Huanguang Jia, PhD

Suicide is the 10th leading cause of death in the US. In 2017, there were 47,173 deaths by suicide (14 deaths per 100,000 people), representing a 33% increase from 1999.¹ In 2017 veterans accounted for 13.5% of all suicide deaths among US adults, although veterans comprised only 7.9% of the adult population; the age- and sex-adjusted suicide rate was 1.5 times higher for veterans than that of nonveteran adults.^2,3

Among veteran users of Veterans Health Administration (VHA) services, mental health and substance use disorders, chronic medical conditions, and chronic pain are associated with an increased risk for suicide.³ About one-half of VHA veterans have been diagnosed with chronic pain.⁴ A chronic pain diagnosis (eg, back pain, migraine, and psychogenic pain) increased the risk of death by suicide even after adjusting for comorbid psychiatric diagnoses, according to a study on pain and suicide among US veterans.⁵

One-quarter of veterans received an opioid prescription during VHA outpatient care in 2012.⁴ Increased prescribing of opioid medications has been associated with opioid overdose and suicides.^6-10 Opioids are the most common drugs found in suicide by overdose.¹¹ The rate of opioid-related suicide deaths is 13 times higher among individuals with opioid use disorder (OUD) than it is for those without OUD.¹² The rate of OUD diagnosis among VHA users was 7 times higher than that for non-VHA users.¹³

In the US the age-adjusted rate of drug overdose deaths increased from 6 per 100,000 persons in 1999 to 22 per 100,000 in 2017.¹⁴ Drug overdoses accounted for 52,404 US deaths in 2015; 33,091 (63.1%) were from opioids.¹⁵ In 2017, there were 70,237 drug overdose deaths; 67.8% involved opioids (ie, 5 per 100,000 population represent prescription opioids).¹⁶

The VHA is committed to reducing opioid use and veteran suicide prevention. In 2013 the VHA launched the Opioid Safety Initiative employing 4 strategies: education, pain management, risk management, and addiction treatment.¹⁷ To address the opioid epidemic, the North Florida/South Georgia Veteran Health System (NF/SGVHS) developed and implemented a multispecialty Opioid Risk Reduction Program that is fully integrated with mental health and addiction services. The purpose of the NF/SGVHS one-stop pain addiction clinic is to provide a treatment program for chronic pain and addiction. The program includes elements of a whole health approach to pain care, including battlefield and traditional acupuncture. The focus went beyond replacing pharmacologic treatments with a complementary integrative health approach to helping veterans regain control of their lives through empowerment, skill building, shared goal setting, and reinforcing self-management.

The self-management programs include a pain school for patient education, a pain psychology program, and a yoga program, all stressing self-management offered onsite and via telehealth. Special effort was directed to identify patients with OUD and opioid dependence. Many of these patients were transitioned to buprenorphine, a potent analgesic that suppresses opioid cravings and withdrawal symptoms associated with stopping opioids. The clinic was structured so that patients could be seen often for follow-up and support. In addition, open lines of communication and referral were set up between this clinic, the interventional pain clinic, and the physical medicine and rehabilitation service. A detailed description of this program has been published elsewhere.¹⁸

The number of veterans receiving opioid prescription across the VHA system decreased by 172,000 prescriptions quarterly between 2012 and 2016.¹⁹ Fewer veterans were prescribed high doses of opioids or concomitant interacting medicines and more veterans were receiving nonopioid therapies.¹⁹ The prescription reduction across the VHA has varied. For example, from 2012 to 2017 the NF/SGVHS reported an 87% reduction of opioid prescriptions (≥ 100 mg morphine equivalents/d), compared with the VHA national average reduction of 49%.¹⁸

Vigorous opioid reduction is controversial. In a systematic review on opioid reduction, Frank and colleagues reported some beneficial effects of opioid reduction, such as increased health-related quality of life.²⁰ However, another study suggested a risk of increased pain with opioid tapering.²¹ The literature findings on the association between prescription opioid use and suicide are mixed. The VHA Office of Mental Health and Suicide Prevention literature review reported that veterans were at increased risk of committing suicide within the first 6 months of discontinuing opioid therapy.²² Another study reported that veterans who discontinued long-term opioid treatment had an increased risk for suicidal ideation.²³ However, higher doses of opioids were associated with an increased risk for suicide among individuals with chronic pain.¹⁰ The link between opioid tapering and the risk of suicide or overdose is uncertain.

Bohnert and Ilgen suggested that discontinuing prescription opioids leads to suicide without examining the risk factors that influenced discontinuation is ill-informed.⁷ Strong evidence about the association or relationship among opioid use, overdose, and suicide is needed. To increase our understanding of that association, Bohnert and Ilgen argued for multifaceted interventions that simultaneously address the shared causes and risk factors for OUD,⁷ such as the multispecialty Opioid Risk Reduction Program at NF/SGVHS.

Because of the reported association between robust integrated mental health and addiction, primary care pain clinic intervention, and