the post hoc analysis of the Hispanic subpopulation. The incidence of skin atrophy (n=3, 3.9%) was more common vs the non-Hispanic population (n=2, 1.0%). Other common AEs—contact dermatitis, pruritus, and application-site pain—were more common in the non-Hispanic population.

A limitation of our analysis was that it was a post hoc analysis of the Hispanic participants. The phase 3 studies were not designed to specifically study the impact of treatment on ethnicity/race, though the number of Hispanic participants enrolled in the 2 studies was relatively high. The absence of Fitzpatrick skin phototypes in this data set is another limitation of this study.

Conclusion

Halobetasol propionate 0.01%–TAZ 0.045% lotion was associated with significant, rapid, and sustained reductions in disease severity in a Hispanic population with moderate to severe psoriasis that continued to show improvement posttreatment with good tolerability and safety.



Acknowledgments
We thank Brian Bulley, MSc (Konic Limited, United Kingdom), for assistance with the preparation of the manuscript. Ortho Dermatologics funded Konic’s activities pertaining to this manuscript.

Psoriasis is a common chronic inflammatory disease affecting a diverse patient population, yet epidemiological and clinical data related to psoriasis in patients with skin of color are sparse. The Hispanic ethnic group includes a broad range of skin types and cultures. Prevalence of psoriasis in a Hispanic population has been reported as lower than in a white population¹; however, these data may be influenced by the finding that Hispanic patients are less likely to see a dermatologist when they have skin problems.² In addition, socioeconomic disparities and cultural variations among racial/ethnic groups may contribute to differences in access to care and thresholds for seeking care,³ leading to a tendency for more severe disease in skin of color and Hispanic ethnic groups.^4,5 Greater impairments in health-related quality of life have been reported in patients with skin of color and Hispanic racial/ethnic groups compared to white patients, independent of psoriasis severity.^4,6 Postinflammatory pigment alteration at the sites of resolving lesions, a common clinical feature in skin of color, may contribute to the impact of psoriasis on quality of life in patients with skin of color. Psoriasis in darker skin types also can present diagnostic challenges due to overlapping features with other papulosquamous disorders and less conspicuous erythema.⁷

We present a post hoc analysis of the treatment of moderate to severe psoriasis with a novel fixed-combination halobetasol propionate (HP) 0.01%–tazarotene (TAZ) 0.045% lotion in a Hispanic patient population. Historically, clinical trials for psoriasis have enrolled low proportions of Hispanic patients and other patients with skin of color; in this analysis, the Hispanic population (115/418) represented 28% of the total study population and provided valuable insights.

Methods

Study Design
Two phase 3 randomized controlled trials were conducted to demonstrate the efficacy and safety of HP/TAZ lotion. Patients with a clinical diagnosis of moderate or severe localized psoriasis (N=418) were randomized to receive HP/TAZ lotion or vehicle (2:1 ratio) once daily for 8 weeks with a 4-week posttreatment follow-up.^8,9 A post hoc analysis was conducted on data of the self-identified Hispanic population.

Assessments
Efficacy assessments included treatment success (at least a 2-grade improvement from baseline in the investigator global assessment [IGA] and a score of clear or almost clear) and impact on individual signs of psoriasis (at least a 2-grade improvement in erythema, plaque elevation, and scaling) at the target lesion. In addition, reduction in body surface area (BSA) was recorded, and an IGA×BSA score was calculated by multiplying IGA by BSA at each timepoint for each individual patient. A clinically meaningful improvement in disease severity (percentage of patients achieving a 75% reduction in IGA×BSA [IGA×BSA-75]) also was calculated.

Information on reported and observed adverse events (AEs) was obtained at each visit. The safety population included 112 participants (76 in the HP/TAZ group and 36 in the vehicle group).

Statistical Analysis
The statistical and analytical plan is detailed elsewhere⁹ and relevant to this post hoc analysis. No statistical analysis was carried out to compare data in the Hispanic population with either the overall study population or the non-Hispanic population.

Results

Overall, 115 Hispanic patients (27.5%) were enrolled (eFigure). Patients had a mean (standard deviation [SD]) age of 46.7 (13.12) years, and more than two-thirds were male (n=80, 69.6%).

Overall completion rates (80.0%) for Hispanic patients were similar to those in the overall study population, though there were more discontinuations in the vehicle group. The main reasons for treatment discontinuation among Hispanic patients were participant request (n=8, 7.0%), lost to follow-up (n=8, 7.0%), and AEs (n=4, 3.5%). Hispanic patients in this study had more severe disease—18.3% (n=21) had an IGA score of 4 compared to 13.5% (n=41) of non-Hispanic patients—and more severe erythema (19.1% vs 9.6%), plaque elevation (20.0% vs 10.2%), and scaling (15.7% vs 12.9%) compared to the non-Hispanic populations (Table).

 

Efficacy of HP/TAZ lotion in Hispanic patients was similar to the overall study populations,⁹ though maintenance of effect posttreatment appeared to be better. The incidence of treatment-related AEs also was lower.

Halobetasol propionate 0.01%–TAZ 0.045% lotion demonstrated statistically significant superiority based on treatment success compared to vehicle as early as week 4 (P=.034). By week 8, 39.3% of participants treated with HP/TAZ lotion achieved treatment success compared to 9.3% of participants in the vehicle group (P=.002)(Figure 1). Treatment success was maintained over the 4-week posttreatment period, whereby 40.5% of the HP/TAZ-treated participants were treatment successes at week 12 compared to only 4.1% of participants in the vehicle group (P<.001).

Improvements in psoriasis signs and symptoms at the target lesion were statistically significant compared to vehicle from week 2 (plaque elevation, P=.018) or week 4 (erythema, P=.004; scaling, P<.001)(Figure 2). By week 8, 46.8%, 58.1%, and 63.2% of participants showed at least a 2-grade improvement from baseline and were therefore treatment successes for erythema, plaque elevation, and scaling, respectively (all statistically significant [P<.001] compared to vehicle). The number of participants who achieved at least a 2-grade improvement in erythema with HP/TAZ lotion increased posttreatment from 46.8% to 53.0%.

Mean (SD) baseline BSA was 6.2 (3.07), and the mean (SD) size of the target lesion was 36.3 (21.85) cm². Overall, BSA also was significantly reduced in participants treated with HP/TAZ lotion compared to vehicle. At week 8, the mean percentage change from baseline was —40.7% compared to an increase (+10.1%) in the vehicle group (P=.002)(Figure 3). Improvements in BSA were maintained posttreatment, whereas in the vehicle group, mean (SD) BSA had increased to 6.1 (4.64).

Halobetasol propionate 0.01%–TAZ 0.045% lotion achieved a 50.5% reduction from baseline IGA×BSA by week 8 compared to an 8.5% increase with vehicle (P<.001)(Figure 4). Differences in treatment groups were significant from week 2 (P=.016). Efficacy was maintained posttreatment, with a 50.6% reduction from baseline IGA×BSA at week 12 compared to an increase of 13.6% in the vehicle group (P<.001). Again, although results were similar to the overall study population at week 8 (50.5% vs 51.9%), maintenance of effect was better posttreatment (50.6% vs 46.6%).¹⁰

A clinically meaningful effect (IGA×BSA-75) was achieved in 39.7% of Hispanic participants treated with HP/TAZ lotion compared to 8.1% of participants treated with vehicle (P<.001) at week 8. The benefits were significantly different from week 4 and more participants maintained a clinically meaningful effect posttreatment (43.1% vs 7.1%, P<.001)(Figure 5).

 

 

 

 

For Hispanic participants overall, 34 participants reported AEs: 26 (34.2%) treated with HP/TAZ lotion and 8 (22.2%) treated with vehicle (eTable). There was 1 (1.3%) serious AE in the HP/TAZ group. Most of the AEs were mild or moderate, with approximately half being related to study treatment. The most common treatment-related AEs in Hispanic participants treated with HP/TAZ lotion were contact dermatitis (n=3, 3.9%) and skin atrophy (n=3, 3.9%) compared to contact dermatitis (n=14, 7.2%) and application-site pain (n=7, 3.6%) in the non-Hispanic population. Pruritus was the most common AE in Hispanic participants treated with vehicle.

Comment

The large number of Hispanic patients in the 2 phase 3 trials^8,9 allowed for this valuable subgroup analysis on the topical treatment of Hispanic patients with plaque psoriasis. Validation of observed differences in maintenance of effect and tolerability warrant further study. Prior clinical studies in psoriasis have tended to enroll a small proportion of Hispanic patients without any post hoc analysis. For example, in a pooled analysis of 4 phase 3 trials with secukinumab, Hispanic patients accounted for only 16% of the overall population.¹¹ In our analysis, the Hispanic cohort represented 28% of the overall study population of 2 phase 3 studies investigating the efficacy, safety, and tolerability of HP/TAZ lotion in patients with moderate to severe psoriasis.^8,9 In addition, proportionately more Hispanic patients had severe disease (IGA of 4) or severe signs and symptoms of psoriasis (erythema, plaque elevation, and scaling) than the non-Hispanic population. This finding supports other studies that have suggested Hispanic patients with psoriasis tend to have more severe disease but also may reflect thresholds for seeking care.^3-5

Halobetasol propionate 0.01%–TAZ 0.045% lotion was significantly more effective than vehicle for all efficacy assessments. In general, efficacy results with HP/TAZ lotion were similar to those reported in the overall phase 3 study populations over the 8-week treatment period. The only noticeable difference was in the posttreatment period. In the overall study population, efficacy was maintained over the 4-week posttreatment period in the HP/TAZ group. In the Hispanic subpopulation, there appeared to be continued improvement in the number of participants achieving treatment success (IGA and erythema), clinically meaningful success, and further reductions in BSA. Although there is a paucity of studies evaluating psoriasis therapies in Hispanic populations, data on etanercept and secukinumab have been published.^6,11

Onset of effect also is an important aspect of treatment. In patients with skin of color, including patients of Hispanic ethnicity and higher Fitzpatrick skin phototypes, early clearance of lesions may help limit the severity and duration of postinflammatory pigment alteration. Improvements in IGA×BSA scores were significant compared to vehicle from week 2 (P=.016), and a clinically meaningful improvement with HP/TAZ lotion (IGA×BSA-75) was seen by week 4 (P=.024).

Halobetasol propionate 0.01%–TAZ 0.045% lotion was well tolerated, both in the 2 phase 3 studies and in the post hoc analysis of the Hispanic subpopulation. The incidence of skin atrophy (n=3, 3.9%) was more common vs the non-Hispanic population (n=2, 1.0%). Other common AEs—contact dermatitis, pruritus, and application-site pain—were more common in the non-Hispanic population.

A limitation of our analysis was that it was a post hoc analysis of the Hispanic participants. The phase 3 studies were not designed to specifically study the impact of treatment on ethnicity/race, though the number of Hispanic participants enrolled in the 2 studies was relatively high. The absence of Fitzpatrick skin phototypes in this data set is another limitation of this study.

Conclusion

Halobetasol propionate 0.01%–TAZ 0.045% lotion was associated with significant, rapid, and sustained reductions in disease severity in a Hispanic population with moderate to severe psoriasis that continued to show improvement posttreatment with good tolerability and safety.



Acknowledgments
We thank Brian Bulley, MSc (Konic Limited, United Kingdom), for assistance with the preparation of the manuscript. Ortho Dermatologics funded Konic’s activities pertaining to this manuscript.

Porphyria cutanea tarda (PCT) is the most common type of porphyria. The accumulation of porphyrin in various organ systems results from a deficiency of uroporphyrinogen decarboxylase (UROD).^1-3 Chronic hepatitis C virus (HCV) causes a hepatic decrease in hepcidin production, resulting in increased iron absorption. Iron loading and increased oxidative stress in the liver leads to nonporphyrin inhibition of UROD production and to oxidation of porphyrinogens to porphyrins.⁴ This in turn leads to accumulation of uroporphyrins and carboxylated metabolites that can be detected in urine.⁴

Signs of PCT include blisters, vesicles, and possibly milia developing on sun-exposed areas of the skin, such as the face, forearms, and dorsal hands.⁴ Case reports have demonstrated a resolution of PCT in patients with chronic HCV with treatment with direct-acting antivirals (DAAs), such as ledipasvir/sofosbuvir.^1,3 However, here we present 2 cases of patients who developed blistering diseases during treatment of chronic HCV with ledipasvir/sofosbuvir. Neither demonstrated complete resolution of symptoms during the treatment regimen.

Cases

Patient 1

A 63-year-old white male with a history of chronic HCV (genotype 1a), bipolar disorder, hyperlipidemia, tobacco dependence, and cirrhosis (F4 by elastography) presented with minimally to moderately painful blisters on his bilateral dorsal hands that had developed around weeks 8 to 9 of treatment with ledipasvir/sofosbuvir. The patient reported that no new blisters had appeared following completion of 12 weeks of treatment and that his current blisters were in various stages of healing. He reported alcohol use of 1 to 2 twelve-ounce beers daily and no history of dioxin exposure. His medications included doxepin, hydralazine, hydrochlorothiazide, quetiapine, folic acid, and thiamine. His hepatitis C viral load was 440,000 IU/mL prior to treatment. Tests for hepatitis B surface antigen and HIV antibodies were negative. His iron level was 135 µg/dL, total iron-binding capacity (TIBC) was 323 µg/dL, and ferritin was 299.0 ng/mL. His HFEgene was negative for mutations. Following 4 weeks of treatment with ledipasvir/sofosbuvir, a hepatitis C viral load was not detected.

A physical examination on presentation revealed erosions with overlying hemorrhagic crusts on the bilateral dorsal hands (Figure). 

The differential diagnosis included PCT, pseudo-PCT, bullous pemphigoid, bullous arthropod bite reaction, and epidermolysis bullosa acquisita. A punch biopsy of the lesion on the right dorsal hand demonstrated re-epithelialization of a previously formed subepidermal bullae deemed compatible with PCT or pseudo-PCT. A 24-hour high-performance liquid chromatography quantitative urine porphyrin showed greatly elevated levels of urine porphyrins, including uroporphyrins and heptacarboxylporphyrins, and slight elevations of hexcarboxyporphyrins, pentacarboxylporphyrins, and coproporphyrins indicating a diagnosis of PCT.

At the 4-month follow-up, the patient reported no new blister formations. A physical examination revealed well-healed scars and several clustered milia on bilateral dorsal hands with no active vesicles or bullae noted.

Patient 2

An African American male aged 63 years presented with a 1-month history of moderately painful blisters on his bilateral dorsal hands during treatment of chronic HCV (genotype 1a) with ledipasvir/sofosbuvir. His medical history included gout, tobacco and alcohol addiction, osteoarthritis, and hepatic fibrosis (F3 by elastography). The patient’s medications included allopurinol, lisinopril, and hydrochlorothiazide. He reported no history of dioxin exposure. On the day of presentation, he was on week 9 of the 12-week treatment ledipasvir/sofosbuvir regimen. Laboratory results included an initial HCV viral load of 1,618,605 IU/mL. Tests for hepatitis B surface antigen and HIV antibodies were negative. His iron was 191 µg/dL, TIBC 388 µg/dL, and ferritin 459.0 ng/mL. After 4 weeks of treatment, the patient’s hepatitis C viral load was undetectable.

 

A physical examination revealed several resolving erosions to his bilateral dorsal hands, some of which had overlying crusting along with one small hemorrhagic vesicle on the right dorsal hand. A punch biopsy of the hemorrhagic vesicle was performed and demonstrated a cell-poor subepidermal blister with festooning of the dermal papilla. A direct immunofluorescence study showed immunoglobulin (Ig) G fluorescence along the dermal-epidermal junction and within vessel walls in the superficial dermis. Weak IgM and C3 fluorescence also was noted within vessel walls in the superficial dermis. All of the patient findings and history were consistent with PCT, although pseudo-PCT also was a consideration. A 24-hour urine sample yielded negative results for porphobilinogen. Urine porphyrin test results were not available, leading to a presumptive histological diagnosis of PCT.

The patient completed 11 of the prescribed 12 weeks of ledipasvir/sofosbuvir. The blisters resolved shortly thereafter.

Discussion

PCT has a well-established association with chronic HCV infection.⁴ We present 2 cases of a blistering disease clinically and histologically compatible with PCT that developed in patients only after initiation of treatment for chronic HCV with ledipasvir/sofosbuvir. One case was confirmed as PCT on the basis of compatible histopathologic findings and a urine porphyrin assay that showed elevated levels of uroporphyrins and carboxylated metabolites. The second case was clinically and histologically suggestive of PCT but not confirmed by urine porphyrin testing. In both patients, after 8 to 9 weeks of a 12-week course of antiviral therapy, the blistering lesions were noted but appeared to be resolving, and no new lesions were noted after discontinuation of therapy. It appeared that the antiviral treatment temporally triggered the initiation of the blistering skin disease, and as the chronic HCV infection cleared after treatment, the blistering lesions also began to resolve.

Mechanistically, it is known that the virally-induced hepatic damage leads to inhibition of uroporphyrinogen decarboxylase, and the subsequent oxidation of porphyrinogens to porphyrins. Cofactors such as HIV infection also may contribute to development of PCT.⁵

De novo PCT has been documented during therapy using interferon and ribavirin.⁶ The hemolytic anemia and increased hepatic iron were implicated as potential etiologies.⁶ Patients with HCV and PCT treated with the newer direct-acting antiviral therapies have been described to have experienced improvement in PCT symptoms.³

Although there were rare reports of deterioration in renal and liver function,⁷ reactivation of HBV infection,⁸ and Stevens-Johnson syndrome⁹ with antiviral therapy, these complications were not observed in these patients. Both patients also had successful resolution of HCV infection, and by completion of the antiviral therapy, the blistering also resolved.

Conclusion

PCT is an extrahepatic manifestation of HCV infection. Health care providers should be aware of the association of chronic HCV infection with PCT. The findings of PCT should not result in the delay or discontinuation of antiviral therapy.

Porphyria cutanea tarda (PCT) is the most common type of porphyria. The accumulation of porphyrin in various organ systems results from a deficiency of uroporphyrinogen decarboxylase (UROD).^1-3 Chronic hepatitis C virus (HCV) causes a hepatic decrease in hepcidin production, resulting in increased iron absorption. Iron loading and increased oxidative stress in the liver leads to nonporphyrin inhibition of UROD production and to oxidation of porphyrinogens to porphyrins.⁴ This in turn leads to accumulation of uroporphyrins and carboxylated metabolites that can be detected in urine.⁴

Signs of PCT include blisters, vesicles, and possibly milia developing on sun-exposed areas of the skin, such as the face, forearms, and dorsal hands.⁴ Case reports have demonstrated a resolution of PCT in patients with chronic HCV with treatment with direct-acting antivirals (DAAs), such as ledipasvir/sofosbuvir.^1,3 However, here we present 2 cases of patients who developed blistering diseases during treatment of chronic HCV with ledipasvir/sofosbuvir. Neither demonstrated complete resolution of symptoms during the treatment regimen.

Cases

Patient 1

A 63-year-old white male with a history of chronic HCV (genotype 1a), bipolar disorder, hyperlipidemia, tobacco dependence, and cirrhosis (F4 by elastography) presented with minimally to moderately painful blisters on his bilateral dorsal hands that had developed around weeks 8 to 9 of treatment with ledipasvir/sofosbuvir. The patient reported that no new blisters had appeared following completion of 12 weeks of treatment and that his current blisters were in various stages of healing. He reported alcohol use of 1 to 2 twelve-ounce beers daily and no history of dioxin exposure. His medications included doxepin, hydralazine, hydrochlorothiazide, quetiapine, folic acid, and thiamine. His hepatitis C viral load was 440,000 IU/mL prior to treatment. Tests for hepatitis B surface antigen and HIV antibodies were negative. His iron level was 135 µg/dL, total iron-binding capacity (TIBC) was 323 µg/dL, and ferritin was 299.0 ng/mL. His HFEgene was negative for mutations. Following 4 weeks of treatment with ledipasvir/sofosbuvir, a hepatitis C viral load was not detected.

A physical examination on presentation revealed erosions with overlying hemorrhagic crusts on the bilateral dorsal hands (Figure). 

The differential diagnosis included PCT, pseudo-PCT, bullous pemphigoid, bullous arthropod bite reaction, and epidermolysis bullosa acquisita. A punch biopsy of the lesion on the right dorsal hand demonstrated re-epithelialization of a previously formed subepidermal bullae deemed compatible with PCT or pseudo-PCT. A 24-hour high-performance liquid chromatography quantitative urine porphyrin showed greatly elevated levels of urine porphyrins, including uroporphyrins and heptacarboxylporphyrins, and slight elevations of hexcarboxyporphyrins, pentacarboxylporphyrins, and coproporphyrins indicating a diagnosis of PCT.

At the 4-month follow-up, the patient reported no new blister formations. A physical examination revealed well-healed scars and several clustered milia on bilateral dorsal hands with no active vesicles or bullae noted.

Patient 2

An African American male aged 63 years presented with a 1-month history of moderately painful blisters on his bilateral dorsal hands during treatment of chronic HCV (genotype 1a) with ledipasvir/sofosbuvir. His medical history included gout, tobacco and alcohol addiction, osteoarthritis, and hepatic fibrosis (F3 by elastography). The patient’s medications included allopurinol, lisinopril, and hydrochlorothiazide. He reported no history of dioxin exposure. On the day of presentation, he was on week 9 of the 12-week treatment ledipasvir/sofosbuvir regimen. Laboratory results included an initial HCV viral load of 1,618,605 IU/mL. Tests for hepatitis B surface antigen and HIV antibodies were negative. His iron was 191 µg/dL, TIBC 388 µg/dL, and ferritin 459.0 ng/mL. After 4 weeks of treatment, the patient’s hepatitis C viral load was undetectable.

 

A physical examination revealed several resolving erosions to his bilateral dorsal hands, some of which had overlying crusting along with one small hemorrhagic vesicle on the right dorsal hand. A punch biopsy of the hemorrhagic vesicle was performed and demonstrated a cell-poor subepidermal blister with festooning of the dermal papilla. A direct immunofluorescence study showed immunoglobulin (Ig) G fluorescence along the dermal-epidermal junction and within vessel walls in the superficial dermis. Weak IgM and C3 fluorescence also was noted within vessel walls in the superficial dermis. All of the patient findings and history were consistent with PCT, although pseudo-PCT also was a consideration. A 24-hour urine sample yielded negative results for porphobilinogen. Urine porphyrin test results were not available, leading to a presumptive histological diagnosis of PCT.

The patient completed 11 of the prescribed 12 weeks of ledipasvir/sofosbuvir. The blisters resolved shortly thereafter.

Discussion

PCT has a well-established association with chronic HCV infection.⁴ We present 2 cases of a blistering disease clinically and histologically compatible with PCT that developed in patients only after initiation of treatment for chronic HCV with ledipasvir/sofosbuvir. One case was confirmed as PCT on the basis of compatible histopathologic findings and a urine porphyrin assay that showed elevated levels of uroporphyrins and carboxylated metabolites. The second case was clinically and histologically suggestive of PCT but not confirmed by urine porphyrin testing. In both patients, after 8 to 9 weeks of a 12-week course of antiviral therapy, the blistering lesions were noted but appeared to be resolving, and no new lesions were noted after discontinuation of therapy. It appeared that the antiviral treatment temporally triggered the initiation of the blistering skin disease, and as the chronic HCV infection cleared after treatment, the blistering lesions also began to resolve.

Mechanistically, it is known that the virally-induced hepatic damage leads to inhibition of uroporphyrinogen decarboxylase, and the subsequent oxidation of porphyrinogens to porphyrins. Cofactors such as HIV infection also may contribute to development of PCT.⁵

De novo PCT has been documented during therapy using interferon and ribavirin.⁶ The hemolytic anemia and increased hepatic iron were implicated as potential etiologies.⁶ Patients with HCV and PCT treated with the newer direct-acting antiviral therapies have been described to have experienced improvement in PCT symptoms.³

Although there were rare reports of deterioration in renal and liver function,⁷ reactivation of HBV infection,⁸ and Stevens-Johnson syndrome⁹ with antiviral therapy, these complications were not observed in these patients. Both patients also had successful resolution of HCV infection, and by completion of the antiviral therapy, the blistering also resolved.

Conclusion

PCT is an extrahepatic manifestation of HCV infection. Health care providers should be aware of the association of chronic HCV infection with PCT. The findings of PCT should not result in the delay or discontinuation of antiviral therapy.

Porphyria cutanea tarda (PCT) is the most common type of porphyria. The accumulation of porphyrin in various organ systems results from a deficiency of uroporphyrinogen decarboxylase (UROD).^1-3 Chronic hepatitis C virus (HCV) causes a hepatic decrease in hepcidin production, resulting in increased iron absorption. Iron loading and increased oxidative stress in the liver leads to nonporphyrin inhibition of UROD production and to oxidation of porphyrinogens to porphyrins.⁴ This in turn leads to accumulation of uroporphyrins and carboxylated metabolites that can be detected in urine.⁴

Signs of PCT include blisters, vesicles, and possibly milia developing on sun-exposed areas of the skin, such as the face, forearms, and dorsal hands.⁴ Case reports have demonstrated a resolution of PCT in patients with chronic HCV with treatment with direct-acting antivirals (DAAs), such as ledipasvir/sofosbuvir.^1,3 However, here we present 2 cases of patients who developed blistering diseases during treatment of chronic HCV with ledipasvir/sofosbuvir. Neither demonstrated complete resolution of symptoms during the treatment regimen.

Cases

Patient 1

A 63-year-old white male with a history of chronic HCV (genotype 1a), bipolar disorder, hyperlipidemia, tobacco dependence, and cirrhosis (F4 by elastography) presented with minimally to moderately painful blisters on his bilateral dorsal hands that had developed around weeks 8 to 9 of treatment with ledipasvir/sofosbuvir. The patient reported that no new blisters had appeared following completion of 12 weeks of treatment and that his current blisters were in various stages of healing. He reported alcohol use of 1 to 2 twelve-ounce beers daily and no history of dioxin exposure. His medications included doxepin, hydralazine, hydrochlorothiazide, quetiapine, folic acid, and thiamine. His hepatitis C viral load was 440,000 IU/mL prior to treatment. Tests for hepatitis B surface antigen and HIV antibodies were negative. His iron level was 135 µg/dL, total iron-binding capacity (TIBC) was 323 µg/dL, and ferritin was 299.0 ng/mL. His HFEgene was negative for mutations. Following 4 weeks of treatment with ledipasvir/sofosbuvir, a hepatitis C viral load was not detected.

A physical examination on presentation revealed erosions with overlying hemorrhagic crusts on the bilateral dorsal hands (Figure). 

The differential diagnosis included PCT, pseudo-PCT, bullous pemphigoid, bullous arthropod bite reaction, and epidermolysis bullosa acquisita. A punch biopsy of the lesion on the right dorsal hand demonstrated re-epithelialization of a previously formed subepidermal bullae deemed compatible with PCT or pseudo-PCT. A 24-hour high-performance liquid chromatography quantitative urine porphyrin showed greatly elevated levels of urine porphyrins, including uroporphyrins and heptacarboxylporphyrins, and slight elevations of hexcarboxyporphyrins, pentacarboxylporphyrins, and coproporphyrins indicating a diagnosis of PCT.

At the 4-month follow-up, the patient reported no new blister formations. A physical examination revealed well-healed scars and several clustered milia on bilateral dorsal hands with no active vesicles or bullae noted.

Patient 2

An African American male aged 63 years presented with a 1-month history of moderately painful blisters on his bilateral dorsal hands during treatment of chronic HCV (genotype 1a) with ledipasvir/sofosbuvir. His medical history included gout, tobacco and alcohol addiction, osteoarthritis, and hepatic fibrosis (F3 by elastography). The patient’s medications included allopurinol, lisinopril, and hydrochlorothiazide. He reported no history of dioxin exposure. On the day of presentation, he was on week 9 of the 12-week treatment ledipasvir/sofosbuvir regimen. Laboratory results included an initial HCV viral load of 1,618,605 IU/mL. Tests for hepatitis B surface antigen and HIV antibodies were negative. His iron was 191 µg/dL, TIBC 388 µg/dL, and ferritin 459.0 ng/mL. After 4 weeks of treatment, the patient’s hepatitis C viral load was undetectable.

 

A physical examination revealed several resolving erosions to his bilateral dorsal hands, some of which had overlying crusting along with one small hemorrhagic vesicle on the right dorsal hand. A punch biopsy of the hemorrhagic vesicle was performed and demonstrated a cell-poor subepidermal blister with festooning of the dermal papilla. A direct immunofluorescence study showed immunoglobulin (Ig) G fluorescence along the dermal-epidermal junction and within vessel walls in the superficial dermis. Weak IgM and C3 fluorescence also was noted within vessel walls in the superficial dermis. All of the patient findings and history were consistent with PCT, although pseudo-PCT also was a consideration. A 24-hour urine sample yielded negative results for porphobilinogen. Urine porphyrin test results were not available, leading to a presumptive histological diagnosis of PCT.

The patient completed 11 of the prescribed 12 weeks of ledipasvir/sofosbuvir. The blisters resolved shortly thereafter.

Discussion

PCT has a well-established association with chronic HCV infection.⁴ We present 2 cases of a blistering disease clinically and histologically compatible with PCT that developed in patients only after initiation of treatment for chronic HCV with ledipasvir/sofosbuvir. One case was confirmed as PCT on the basis of compatible histopathologic findings and a urine porphyrin assay that showed elevated levels of uroporphyrins and carboxylated metabolites. The second case was clinically and histologically suggestive of PCT but not confirmed by urine porphyrin testing. In both patients, after 8 to 9 weeks of a 12-week course of antiviral therapy, the blistering lesions were noted but appeared to be resolving, and no new lesions were noted after discontinuation of therapy. It appeared that the antiviral treatment temporally triggered the initiation of the blistering skin disease, and as the chronic HCV infection cleared after treatment, the blistering lesions also began to resolve.

Mechanistically, it is known that the virally-induced hepatic damage leads to inhibition of uroporphyrinogen decarboxylase, and the subsequent oxidation of porphyrinogens to porphyrins. Cofactors such as HIV infection also may contribute to development of PCT.⁵

De novo PCT has been documented during therapy using interferon and ribavirin.⁶ The hemolytic anemia and increased hepatic iron were implicated as potential etiologies.⁶ Patients with HCV and PCT treated with the newer direct-acting antiviral therapies have been described to have experienced improvement in PCT symptoms.³

Although there were rare reports of deterioration in renal and liver function,⁷ reactivation of HBV infection,⁸ and Stevens-Johnson syndrome⁹ with antiviral therapy, these complications were not observed in these patients. Both patients also had successful resolution of HCV infection, and by completion of the antiviral therapy, the blistering also resolved.

Conclusion

PCT is an extrahepatic manifestation of HCV infection. Health care providers should be aware of the association of chronic HCV infection with PCT. The findings of PCT should not result in the delay or discontinuation of antiviral therapy.

Sepsis is a major public health concern: 10% of patients with sepsis die, and mortality quadruples with progression to septic shock.¹ Systemic inflammatory response syndrome (SIRS) criteria, originally published in 1992, are commonly used to detect sepsis, but as early as 2001, these criteria were recognized as lacking specificity.² Nonetheless, the use of SIRS criteria has persisted in practice. Sepsis was redefined in Sepsis-3 (2016) to guide earlier and more appropriate identification and treatment, which has been shown to greatly improve patient outcomes.^1,3 Key recommendations in Sepsis 3 included eliminating SIRS criteria, defining organ dysfunction by the Sequential Organ Failure Assessment (SOFA) score, and introducing the quick SOFA (qSOFA) score.¹

The qSOFA combines 3 clinical variables to provide a rapid, simple bedside score that measures the likelihood of poor outcomes, such as admission to an intensive care unit (ICU) or mortality in adults with suspected infection.^1,3 The qSOFA score is intended to aid healthcare professionals in more timely stratification of those patients who need escalated care to prevent deterioration.¹ The assessment also has been explored as a screening tool for sepsis in clinical practice; however, limited data exists concerning the comparative utility of qSOFA and SIRS in this capacity, and study results are inconsistent.^4-6

The most important attribute of a screening tool is high sensitivity, but high specificity also is desired. The qSOFA could supplant SIRS as a screening tool for sepsis if it maintained similarly high sensitivity but achieved superior specificity. Therefore, our primary objective for this study was to determine the effectiveness of qSOFA as a screening assessment for sepsis in the setting of a general inpatient medicine service by contrasting the sensitivity and specificity of qSOFA with SIRS in predicting sepsis, using a retrospective chart review design.

Methods

Administrative data from the Department of Veterans Affairs (VA) Corporate Data Warehouse were accessed via the VA Informatics and Computing Infrastructure (VINCI) and used to identify VA inpatient admissions and obtain the laboratory and vital sign data necessary to calculate SIRS, qSOFA, and SOFA scores. The data were supplemented by manual review of VA health records to obtain information that was not readily available in administrative records, including septic shock outcomes and laboratory and vital sign data obtained in the ICU. This study was approved by the institutional review board at the University of Iowa and the research and development committee at the Iowa City VA Medical Center (ICVAMC).

Patients

The study population included veterans admitted to the nonsurgical medicine unit at ICVAMC between August 1, 2014 and August 1, 2016 who were transferred to an ICU after admission; direct ICU admissions were not included as the qSOFA has been shown in studies to be more beneficial and offer better predictive validity outside the ICU. Excluding these direct admissions prevented any potential skewing of the data. To control for possible selection bias, veterans also were excluded if they transferred from another facility, were admitted under observation status, or if they had been admitted within the prior 30 days. These patients may have been more critically ill than those who presented directly to our facility and any prior treatment could affect the clinical status of the patient and assessment for sepsis at the time of presentation to the VA. Veterans were further required to have evidence of suspected infection based on manual review of the health record, which was determined by receipt of an antibiotic relevant to the empiric treatment of sepsis within 48 hours of admission.

 

Sepsis and Septic Shock Assessment Tools

As outlined in the Sepsis-3 guidelines, sepsis was defined as suspected or confirmed infection with an acute change in the SOFA score of ≥ 2 points, which is assumed to be 0 in those not known to have preexisting dysfunction.¹ The SOFA score includes variables from the respiratory, coagulation, hepatic, cardiovascular, renal, and central nervous systems.¹ Septic shock was defined as vasopressor administration and a serum lactic acid level > 2 mmol/L occurring up to 24 hours apart and within 3 days of the first antibiotic dose administered.

The SIRS assessment includes 4 clinical variables (temperature, heart rate, respiratory rate, and white blood cell count) while qSOFA is comprised of 3 variables (respiratory rate, systolic blood pressure, and altered mental status).¹ With both assessments, a score ≥ 2 is considered positive, which indicates increased risk for sepsis in patients with suspected infection.¹ In keeping with existing studies, qSOFA and SIRS assessments were scored using maximum values found within 48 hours before and 24 hours after the first administered antibiotic dose.³

Outcomes

The primary outcome variable was the presence of sepsis in adults with evidence of infection within 48 hours of admission. Secondary outcome measures included 30-day mortality and septic shock.

Performance between the SIRS and qSOFA assessments was contrasted using sensitivity, specificity, and positive and negative predictive value measurements. Associations of qSOFA and SIRS with septic shock and 30-day mortality were evaluated using a 2-tailed Fisher’s exact test with a threshold of α = 0.05 to determine statistical significance.

Results

The study sample of 481 veterans had a mean age of 67.4 years, 94% were male, and 91.1% were white (Table 1). 

When predicting risk for sepsis, the qSOFA demonstrated lower sensitivity than SIRS (44.7% vs 80.0%) but higher specificity (83.6% vs 25.7%) and higher positive predictive value (75.5% vs 54.8%) than did SIRS (Table 2). Specificity and positive predictive value results indicated a good probability that veterans with positive qSOFA assessments actually had sepsis.

Scores for qSOFA, but not SIRS, were significantly associated with septic shock (Fisher’s exact test; qSOFA: P = .009; SIRS: P = .58) (Table 3). 

Both assessments were significantly associated with increased risk for 30-day mortality (Fisher’s exact test; qSOFA: P < .001; SIRS: P = .025). In an additional analysis, scores for SOFA were not significantly associated with septic shock (Fisher’s exact test, P = .13) but were significantly associated with an increased risk for 30-day mortality (Fisher’s exact test, P = .016) (Table 4).

Discussion

High sensitivity is critical for a sepsis screening tool. To be clinically useful, it has been suggested that biomarkers predicting poor outcomes for sepsis should have a sensitivity of > 80%.⁴ Although qSOFA demonstrated greater specificity than SIRS in our study (83.6% vs 25.7%), qSOFA showed lower sensitivity (44.7% vs 80.0%), which resulted in a greater potential for false negatives; 55.3% of those with sepsis would go undetected. Therefore, our study does not support qSOFA as a better screening assessment than SIRS for sepsis in the veteran population.

 

Most studies concur with our findings of low sensitivity and high specificity of qSOFA. In a systematic review and meta-analysis, Serafim and colleagues identified 10 studies published after Sepsis-3 that reported sensitivity or specificity of qSOFA and SIRS for sepsis diagnosis.⁵ Seven of the 10 studies reported sensitivities and favored SIRS in the diagnosis of sepsis (Relative risk: 1.32; 95% CI: 0.40-2.24; P < .0001; I² = 100%). The authors noted that substantial heterogeneity among studies, including differences in study design, sample size, and criteria for determination of infection, was an important limitation. In addition, most studies that contrast qSOFA and SIRS center on prognostic value in predicting mortality, rather than as a screening test for a diagnosis of sepsis.

We concluded SIRS was more sensitive and thus superior to qSOFA when used as a screening tool for sepsis but conceded that more prospective and homogenous investigations were necessary. To our knowledge, only 1 published study has deviated from this conclusion and reported comparable sensitivity between SIRS (92%) and qSOFA (90%).⁶ Our study adds to existing literature as it is the first conducted in a veteran population. Additionally, we performed our investigation in a general medicine population with methods similar to existing literature, including the key study validating clinical criteria for sepsis by Seymour and colleagues.³

Limitations

This study is not without limitations, including potential misclassification of cases if essential data points were not available during data collection via health record review or the data points were not representative of a true change from baseline (eg, the Glasgow Coma Scale score for altered mental status in the qSOFA or the SOFA score for organ dysfunction). Generalizability of the results also may be limited due to our retrospective, single-center design and characteristics typical of a veteran population (eg, older, white males). Additionally, many veterans were excluded from the study if they transferred from another facility. These veterans may have been more critically ill than those who presented directly to our facility, which possibly introduced selection bias.

Conclusion

Our findings do not support use of the qSOFA as a suitable replacement for SIRS as a sepsis screening tool among patients with suspected infection in the general medicine inpatient setting. The clinical concern with SIRS is that unfavorable specificity leads to unnecessary antibiotic exposure among patients who are falsely positive. While qSOFA has demonstrated higher specificity, its use would cause many sepsis cases to go undetected due to the technique’s low sensitivity. Frequent false negative qSOFA results could thus serve to impede, rather than enhance, early recognition and intervention for sepsis.

The ideal sepsis screening tool is rapid and possesses high sensitivity and specificity to promptly identify and manage sepsis and avert unfavorable outcomes such as septic shock and death. While the SIRS criteria do not satisfy these ideal features, its measurement characteristics are more suitable for the application of sepsis screening than the qSOFA and should thus remain the standard tool in this setting. Future prospectively designed studies with more uniform methodologies are necessary to ascertain the most effective approach to identify sepsis for which novel screening approaches with more clinically suitable measurement properties are greatly needed.

Acknowledgements
This research was supported by the Iowa City VA Health Care System, Department of Pharmacy Services. Additional support was provided by the Health Services Research and Development Service, Department of Veterans Affairs.

 

Sepsis is a major public health concern: 10% of patients with sepsis die, and mortality quadruples with progression to septic shock.¹ Systemic inflammatory response syndrome (SIRS) criteria, originally published in 1992, are commonly used to detect sepsis, but as early as 2001, these criteria were recognized as lacking specificity.² Nonetheless, the use of SIRS criteria has persisted in practice. Sepsis was redefined in Sepsis-3 (2016) to guide earlier and more appropriate identification and treatment, which has been shown to greatly improve patient outcomes.^1,3 Key recommendations in Sepsis 3 included eliminating SIRS criteria, defining organ dysfunction by the Sequential Organ Failure Assessment (SOFA) score, and introducing the quick SOFA (qSOFA) score.¹

The qSOFA combines 3 clinical variables to provide a rapid, simple bedside score that measures the likelihood of poor outcomes, such as admission to an intensive care unit (ICU) or mortality in adults with suspected infection.^1,3 The qSOFA score is intended to aid healthcare professionals in more timely stratification of those patients who need escalated care to prevent deterioration.¹ The assessment also has been explored as a screening tool for sepsis in clinical practice; however, limited data exists concerning the comparative utility of qSOFA and SIRS in this capacity, and study results are inconsistent.^4-6

The most important attribute of a screening tool is high sensitivity, but high specificity also is desired. The qSOFA could supplant SIRS as a screening tool for sepsis if it maintained similarly high sensitivity but achieved superior specificity. Therefore, our primary objective for this study was to determine the effectiveness of qSOFA as a screening assessment for sepsis in the setting of a general inpatient medicine service by contrasting the sensitivity and specificity of qSOFA with SIRS in predicting sepsis, using a retrospective chart review design.

Methods

Administrative data from the Department of Veterans Affairs (VA) Corporate Data Warehouse were accessed via the VA Informatics and Computing Infrastructure (VINCI) and used to identify VA inpatient admissions and obtain the laboratory and vital sign data necessary to calculate SIRS, qSOFA, and SOFA scores. The data were supplemented by manual review of VA health records to obtain information that was not readily available in administrative records, including septic shock outcomes and laboratory and vital sign data obtained in the ICU. This study was approved by the institutional review board at the University of Iowa and the research and development committee at the Iowa City VA Medical Center (ICVAMC).

Patients

The study population included veterans admitted to the nonsurgical medicine unit at ICVAMC between August 1, 2014 and August 1, 2016 who were transferred to an ICU after admission; direct ICU admissions were not included as the qSOFA has been shown in studies to be more beneficial and offer better predictive validity outside the ICU. Excluding these direct admissions prevented any potential skewing of the data. To control for possible selection bias, veterans also were excluded if they transferred from another facility, were admitted under observation status, or if they had been admitted within the prior 30 days. These patients may have been more critically ill than those who presented directly to our facility and any prior treatment could affect the clinical status of the patient and assessment for sepsis at the time of presentation to the VA. Veterans were further required to have evidence of suspected infection based on manual review of the health record, which was determined by receipt of an antibiotic relevant to the empiric treatment of sepsis within 48 hours of admission.

 

Sepsis and Septic Shock Assessment Tools

As outlined in the Sepsis-3 guidelines, sepsis was defined as suspected or confirmed infection with an acute change in the SOFA score of ≥ 2 points, which is assumed to be 0 in those not known to have preexisting dysfunction.¹ The SOFA score includes variables from the respiratory, coagulation, hepatic, cardiovascular, renal, and central nervous systems.¹ Septic shock was defined as vasopressor administration and a serum lactic acid level > 2 mmol/L occurring up to 24 hours apart and within 3 days of the first antibiotic dose administered.

The SIRS assessment includes 4 clinical variables (temperature, heart rate, respiratory rate, and white blood cell count) while qSOFA is comprised of 3 variables (respiratory rate, systolic blood pressure, and altered mental status).¹ With both assessments, a score ≥ 2 is considered positive, which indicates increased risk for sepsis in patients with suspected infection.¹ In keeping with existing studies, qSOFA and SIRS assessments were scored using maximum values found within 48 hours before and 24 hours after the first administered antibiotic dose.³

Outcomes

The primary outcome variable was the presence of sepsis in adults with evidence of infection within 48 hours of admission. Secondary outcome measures included 30-day mortality and septic shock.

Performance between the SIRS and qSOFA assessments was contrasted using sensitivity, specificity, and positive and negative predictive value measurements. Associations of qSOFA and SIRS with septic shock and 30-day mortality were evaluated using a 2-tailed Fisher’s exact test with a threshold of α = 0.05 to determine statistical significance.

Results

The study sample of 481 veterans had a mean age of 67.4 years, 94% were male, and 91.1% were white (Table 1). 

When predicting risk for sepsis, the qSOFA demonstrated lower sensitivity than SIRS (44.7% vs 80.0%) but higher specificity (83.6% vs 25.7%) and higher positive predictive value (75.5% vs 54.8%) than did SIRS (Table 2). Specificity and positive predictive value results indicated a good probability that veterans with positive qSOFA assessments actually had sepsis.

Scores for qSOFA, but not SIRS, were significantly associated with septic shock (Fisher’s exact test; qSOFA: P = .009; SIRS: P = .58) (Table 3). 

Both assessments were significantly associated with increased risk for 30-day mortality (Fisher’s exact test; qSOFA: P < .001; SIRS: P = .025). In an additional analysis, scores for SOFA were not significantly associated with septic shock (Fisher’s exact test, P = .13) but were significantly associated with an increased risk for 30-day mortality (Fisher’s exact test, P = .016) (Table 4).

Discussion

High sensitivity is critical for a sepsis screening tool. To be clinically useful, it has been suggested that biomarkers predicting poor outcomes for sepsis should have a sensitivity of > 80%.⁴ Although qSOFA demonstrated greater specificity than SIRS in our study (83.6% vs 25.7%), qSOFA showed lower sensitivity (44.7% vs 80.0%), which resulted in a greater potential for false negatives; 55.3% of those with sepsis would go undetected. Therefore, our study does not support qSOFA as a better screening assessment than SIRS for sepsis in the veteran population.

 

Most studies concur with our findings of low sensitivity and high specificity of qSOFA. In a systematic review and meta-analysis, Serafim and colleagues identified 10 studies published after Sepsis-3 that reported sensitivity or specificity of qSOFA and SIRS for sepsis diagnosis.⁵ Seven of the 10 studies reported sensitivities and favored SIRS in the diagnosis of sepsis (Relative risk: 1.32; 95% CI: 0.40-2.24; P < .0001; I² = 100%). The authors noted that substantial heterogeneity among studies, including differences in study design, sample size, and criteria for determination of infection, was an important limitation. In addition, most studies that contrast qSOFA and SIRS center on prognostic value in predicting mortality, rather than as a screening test for a diagnosis of sepsis.

We concluded SIRS was more sensitive and thus superior to qSOFA when used as a screening tool for sepsis but conceded that more prospective and homogenous investigations were necessary. To our knowledge, only 1 published study has deviated from this conclusion and reported comparable sensitivity between SIRS (92%) and qSOFA (90%).⁶ Our study adds to existing literature as it is the first conducted in a veteran population. Additionally, we performed our investigation in a general medicine population with methods similar to existing literature, including the key study validating clinical criteria for sepsis by Seymour and colleagues.³

Limitations

This study is not without limitations, including potential misclassification of cases if essential data points were not available during data collection via health record review or the data points were not representative of a true change from baseline (eg, the Glasgow Coma Scale score for altered mental status in the qSOFA or the SOFA score for organ dysfunction). Generalizability of the results also may be limited due to our retrospective, single-center design and characteristics typical of a veteran population (eg, older, white males). Additionally, many veterans were excluded from the study if they transferred from another facility. These veterans may have been more critically ill than those who presented directly to our facility, which possibly introduced selection bias.

Conclusion

Our findings do not support use of the qSOFA as a suitable replacement for SIRS as a sepsis screening tool among patients with suspected infection in the general medicine inpatient setting. The clinical concern with SIRS is that unfavorable specificity leads to unnecessary antibiotic exposure among patients who are falsely positive. While qSOFA has demonstrated higher specificity, its use would cause many sepsis cases to go undetected due to the technique’s low sensitivity. Frequent false negative qSOFA results could thus serve to impede, rather than enhance, early recognition and intervention for sepsis.

The ideal sepsis screening tool is rapid and possesses high sensitivity and specificity to promptly identify and manage sepsis and avert unfavorable outcomes such as septic shock and death. While the SIRS criteria do not satisfy these ideal features, its measurement characteristics are more suitable for the application of sepsis screening than the qSOFA and should thus remain the standard tool in this setting. Future prospectively designed studies with more uniform methodologies are necessary to ascertain the most effective approach to identify sepsis for which novel screening approaches with more clinically suitable measurement properties are greatly needed.

Acknowledgements
This research was supported by the Iowa City VA Health Care System, Department of Pharmacy Services. Additional support was provided by the Health Services Research and Development Service, Department of Veterans Affairs.

 

Sepsis is a major public health concern: 10% of patients with sepsis die, and mortality quadruples with progression to septic shock.¹ Systemic inflammatory response syndrome (SIRS) criteria, originally published in 1992, are commonly used to detect sepsis, but as early as 2001, these criteria were recognized as lacking specificity.² Nonetheless, the use of SIRS criteria has persisted in practice. Sepsis was redefined in Sepsis-3 (2016) to guide earlier and more appropriate identification and treatment, which has been shown to greatly improve patient outcomes.^1,3 Key recommendations in Sepsis 3 included eliminating SIRS criteria, defining organ dysfunction by the Sequential Organ Failure Assessment (SOFA) score, and introducing the quick SOFA (qSOFA) score.¹

The qSOFA combines 3 clinical variables to provide a rapid, simple bedside score that measures the likelihood of poor outcomes, such as admission to an intensive care unit (ICU) or mortality in adults with suspected infection.^1,3 The qSOFA score is intended to aid healthcare professionals in more timely stratification of those patients who need escalated care to prevent deterioration.¹ The assessment also has been explored as a screening tool for sepsis in clinical practice; however, limited data exists concerning the comparative utility of qSOFA and SIRS in this capacity, and study results are inconsistent.^4-6

The most important attribute of a screening tool is high sensitivity, but high specificity also is desired. The qSOFA could supplant SIRS as a screening tool for sepsis if it maintained similarly high sensitivity but achieved superior specificity. Therefore, our primary objective for this study was to determine the effectiveness of qSOFA as a screening assessment for sepsis in the setting of a general inpatient medicine service by contrasting the sensitivity and specificity of qSOFA with SIRS in predicting sepsis, using a retrospective chart review design.

Methods

Administrative data from the Department of Veterans Affairs (VA) Corporate Data Warehouse were accessed via the VA Informatics and Computing Infrastructure (VINCI) and used to identify VA inpatient admissions and obtain the laboratory and vital sign data necessary to calculate SIRS, qSOFA, and SOFA scores. The data were supplemented by manual review of VA health records to obtain information that was not readily available in administrative records, including septic shock outcomes and laboratory and vital sign data obtained in the ICU. This study was approved by the institutional review board at the University of Iowa and the research and development committee at the Iowa City VA Medical Center (ICVAMC).

Patients

The study population included veterans admitted to the nonsurgical medicine unit at ICVAMC between August 1, 2014 and August 1, 2016 who were transferred to an ICU after admission; direct ICU admissions were not included as the qSOFA has been shown in studies to be more beneficial and offer better predictive validity outside the ICU. Excluding these direct admissions prevented any potential skewing of the data. To control for possible selection bias, veterans also were excluded if they transferred from another facility, were admitted under observation status, or if they had been admitted within the prior 30 days. These patients may have been more critically ill than those who presented directly to our facility and any prior treatment could affect the clinical status of the patient and assessment for sepsis at the time of presentation to the VA. Veterans were further required to have evidence of suspected infection based on manual review of the health record, which was determined by receipt of an antibiotic relevant to the empiric treatment of sepsis within 48 hours of admission.

 

Sepsis and Septic Shock Assessment Tools

As outlined in the Sepsis-3 guidelines, sepsis was defined as suspected or confirmed infection with an acute change in the SOFA score of ≥ 2 points, which is assumed to be 0 in those not known to have preexisting dysfunction.¹ The SOFA score includes variables from the respiratory, coagulation, hepatic, cardiovascular, renal, and central nervous systems.¹ Septic shock was defined as vasopressor administration and a serum lactic acid level > 2 mmol/L occurring up to 24 hours apart and within 3 days of the first antibiotic dose administered.

The SIRS assessment includes 4 clinical variables (temperature, heart rate, respiratory rate, and white blood cell count) while qSOFA is comprised of 3 variables (respiratory rate, systolic blood pressure, and altered mental status).¹ With both assessments, a score ≥ 2 is considered positive, which indicates increased risk for sepsis in patients with suspected infection.¹ In keeping with existing studies, qSOFA and SIRS assessments were scored using maximum values found within 48 hours before and 24 hours after the first administered antibiotic dose.³

Outcomes

The primary outcome variable was the presence of sepsis in adults with evidence of infection within 48 hours of admission. Secondary outcome measures included 30-day mortality and septic shock.

Performance between the SIRS and qSOFA assessments was contrasted using sensitivity, specificity, and positive and negative predictive value measurements. Associations of qSOFA and SIRS with septic shock and 30-day mortality were evaluated using a 2-tailed Fisher’s exact test with a threshold of α = 0.05 to determine statistical significance.

Results

The study sample of 481 veterans had a mean age of 67.4 years, 94% were male, and 91.1% were white (Table 1). 

When predicting risk for sepsis, the qSOFA demonstrated lower sensitivity than SIRS (44.7% vs 80.0%) but higher specificity (83.6% vs 25.7%) and higher positive predictive value (75.5% vs 54.8%) than did SIRS (Table 2). Specificity and positive predictive value results indicated a good probability that veterans with positive qSOFA assessments actually had sepsis.

Scores for qSOFA, but not SIRS, were significantly associated with septic shock (Fisher’s exact test; qSOFA: P = .009; SIRS: P = .58) (Table 3). 

Both assessments were significantly associated with increased risk for 30-day mortality (Fisher’s exact test; qSOFA: P < .001; SIRS: P = .025). In an additional analysis, scores for SOFA were not significantly associated with septic shock (Fisher’s exact test, P = .13) but were significantly associated with an increased risk for 30-day mortality (Fisher’s exact test, P = .016) (Table 4).

Discussion

High sensitivity is critical for a sepsis screening tool. To be clinically useful, it has been suggested that biomarkers predicting poor outcomes for sepsis should have a sensitivity of > 80%.⁴ Although qSOFA demonstrated greater specificity than SIRS in our study (83.6% vs 25.7%), qSOFA showed lower sensitivity (44.7% vs 80.0%), which resulted in a greater potential for false negatives; 55.3% of those with sepsis would go undetected. Therefore, our study does not support qSOFA as a better screening assessment than SIRS for sepsis in the veteran population.

 

Most studies concur with our findings of low sensitivity and high specificity of qSOFA. In a systematic review and meta-analysis, Serafim and colleagues identified 10 studies published after Sepsis-3 that reported sensitivity or specificity of qSOFA and SIRS for sepsis diagnosis.⁵ Seven of the 10 studies reported sensitivities and favored SIRS in the diagnosis of sepsis (Relative risk: 1.32; 95% CI: 0.40-2.24; P < .0001; I² = 100%). The authors noted that substantial heterogeneity among studies, including differences in study design, sample size, and criteria for determination of infection, was an important limitation. In addition, most studies that contrast qSOFA and SIRS center on prognostic value in predicting mortality, rather than as a screening test for a diagnosis of sepsis.

We concluded SIRS was more sensitive and thus superior to qSOFA when used as a screening tool for sepsis but conceded that more prospective and homogenous investigations were necessary. To our knowledge, only 1 published study has deviated from this conclusion and reported comparable sensitivity between SIRS (92%) and qSOFA (90%).⁶ Our study adds to existing literature as it is the first conducted in a veteran population. Additionally, we performed our investigation in a general medicine population with methods similar to existing literature, including the key study validating clinical criteria for sepsis by Seymour and colleagues.³

Limitations

This study is not without limitations, including potential misclassification of cases if essential data points were not available during data collection via health record review or the data points were not representative of a true change from baseline (eg, the Glasgow Coma Scale score for altered mental status in the qSOFA or the SOFA score for organ dysfunction). Generalizability of the results also may be limited due to our retrospective, single-center design and characteristics typical of a veteran population (eg, older, white males). Additionally, many veterans were excluded from the study if they transferred from another facility. These veterans may have been more critically ill than those who presented directly to our facility, which possibly introduced selection bias.

Conclusion

Our findings do not support use of the qSOFA as a suitable replacement for SIRS as a sepsis screening tool among patients with suspected infection in the general medicine inpatient setting. The clinical concern with SIRS is that unfavorable specificity leads to unnecessary antibiotic exposure among patients who are falsely positive. While qSOFA has demonstrated higher specificity, its use would cause many sepsis cases to go undetected due to the technique’s low sensitivity. Frequent false negative qSOFA results could thus serve to impede, rather than enhance, early recognition and intervention for sepsis.

The ideal sepsis screening tool is rapid and possesses high sensitivity and specificity to promptly identify and manage sepsis and avert unfavorable outcomes such as septic shock and death. While the SIRS criteria do not satisfy these ideal features, its measurement characteristics are more suitable for the application of sepsis screening than the qSOFA and should thus remain the standard tool in this setting. Future prospectively designed studies with more uniform methodologies are necessary to ascertain the most effective approach to identify sepsis for which novel screening approaches with more clinically suitable measurement properties are greatly needed.

Acknowledgements
This research was supported by the Iowa City VA Health Care System, Department of Pharmacy Services. Additional support was provided by the Health Services Research and Development Service, Department of Veterans Affairs.

 

Population studies show high prevalence of chronic hepatitis C virus (HCV) infection among veterans, especially Vietnam War era veterans.^1,2 The development of safe and efficacious direct-acting antiviral (DAA) medications to treat HCV infection made the majority of those infected eligible for treatment. However, the large number of veterans needing DAA treatment stressed the resources of the US Department of Veterans Affairs (VA) health care system. This occurred while Congress was focused on reducing wait times for veterans receiving care at the VA.

Congress passed the Veterans Access, Choice, and Accountability Act (Choice) on August 7, 2014, leading to the creation of the Veterans Choice Program. Legislators felt there were inappropriate delays in care at the VA, and the Choice program was meant to address this problem and provide an “apples-to-apples comparison [of the VA] with non-VA hospitals.”³

Congress acknowledged the importance of curing HCV in the veteran population and allocated $1.5 billion for fiscal year (FY) 2016 for DAAs. The VA Central Office (VACO) carefully monitored these resources. The first policy memorandum from VACO for HCV care, issued on May 21, 2015, recommended that the sickest patients who will benefit from the treatment “receive priority over those who are less ill.”^4,5 Those who met criteria for advanced liver disease were prioritized for treatment at the VA, while those who did not meet criteria were given the option of receiving treatment through Choice, or waiting for a change in policy.⁶ Over time, revisions to the guidelines relaxed the criteria for VA treatment eligibility, and on February 24, 2016, all restrictions on HCV treatment at the VA were lifted.^7,8

The aim of this study was to provide a comparison of VA and non-VA care, specifically to determine whether care provided through Choice was timelier and more cost effective than care provided by the VA, and whether there was a quality difference. The high prevalence among veterans, well-established standards of care, and finite treatment course with clear indicators of success and failure makes HCV treatment an ideal disease with which to make this comparison.

Methods

We retrospectively analyzed the VA electronic health records of all veterans seen in the VA Loma Linda Healthcare System (VALLHCS) Hepatology clinic for chronic HCV infection during FY 2016 who were referred to Choice for HCV treatment. One hundred veterans met these criteria, encompassing the Choice population; 71 were seen at least once by a non-VA (Choice) health care provider (HCP) and 61 completed a treatment regimen through Choice. Treatment completion was defined as cessation of medication after the planned duration of therapy, or early termination of medication without resumption by that HCP. The Choice population was matched to an equal number of veterans who received HCV treatment from VALLHCS HCPs.

Data collected included age, gender, HCV genotype, determinants of liver fibrosis, and treatment success (defined as sustained virologic response at 12 weeks after the last dose of medication [SVR12]). Determinants of liver fibrosis included documented cirrhosis or complications of cirrhosis, Fibrosis-4 score (Fib-4), and platelet count.

Treatment failures were categorized as nonresponse (defined as detectable HCV viral load at the end of treatment), relapse (defined as an undetectable HCV viral load at the end of treatment with a subsequent positive test), and early termination (defined as a failure to complete the planned treatment regimen). Documented patient nonadherence, medical comorbidities that affected the treatment protocol, mental health diagnoses, and active social issues (defined as active or history of heavy alcohol use, active or history of illicit drug use, lack of social support, and homelessness) were noted.

Timeliness of delivery of care was measured in days. For the VA group, the wait time was defined as the date the consult for HCV treatment was placed to the date of the initial appointment with the HCV treatment provider. For the Choice group, the wait time was defined as the date the referral to the Choice program was made to the date of the initial appointment with the Choice HCP. Treatment regimens were evaluated for appropriateness based on guidelines from VACO and the American Association for the Study of Liver Diseases.^9-11

Tests performed by Choice providers were evaluated for whether they were relevant to HCV care and whether similar data already were available from VALLHCS. Tests that were not indicated were identified as unnecessary costs incurred by the Choice program, as were tests that had to be repeated at the VA because of a lack of documentation from the Choice provider. All medications given inappropriately were considered added costs. Medicare reimbursement rates for the most applicable Current Procedural Terminology (CPT) code and VA national contract pricing for medications were used for calculations. This study was approved by the VALLHCS institutional review board.

 

Statistical Analysis

IBM (Armonk, NY) Statistical Package for Social Sciences software was used to evaluate for differences in Fib-4, platelet count, prevalence of cirrhosis, prevalence of medical comorbidities, prevalence of mental health comorbidities, prevalence of the social issues defined in the Methods section, time from referral to time of appointment date, and SVR12 rate between the VA and Choice groups.

Exclusions

There were 15 veterans in the VA group who had a wait time of > 100 days. Of these, 5 (33%) were initially Choice referrals, but due to negative interactions with the Choice provider, the veterans returned to VALLHCS for care. Two of the 15 (13%) did not keep appointments and were lost to follow up. Six of the 15 (40%) had medical comorbidities that required more immediate attention, so HCV treatment initiation was deliberately moved back. The final 2 veterans scheduled their appointments unusually far apart, artificially increasing their wait time. Given that these were unique situations and some of the veterans received care from both Choice and VA providers, a decision was made to exclude these individuals from the study.

It has been shown that platelet count correlates with degree of liver fibrosis, a concept that is the basis for the Fib-4 scoring system.¹² Studies have shown that platelet count is a survival predictor in those with cirrhosis, and thrombocytopenia is a negative predictor of HCV treatment success using peginterferon and ribavirin.^13,14 Therefore, the VA memorandum automatically assigned the sickest individuals to the VA for HCV treatment. The goal of this study was to compare the impact of factors other than stage of fibrosis on HCV treatment success, which is why the 12 veterans with platelet count < 100,000 in the VA group were excluded. There were no veterans with platelet count < 100,000 in the Choice group.

When comparing SVR12 rates between the VA and Choice groups, every veteran treated at VALLHCS in FY 2016 was included, increasing the number in the VA group from 100 to 320 and therefore the power of this comparison.

Results

A summary of the statistical analysis can be found in Table 1. The genotype distribution was consistent with epidemiological studies, including those specific to veterans.^15,16 There were statistically significant differences (P < .001) in mean Fib-4 and mean platelet count. The VA group had a higher Fib-4 and lower platelet count. Seventy-four percent of the VA population was defined as cirrhotic, while only 3% of the Choice population met similar criteria (P < .001). The VA and Choice groups were similar in terms of age, gender, and genotype distribution (Table 2).

The VA group was found to have a higher prevalence of comorbidities that affected HCV treatment. These conditions included but were not limited to: chronic kidney disease that precluded the use of certain medications, any condition that required medication with a known interaction with DAAs (ie, proton pump inhibitors, statins, and amiodarone), and cirrhosis if it impacted the treatment regimen. The difference in the prevalence of mental health comorbidities was not significant (P = .39), but there was a higher prevalence of social issues among the VA group (P = .002).

The mean wait time from referral to appointment was 28.6 days for the VA group and 42.3 days for the Choice group (P < .001), indicating that a Choice referral took longer to complete than a referral within the VA for HCV treatment. Thirty of the 71 (42%) veterans seen by a Choice provider accrued extraneous cost, with a mean additional cost of $8,561.40 per veteran. In the Choice group, 61 veterans completed a treatment regimen with the Choice HCP. Fifty-five veterans completed treatment and had available SVR12 data (6 were lost to follow up without SVR12 testing) and 50 (91%) had confirmed SVR12. The charts of the 5 treatment failures were reviewed to discern the cause for failure. Two cases involved early termination of therapy, 3 involved relapse and 2 failed to comply with medication instructions. There was 1 case of the Choice HCP not addressing simultaneous use of ledipasvir and a proton pump inhibitor, potentially causing an interaction, and 1 case where both the VA and Choice providers failed to recognize indicators of cirrhosis, which impacted the regimen used.

In the VALLHCS group, records of 320 veterans who completed treatment and had SVR12 testing were reviewed. While the Choice memorandum was active, veterans selected to be treated at VALLHCS had advanced liver fibrosis or cirrhosis, medical and mental health comorbidities that increased the risk of treatment complications or were considered to have difficulty adhering to the medication regimen. For this group, 296 (93%) had confirmed SVR12. Eighteen of the 24 (75%) treatment failures were complicated by nonadherence, including all 13 cases of early termination. One patient died from complications of decompensated cirrhosis before completing treatment, and 1 did not receive HCV medications during a hospital admission due to poor coordination of care between the VA inpatient and outpatient pharmacy services, leading to multiple missed doses.

 

The difference in SVR12 rates (ie, treatment failure rates), between the VA and Choice groups was not statistically significant (P = .61). None of the specific reasons for treatment failure had a statistically significant difference between groups. A treatment failure analysis is shown in Table 3, and Table 4 indicates the breakdown of treatment regimens.

 

Discussion

The Veterans Health Administration (VHA) is the largest integrated health care system in the US, consisting of 152 medical centers and > 1,700 sites of care. The VA has the potential to meet the health care needs of 21.6 million veterans. About 9 million veterans are enrolled in the VA system and 5.9 million received health care through VHA.¹⁷ However, every medical service cannot realistically be made available at every facility, and some veterans have difficulty gaining access to VHA care; distance and wait times have been well-publicized issues that need further exploration.^18,19 The Choice program is an attempt to meet gaps in VA coverage using non-VA HCPs.

HCV infection is a specific diagnosis with national treatment guidelines and well-studied treatments; it can be cured, with an evidence-based definition of cure. The VACO policy memorandum to refer less sick veterans to Choice while treating sicker veterans at the VA provided the opportunity to directly compare the quality of the 2 programs. The SVR12 rates of VALLHCS and Choice providers were comparable to the national average at the time, and while the difference in SVR12 rate was not significant, VALLHCS treated a significantly higher number of patients with cirrhosis because of the referral criteria.²⁰

The significant difference in medical comorbidities between the VA and Choice groups was not surprising, partly because of the referral criteria. Cirrhosis can impact the treatment regimen, especially in regard to use of ribavirin. Since the presence of mental health comorbidities did not affect selection into the Choice group, it makes sense that there was no significant difference in prevalence between the groups.

VACO allowed veterans with HCV treatment plans that VA HCPs felt were too complicated for the Choice program to be treated by VHA HCPs.⁹ VALLHCS exercised this right for veterans at risk for nonadherence, because in HCV treatment, nonadherence leads to treatment failure and development of drug resistant virus strains. Therefore, veterans who would have difficulty traveling to VALLHCS to pick up medications, those who lacked means of communication (such as those who were homeless), and those who had active substance abuse were treated at the VA, where closer monitoring and immediate access to a wide range of services was possible. Studies have confirmed the impact of these types of issues on HCV treatment adherence and success.²¹ This explains the higher prevalence of social issues in the VA group.

For an internal referral for HCV treatment at VALLHCS, the hepatology provider submits a consult request to the HCV treatment provider, who works in the same office, making direct communication simple. The main administrative limiting factor to minimizing wait times is the number of HCPs, which is dependent on hiring allowances.

When a veteran is referred to Choice, the VA provider places a consult for non-VA care, which the VA Office of Community Care processes by compiling relevant documents and sending the package to Triwest Healthcare Alliance, a private insurance processor contracted with the VA. Triwest selects the Choice provider, often without any input from the VA, and arranges the veteran’s initial appointment.²² Geographic distance to the veteran’s address is the main selection criteria for Triwest. Documents sent between the Choice and VA HCPs go through the Office of Community Care and Triwest. This significantly increases the potential for delays and failed communication. Triwest had a comprehensive list of providers deemed to be qualified to treat HCV within the geographic catchment of VALLHCS. This list was reviewed, and all veterans referred to Choice had HCPs near their home address; therefore, availability of Choice HCPs was not an issue.

The VA can provide guidance on management of the veteran in the form of bundle packages containing a list of services for which the Choice provider is authorized to provide, and ones the Choice provider is not authorized to provide. Some Choice HCPs ordered tests that were not authorized for HCV treatment such as esophagogastroduodenoscopy, colonoscopy, and liver biopsy. In all, 17 of 71 (24%) veterans seen by Choice HCPs had tests performed or ordered that VA HCPs would not have obtained for the purpose of HCV treatment (Table 5).

In order to prevent veterans from receiving unnecessary tests, a VALLHCS hepatologist asked to be notified by VA administrators overseeing Choice referrals whenever a secondary authorization request (SAR) was submitted by a Choice HCP. This strategy is not standard VA practice, therefore at many VA sites these requested tests would have been performed by the Choice HCP, which is why SARs were factored into cost analysis.

SVR12 test results that were drawn too early and had to be repeated at VALLHCS were a cost unique to the Choice program. Duplicate tests, particularly imaging studies and blood work, were extraneous costs. The largest extraneous costs were treatment regimens prescribed by Choice HCPs that did not follow standard of care and required VA provider intervention. Thirty of the 71 (42%) veterans seen by a Choice provider accrued a mean $8,561.40 in extra costs. As a result, the Choice program cost VHA $250,000 more to provide care for 30 veterans (enough to pay for a physician’s annual salary).

Some inappropriate treatment regimens were the result of Choice HCP error, such as 1 case in which a veteran was inadvertently switched from ledipasvir/sofosbuvir to ombitasvir/paritaprevir/ritonavir/dasabuvir after week 4. The veteran had to start therapy over but still achieved SVR12. Other cases saw veterans receive regimens for which they had clear contraindications, such as creatinine clearance < 30 mL/min/1.73m² for sofosbuvir or a positive resistance panel for specific medications. Eleven of 62 (18%) veterans who were started on HCV treatment by a Choice HCP received a regimen not consistent with VA guidelines—an alarming result.

Follow up for veterans referred to Choice was extremely labor intensive, and assessment of personnel requirements in a Choice-based VA system must take this into consideration. The Choice HCP has no obligation to communicate with the VA HCP. At the time of chart review, 57 of 71 (80%) Choice veterans had inadequate documentation to make a confident assessment of the treatment outcome. Multiple calls to the offices of the Choice HCP were needed to acquire records, and veterans had to be tracked down for additional tests. Veterans often would complete treatment and stop following up with the Choice provider before SVR12 confirmation. The VA hepatology provider reviewing Choice referrals served as clinician, case manager, and clerk in order to get veterans to an appropriate end point in their hepatitis C treatment, with mostly unmeasured hours of work.

 

Limitations

The study population size was limited by the number of veterans able to complete treatment through Choice. The parameters in the VACO policy memos automatically selected the VA and Choice groups but made them clinically distinct populations. New treatment medications were released during the study period, which impacted management strategy. Occasionally, VA and non-VA HCPs preferred different treatment regimens, leading to variation in the distribution of regimens used despite similar genotype distribution (Tables 2 and 4). In addition, a retrospective study is at risk for recall bias. A prospective study randomizing veterans to the Choice and VA groups is an important future endeavor. Comparing veteran satisfaction for Choice and VA services is also crucial.

Conclusions

This study demonstrates that the VA was able to provide more cost-effective and more timely care for HCV treatment to a relatively sicker population with no reduction in treatment success when compared with non-VA HCPs through the Choice program. While the Choice program can help veterans receive services they may otherwise not have access to and reduce travel time, the current system introduces inefficiencies that delay care and decrease cost-effectiveness. The Choice HCP selection process is based on proximity rather than quality, which may place the veteran at risk for receiving substandard care. Large-scale quality of care studies that compare efficiency measures, clinical outcomes, patient demographics, travel distance, cost efficacy and patient satisfaction for veterans receiving similar services at a VA facility and through Choice should be performed to ensure that veterans receive the best care available.

Population studies show high prevalence of chronic hepatitis C virus (HCV) infection among veterans, especially Vietnam War era veterans.^1,2 The development of safe and efficacious direct-acting antiviral (DAA) medications to treat HCV infection made the majority of those infected eligible for treatment. However, the large number of veterans needing DAA treatment stressed the resources of the US Department of Veterans Affairs (VA) health care system. This occurred while Congress was focused on reducing wait times for veterans receiving care at the VA.

Congress passed the Veterans Access, Choice, and Accountability Act (Choice) on August 7, 2014, leading to the creation of the Veterans Choice Program. Legislators felt there were inappropriate delays in care at the VA, and the Choice program was meant to address this problem and provide an “apples-to-apples comparison [of the VA] with non-VA hospitals.”³

Congress acknowledged the importance of curing HCV in the veteran population and allocated $1.5 billion for fiscal year (FY) 2016 for DAAs. The VA Central Office (VACO) carefully monitored these resources. The first policy memorandum from VACO for HCV care, issued on May 21, 2015, recommended that the sickest patients who will benefit from the treatment “receive priority over those who are less ill.”^4,5 Those who met criteria for advanced liver disease were prioritized for treatment at the VA, while those who did not meet criteria were given the option of receiving treatment through Choice, or waiting for a change in policy.⁶ Over time, revisions to the guidelines relaxed the criteria for VA treatment eligibility, and on February 24, 2016, all restrictions on HCV treatment at the VA were lifted.^7,8

The aim of this study was to provide a comparison of VA and non-VA care, specifically to determine whether care provided through Choice was timelier and more cost effective than care provided by the VA, and whether there was a quality difference. The high prevalence among veterans, well-established standards of care, and finite treatment course with clear indicators of success and failure makes HCV treatment an ideal disease with which to make this comparison.

Methods

We retrospectively analyzed the VA electronic health records of all veterans seen in the VA Loma Linda Healthcare System (VALLHCS) Hepatology clinic for chronic HCV infection during FY 2016 who were referred to Choice for HCV treatment. One hundred veterans met these criteria, encompassing the Choice population; 71 were seen at least once by a non-VA (Choice) health care provider (HCP) and 61 completed a treatment regimen through Choice. Treatment completion was defined as cessation of medication after the planned duration of therapy, or early termination of medication without resumption by that HCP. The Choice population was matched to an equal number of veterans who received HCV treatment from VALLHCS HCPs.

Data collected included age, gender, HCV genotype, determinants of liver fibrosis, and treatment success (defined as sustained virologic response at 12 weeks after the last dose of medication [SVR12]). Determinants of liver fibrosis included documented cirrhosis or complications of cirrhosis, Fibrosis-4 score (Fib-4), and platelet count.

Treatment failures were categorized as nonresponse (defined as detectable HCV viral load at the end of treatment), relapse (defined as an undetectable HCV viral load at the end of treatment with a subsequent positive test), and early termination (defined as a failure to complete the planned treatment regimen). Documented patient nonadherence, medical comorbidities that affected the treatment protocol, mental health diagnoses, and active social issues (defined as active or history of heavy alcohol use, active or history of illicit drug use, lack of social support, and homelessness) were noted.

Timeliness of delivery of care was measured in days. For the VA group, the wait time was defined as the date the consult for HCV treatment was placed to the date of the initial appointment with the HCV treatment provider. For the Choice group, the wait time was defined as the date the referral to the Choice program was made to the date of the initial appointment with the Choice HCP. Treatment regimens were evaluated for appropriateness based on guidelines from VACO and the American Association for the Study of Liver Diseases.^9-11

Tests performed by Choice providers were evaluated for whether they were relevant to HCV care and whether similar data already were available from VALLHCS. Tests that were not indicated were identified as unnecessary costs incurred by the Choice program, as were tests that had to be repeated at the VA because of a lack of documentation from the Choice provider. All medications given inappropriately were considered added costs. Medicare reimbursement rates for the most applicable Current Procedural Terminology (CPT) code and VA national contract pricing for medications were used for calculations. This study was approved by the VALLHCS institutional review board.

 

Statistical Analysis

IBM (Armonk, NY) Statistical Package for Social Sciences software was used to evaluate for differences in Fib-4, platelet count, prevalence of cirrhosis, prevalence of medical comorbidities, prevalence of mental health comorbidities, prevalence of the social issues defined in the Methods section, time from referral to time of appointment date, and SVR12 rate between the VA and Choice groups.

Exclusions

There were 15 veterans in the VA group who had a wait time of > 100 days. Of these, 5 (33%) were initially Choice referrals, but due to negative interactions with the Choice provider, the veterans returned to VALLHCS for care. Two of the 15 (13%) did not keep appointments and were lost to follow up. Six of the 15 (40%) had medical comorbidities that required more immediate attention, so HCV treatment initiation was deliberately moved back. The final 2 veterans scheduled their appointments unusually far apart, artificially increasing their wait time. Given that these were unique situations and some of the veterans received care from both Choice and VA providers, a decision was made to exclude these individuals from the study.

It has been shown that platelet count correlates with degree of liver fibrosis, a concept that is the basis for the Fib-4 scoring system.¹² Studies have shown that platelet count is a survival predictor in those with cirrhosis, and thrombocytopenia is a negative predictor of HCV treatment success using peginterferon and ribavirin.^13,14 Therefore, the VA memorandum automatically assigned the sickest individuals to the VA for HCV treatment. The goal of this study was to compare the impact of factors other than stage of fibrosis on HCV treatment success, which is why the 12 veterans with platelet count < 100,000 in the VA group were excluded. There were no veterans with platelet count < 100,000 in the Choice group.

When comparing SVR12 rates between the VA and Choice groups, every veteran treated at VALLHCS in FY 2016 was included, increasing the number in the VA group from 100 to 320 and therefore the power of this comparison.

Results

A summary of the statistical analysis can be found in Table 1. The genotype distribution was consistent with epidemiological studies, including those specific to veterans.^15,16 There were statistically significant differences (P < .001) in mean Fib-4 and mean platelet count. The VA group had a higher Fib-4 and lower platelet count. Seventy-four percent of the VA population was defined as cirrhotic, while only 3% of the Choice population met similar criteria (P < .001). The VA and Choice groups were similar in terms of age, gender, and genotype distribution (Table 2).

The VA group was found to have a higher prevalence of comorbidities that affected HCV treatment. These conditions included but were not limited to: chronic kidney disease that precluded the use of certain medications, any condition that required medication with a known interaction with DAAs (ie, proton pump inhibitors, statins, and amiodarone), and cirrhosis if it impacted the treatment regimen. The difference in the prevalence of mental health comorbidities was not significant (P = .39), but there was a higher prevalence of social issues among the VA group (P = .002).

The mean wait time from referral to appointment was 28.6 days for the VA group and 42.3 days for the Choice group (P < .001), indicating that a Choice referral took longer to complete than a referral within the VA for HCV treatment. Thirty of the 71 (42%) veterans seen by a Choice provider accrued extraneous cost, with a mean additional cost of $8,561.40 per veteran. In the Choice group, 61 veterans completed a treatment regimen with the Choice HCP. Fifty-five veterans completed treatment and had available SVR12 data (6 were lost to follow up without SVR12 testing) and 50 (91%) had confirmed SVR12. The charts of the 5 treatment failures were reviewed to discern the cause for failure. Two cases involved early termination of therapy, 3 involved relapse and 2 failed to comply with medication instructions. There was 1 case of the Choice HCP not addressing simultaneous use of ledipasvir and a proton pump inhibitor, potentially causing an interaction, and 1 case where both the VA and Choice providers failed to recognize indicators of cirrhosis, which impacted the regimen used.

In the VALLHCS group, records of 320 veterans who completed treatment and had SVR12 testing were reviewed. While the Choice memorandum was active, veterans selected to be treated at VALLHCS had advanced liver fibrosis or cirrhosis, medical and mental health comorbidities that increased the risk of treatment complications or were considered to have difficulty adhering to the medication regimen. For this group, 296 (93%) had confirmed SVR12. Eighteen of the 24 (75%) treatment failures were complicated by nonadherence, including all 13 cases of early termination. One patient died from complications of decompensated cirrhosis before completing treatment, and 1 did not receive HCV medications during a hospital admission due to poor coordination of care between the VA inpatient and outpatient pharmacy services, leading to multiple missed doses.

 

The difference in SVR12 rates (ie, treatment failure rates), between the VA and Choice groups was not statistically significant (P = .61). None of the specific reasons for treatment failure had a statistically significant difference between groups. A treatment failure analysis is shown in Table 3, and Table 4 indicates the breakdown of treatment regimens.

 

Discussion

The Veterans Health Administration (VHA) is the largest integrated health care system in the US, consisting of 152 medical centers and > 1,700 sites of care. The VA has the potential to meet the health care needs of 21.6 million veterans. About 9 million veterans are enrolled in the VA system and 5.9 million received health care through VHA.¹⁷ However, every medical service cannot realistically be made available at every facility, and some veterans have difficulty gaining access to VHA care; distance and wait times have been well-publicized issues that need further exploration.^18,19 The Choice program is an attempt to meet gaps in VA coverage using non-VA HCPs.

HCV infection is a specific diagnosis with national treatment guidelines and well-studied treatments; it can be cured, with an evidence-based definition of cure. The VACO policy memorandum to refer less sick veterans to Choice while treating sicker veterans at the VA provided the opportunity to directly compare the quality of the 2 programs. The SVR12 rates of VALLHCS and Choice providers were comparable to the national average at the time, and while the difference in SVR12 rate was not significant, VALLHCS treated a significantly higher number of patients with cirrhosis because of the referral criteria.²⁰

The significant difference in medical comorbidities between the VA and Choice groups was not surprising, partly because of the referral criteria. Cirrhosis can impact the treatment regimen, especially in regard to use of ribavirin. Since the presence of mental health comorbidities did not affect selection into the Choice group, it makes sense that there was no significant difference in prevalence between the groups.

VACO allowed veterans with HCV treatment plans that VA HCPs felt were too complicated for the Choice program to be treated by VHA HCPs.⁹ VALLHCS exercised this right for veterans at risk for nonadherence, because in HCV treatment, nonadherence leads to treatment failure and development of drug resistant virus strains. Therefore, veterans who would have difficulty traveling to VALLHCS to pick up medications, those who lacked means of communication (such as those who were homeless), and those who had active substance abuse were treated at the VA, where closer monitoring and immediate access to a wide range of services was possible. Studies have confirmed the impact of these types of issues on HCV treatment adherence and success.²¹ This explains the higher prevalence of social issues in the VA group.

For an internal referral for HCV treatment at VALLHCS, the hepatology provider submits a consult request to the HCV treatment provider, who works in the same office, making direct communication simple. The main administrative limiting factor to minimizing wait times is the number of HCPs, which is dependent on hiring allowances.

When a veteran is referred to Choice, the VA provider places a consult for non-VA care, which the VA Office of Community Care processes by compiling relevant documents and sending the package to Triwest Healthcare Alliance, a private insurance processor contracted with the VA. Triwest selects the Choice provider, often without any input from the VA, and arranges the veteran’s initial appointment.²² Geographic distance to the veteran’s address is the main selection criteria for Triwest. Documents sent between the Choice and VA HCPs go through the Office of Community Care and Triwest. This significantly increases the potential for delays and failed communication. Triwest had a comprehensive list of providers deemed to be qualified to treat HCV within the geographic catchment of VALLHCS. This list was reviewed, and all veterans referred to Choice had HCPs near their home address; therefore, availability of Choice HCPs was not an issue.

The VA can provide guidance on management of the veteran in the form of bundle packages containing a list of services for which the Choice provider is authorized to provide, and ones the Choice provider is not authorized to provide. Some Choice HCPs ordered tests that were not authorized for HCV treatment such as esophagogastroduodenoscopy, colonoscopy, and liver biopsy. In all, 17 of 71 (24%) veterans seen by Choice HCPs had tests performed or ordered that VA HCPs would not have obtained for the purpose of HCV treatment (Table 5).

In order to prevent veterans from receiving unnecessary tests, a VALLHCS hepatologist asked to be notified by VA administrators overseeing Choice referrals whenever a secondary authorization request (SAR) was submitted by a Choice HCP. This strategy is not standard VA practice, therefore at many VA sites these requested tests would have been performed by the Choice HCP, which is why SARs were factored into cost analysis.

SVR12 test results that were drawn too early and had to be repeated at VALLHCS were a cost unique to the Choice program. Duplicate tests, particularly imaging studies and blood work, were extraneous costs. The largest extraneous costs were treatment regimens prescribed by Choice HCPs that did not follow standard of care and required VA provider intervention. Thirty of the 71 (42%) veterans seen by a Choice provider accrued a mean $8,561.40 in extra costs. As a result, the Choice program cost VHA $250,000 more to provide care for 30 veterans (enough to pay for a physician’s annual salary).

Some inappropriate treatment regimens were the result of Choice HCP error, such as 1 case in which a veteran was inadvertently switched from ledipasvir/sofosbuvir to ombitasvir/paritaprevir/ritonavir/dasabuvir after week 4. The veteran had to start therapy over but still achieved SVR12. Other cases saw veterans receive regimens for which they had clear contraindications, such as creatinine clearance < 30 mL/min/1.73m² for sofosbuvir or a positive resistance panel for specific medications. Eleven of 62 (18%) veterans who were started on HCV treatment by a Choice HCP received a regimen not consistent with VA guidelines—an alarming result.

Follow up for veterans referred to Choice was extremely labor intensive, and assessment of personnel requirements in a Choice-based VA system must take this into consideration. The Choice HCP has no obligation to communicate with the VA HCP. At the time of chart review, 57 of 71 (80%) Choice veterans had inadequate documentation to make a confident assessment of the treatment outcome. Multiple calls to the offices of the Choice HCP were needed to acquire records, and veterans had to be tracked down for additional tests. Veterans often would complete treatment and stop following up with the Choice provider before SVR12 confirmation. The VA hepatology provider reviewing Choice referrals served as clinician, case manager, and clerk in order to get veterans to an appropriate end point in their hepatitis C treatment, with mostly unmeasured hours of work.

 

Limitations

The study population size was limited by the number of veterans able to complete treatment through Choice. The parameters in the VACO policy memos automatically selected the VA and Choice groups but made them clinically distinct populations. New treatment medications were released during the study period, which impacted management strategy. Occasionally, VA and non-VA HCPs preferred different treatment regimens, leading to variation in the distribution of regimens used despite similar genotype distribution (Tables 2 and 4). In addition, a retrospective study is at risk for recall bias. A prospective study randomizing veterans to the Choice and VA groups is an important future endeavor. Comparing veteran satisfaction for Choice and VA services is also crucial.

Conclusions

This study demonstrates that the VA was able to provide more cost-effective and more timely care for HCV treatment to a relatively sicker population with no reduction in treatment success when compared with non-VA HCPs through the Choice program. While the Choice program can help veterans receive services they may otherwise not have access to and reduce travel time, the current system introduces inefficiencies that delay care and decrease cost-effectiveness. The Choice HCP selection process is based on proximity rather than quality, which may place the veteran at risk for receiving substandard care. Large-scale quality of care studies that compare efficiency measures, clinical outcomes, patient demographics, travel distance, cost efficacy and patient satisfaction for veterans receiving similar services at a VA facility and through Choice should be performed to ensure that veterans receive the best care available.

Population studies show high prevalence of chronic hepatitis C virus (HCV) infection among veterans, especially Vietnam War era veterans.^1,2 The development of safe and efficacious direct-acting antiviral (DAA) medications to treat HCV infection made the majority of those infected eligible for treatment. However, the large number of veterans needing DAA treatment stressed the resources of the US Department of Veterans Affairs (VA) health care system. This occurred while Congress was focused on reducing wait times for veterans receiving care at the VA.

Congress passed the Veterans Access, Choice, and Accountability Act (Choice) on August 7, 2014, leading to the creation of the Veterans Choice Program. Legislators felt there were inappropriate delays in care at the VA, and the Choice program was meant to address this problem and provide an “apples-to-apples comparison [of the VA] with non-VA hospitals.”³

Congress acknowledged the importance of curing HCV in the veteran population and allocated $1.5 billion for fiscal year (FY) 2016 for DAAs. The VA Central Office (VACO) carefully monitored these resources. The first policy memorandum from VACO for HCV care, issued on May 21, 2015, recommended that the sickest patients who will benefit from the treatment “receive priority over those who are less ill.”^4,5 Those who met criteria for advanced liver disease were prioritized for treatment at the VA, while those who did not meet criteria were given the option of receiving treatment through Choice, or waiting for a change in policy.⁶ Over time, revisions to the guidelines relaxed the criteria for VA treatment eligibility, and on February 24, 2016, all restrictions on HCV treatment at the VA were lifted.^7,8

The aim of this study was to provide a comparison of VA and non-VA care, specifically to determine whether care provided through Choice was timelier and more cost effective than care provided by the VA, and whether there was a quality difference. The high prevalence among veterans, well-established standards of care, and finite treatment course with clear indicators of success and failure makes HCV treatment an ideal disease with which to make this comparison.

Methods

We retrospectively analyzed the VA electronic health records of all veterans seen in the VA Loma Linda Healthcare System (VALLHCS) Hepatology clinic for chronic HCV infection during FY 2016 who were referred to Choice for HCV treatment. One hundred veterans met these criteria, encompassing the Choice population; 71 were seen at least once by a non-VA (Choice) health care provider (HCP) and 61 completed a treatment regimen through Choice. Treatment completion was defined as cessation of medication after the planned duration of therapy, or early termination of medication without resumption by that HCP. The Choice population was matched to an equal number of veterans who received HCV treatment from VALLHCS HCPs.

Data collected included age, gender, HCV genotype, determinants of liver fibrosis, and treatment success (defined as sustained virologic response at 12 weeks after the last dose of medication [SVR12]). Determinants of liver fibrosis included documented cirrhosis or complications of cirrhosis, Fibrosis-4 score (Fib-4), and platelet count.

Treatment failures were categorized as nonresponse (defined as detectable HCV viral load at the end of treatment), relapse (defined as an undetectable HCV viral load at the end of treatment with a subsequent positive test), and early termination (defined as a failure to complete the planned treatment regimen). Documented patient nonadherence, medical comorbidities that affected the treatment protocol, mental health diagnoses, and active social issues (defined as active or history of heavy alcohol use, active or history of illicit drug use, lack of social support, and homelessness) were noted.

Timeliness of delivery of care was measured in days. For the VA group, the wait time was defined as the date the consult for HCV treatment was placed to the date of the initial appointment with the HCV treatment provider. For the Choice group, the wait time was defined as the date the referral to the Choice program was made to the date of the initial appointment with the Choice HCP. Treatment regimens were evaluated for appropriateness based on guidelines from VACO and the American Association for the Study of Liver Diseases.^9-11

Tests performed by Choice providers were evaluated for whether they were relevant to HCV care and whether similar data already were available from VALLHCS. Tests that were not indicated were identified as unnecessary costs incurred by the Choice program, as were tests that had to be repeated at the VA because of a lack of documentation from the Choice provider. All medications given inappropriately were considered added costs. Medicare reimbursement rates for the most applicable Current Procedural Terminology (CPT) code and VA national contract pricing for medications were used for calculations. This study was approved by the VALLHCS institutional review board.

 

Statistical Analysis

IBM (Armonk, NY) Statistical Package for Social Sciences software was used to evaluate for differences in Fib-4, platelet count, prevalence of cirrhosis, prevalence of medical comorbidities, prevalence of mental health comorbidities, prevalence of the social issues defined in the Methods section, time from referral to time of appointment date, and SVR12 rate between the VA and Choice groups.

Exclusions

There were 15 veterans in the VA group who had a wait time of > 100 days. Of these, 5 (33%) were initially Choice referrals, but due to negative interactions with the Choice provider, the veterans returned to VALLHCS for care. Two of the 15 (13%) did not keep appointments and were lost to follow up. Six of the 15 (40%) had medical comorbidities that required more immediate attention, so HCV treatment initiation was deliberately moved back. The final 2 veterans scheduled their appointments unusually far apart, artificially increasing their wait time. Given that these were unique situations and some of the veterans received care from both Choice and VA providers, a decision was made to exclude these individuals from the study.

It has been shown that platelet count correlates with degree of liver fibrosis, a concept that is the basis for the Fib-4 scoring system.¹² Studies have shown that platelet count is a survival predictor in those with cirrhosis, and thrombocytopenia is a negative predictor of HCV treatment success using peginterferon and ribavirin.^13,14 Therefore, the VA memorandum automatically assigned the sickest individuals to the VA for HCV treatment. The goal of this study was to compare the impact of factors other than stage of fibrosis on HCV treatment success, which is why the 12 veterans with platelet count < 100,000 in the VA group were excluded. There were no veterans with platelet count < 100,000 in the Choice group.

When comparing SVR12 rates between the VA and Choice groups, every veteran treated at VALLHCS in FY 2016 was included, increasing the number in the VA group from 100 to 320 and therefore the power of this comparison.

Results

A summary of the statistical analysis can be found in Table 1. The genotype distribution was consistent with epidemiological studies, including those specific to veterans.^15,16 There were statistically significant differences (P < .001) in mean Fib-4 and mean platelet count. The VA group had a higher Fib-4 and lower platelet count. Seventy-four percent of the VA population was defined as cirrhotic, while only 3% of the Choice population met similar criteria (P < .001). The VA and Choice groups were similar in terms of age, gender, and genotype distribution (Table 2).

The VA group was found to have a higher prevalence of comorbidities that affected HCV treatment. These conditions included but were not limited to: chronic kidney disease that precluded the use of certain medications, any condition that required medication with a known interaction with DAAs (ie, proton pump inhibitors, statins, and amiodarone), and cirrhosis if it impacted the treatment regimen. The difference in the prevalence of mental health comorbidities was not significant (P = .39), but there was a higher prevalence of social issues among the VA group (P = .002).

The mean wait time from referral to appointment was 28.6 days for the VA group and 42.3 days for the Choice group (P < .001), indicating that a Choice referral took longer to complete than a referral within the VA for HCV treatment. Thirty of the 71 (42%) veterans seen by a Choice provider accrued extraneous cost, with a mean additional cost of $8,561.40 per veteran. In the Choice group, 61 veterans completed a treatment regimen with the Choice HCP. Fifty-five veterans completed treatment and had available SVR12 data (6 were lost to follow up without SVR12 testing) and 50 (91%) had confirmed SVR12. The charts of the 5 treatment failures were reviewed to discern the cause for failure. Two cases involved early termination of therapy, 3 involved relapse and 2 failed to comply with medication instructions. There was 1 case of the Choice HCP not addressing simultaneous use of ledipasvir and a proton pump inhibitor, potentially causing an interaction, and 1 case where both the VA and Choice providers failed to recognize indicators of cirrhosis, which impacted the regimen used.

In the VALLHCS group, records of 320 veterans who completed treatment and had SVR12 testing were reviewed. While the Choice memorandum was active, veterans selected to be treated at VALLHCS had advanced liver fibrosis or cirrhosis, medical and mental health comorbidities that increased the risk of treatment complications or were considered to have difficulty adhering to the medication regimen. For this group, 296 (93%) had confirmed SVR12. Eighteen of the 24 (75%) treatment failures were complicated by nonadherence, including all 13 cases of early termination. One patient died from complications of decompensated cirrhosis before completing treatment, and 1 did not receive HCV medications during a hospital admission due to poor coordination of care between the VA inpatient and outpatient pharmacy services, leading to multiple missed doses.

 

The difference in SVR12 rates (ie, treatment failure rates), between the VA and Choice groups was not statistically significant (P = .61). None of the specific reasons for treatment failure had a statistically significant difference between groups. A treatment failure analysis is shown in Table 3, and Table 4 indicates the breakdown of treatment regimens.

 

Discussion

The Veterans Health Administration (VHA) is the largest integrated health care system in the US, consisting of 152 medical centers and > 1,700 sites of care. The VA has the potential to meet the health care needs of 21.6 million veterans. About 9 million veterans are enrolled in the VA system and 5.9 million received health care through VHA.¹⁷ However, every medical service cannot realistically be made available at every facility, and some veterans have difficulty gaining access to VHA care; distance and wait times have been well-publicized issues that need further exploration.^18,19 The Choice program is an attempt to meet gaps in VA coverage using non-VA HCPs.

HCV infection is a specific diagnosis with national treatment guidelines and well-studied treatments; it can be cured, with an evidence-based definition of cure. The VACO policy memorandum to refer less sick veterans to Choice while treating sicker veterans at the VA provided the opportunity to directly compare the quality of the 2 programs. The SVR12 rates of VALLHCS and Choice providers were comparable to the national average at the time, and while the difference in SVR12 rate was not significant, VALLHCS treated a significantly higher number of patients with cirrhosis because of the referral criteria.²⁰

The significant difference in medical comorbidities between the VA and Choice groups was not surprising, partly because of the referral criteria. Cirrhosis can impact the treatment regimen, especially in regard to use of ribavirin. Since the presence of mental health comorbidities did not affect selection into the Choice group, it makes sense that there was no significant difference in prevalence between the groups.

VACO allowed veterans with HCV treatment plans that VA HCPs felt were too complicated for the Choice program to be treated by VHA HCPs.⁹ VALLHCS exercised this right for veterans at risk for nonadherence, because in HCV treatment, nonadherence leads to treatment failure and development of drug resistant virus strains. Therefore, veterans who would have difficulty traveling to VALLHCS to pick up medications, those who lacked means of communication (such as those who were homeless), and those who had active substance abuse were treated at the VA, where closer monitoring and immediate access to a wide range of services was possible. Studies have confirmed the impact of these types of issues on HCV treatment adherence and success.²¹ This explains the higher prevalence of social issues in the VA group.

For an internal referral for HCV treatment at VALLHCS, the hepatology provider submits a consult request to the HCV treatment provider, who works in the same office, making direct communication simple. The main administrative limiting factor to minimizing wait times is the number of HCPs, which is dependent on hiring allowances.

When a veteran is referred to Choice, the VA provider places a consult for non-VA care, which the VA Office of Community Care processes by compiling relevant documents and sending the package to Triwest Healthcare Alliance, a private insurance processor contracted with the VA. Triwest selects the Choice provider, often without any input from the VA, and arranges the veteran’s initial appointment.²² Geographic distance to the veteran’s address is the main selection criteria for Triwest. Documents sent between the Choice and VA HCPs go through the Office of Community Care and Triwest. This significantly increases the potential for delays and failed communication. Triwest had a comprehensive list of providers deemed to be qualified to treat HCV within the geographic catchment of VALLHCS. This list was reviewed, and all veterans referred to Choice had HCPs near their home address; therefore, availability of Choice HCPs was not an issue.

The VA can provide guidance on management of the veteran in the form of bundle packages containing a list of services for which the Choice provider is authorized to provide, and ones the Choice provider is not authorized to provide. Some Choice HCPs ordered tests that were not authorized for HCV treatment such as esophagogastroduodenoscopy, colonoscopy, and liver biopsy. In all, 17 of 71 (24%) veterans seen by Choice HCPs had tests performed or ordered that VA HCPs would not have obtained for the purpose of HCV treatment (Table 5).

In order to prevent veterans from receiving unnecessary tests, a VALLHCS hepatologist asked to be notified by VA administrators overseeing Choice referrals whenever a secondary authorization request (SAR) was submitted by a Choice HCP. This strategy is not standard VA practice, therefore at many VA sites these requested tests would have been performed by the Choice HCP, which is why SARs were factored into cost analysis.

SVR12 test results that were drawn too early and had to be repeated at VALLHCS were a cost unique to the Choice program. Duplicate tests, particularly imaging studies and blood work, were extraneous costs. The largest extraneous costs were treatment regimens prescribed by Choice HCPs that did not follow standard of care and required VA provider intervention. Thirty of the 71 (42%) veterans seen by a Choice provider accrued a mean $8,561.40 in extra costs. As a result, the Choice program cost VHA $250,000 more to provide care for 30 veterans (enough to pay for a physician’s annual salary).

Some inappropriate treatment regimens were the result of Choice HCP error, such as 1 case in which a veteran was inadvertently switched from ledipasvir/sofosbuvir to ombitasvir/paritaprevir/ritonavir/dasabuvir after week 4. The veteran had to start therapy over but still achieved SVR12. Other cases saw veterans receive regimens for which they had clear contraindications, such as creatinine clearance < 30 mL/min/1.73m² for sofosbuvir or a positive resistance panel for specific medications. Eleven of 62 (18%) veterans who were started on HCV treatment by a Choice HCP received a regimen not consistent with VA guidelines—an alarming result.

Follow up for veterans referred to Choice was extremely labor intensive, and assessment of personnel requirements in a Choice-based VA system must take this into consideration. The Choice HCP has no obligation to communicate with the VA HCP. At the time of chart review, 57 of 71 (80%) Choice veterans had inadequate documentation to make a confident assessment of the treatment outcome. Multiple calls to the offices of the Choice HCP were needed to acquire records, and veterans had to be tracked down for additional tests. Veterans often would complete treatment and stop following up with the Choice provider before SVR12 confirmation. The VA hepatology provider reviewing Choice referrals served as clinician, case manager, and clerk in order to get veterans to an appropriate end point in their hepatitis C treatment, with mostly unmeasured hours of work.

 

Limitations

The study population size was limited by the number of veterans able to complete treatment through Choice. The parameters in the VACO policy memos automatically selected the VA and Choice groups but made them clinically distinct populations. New treatment medications were released during the study period, which impacted management strategy. Occasionally, VA and non-VA HCPs preferred different treatment regimens, leading to variation in the distribution of regimens used despite similar genotype distribution (Tables 2 and 4). In addition, a retrospective study is at risk for recall bias. A prospective study randomizing veterans to the Choice and VA groups is an important future endeavor. Comparing veteran satisfaction for Choice and VA services is also crucial.

Conclusions

This study demonstrates that the VA was able to provide more cost-effective and more timely care for HCV treatment to a relatively sicker population with no reduction in treatment success when compared with non-VA HCPs through the Choice program. While the Choice program can help veterans receive services they may otherwise not have access to and reduce travel time, the current system introduces inefficiencies that delay care and decrease cost-effectiveness. The Choice HCP selection process is based on proximity rather than quality, which may place the veteran at risk for receiving substandard care. Large-scale quality of care studies that compare efficiency measures, clinical outcomes, patient demographics, travel distance, cost efficacy and patient satisfaction for veterans receiving similar services at a VA facility and through Choice should be performed to ensure that veterans receive the best care available.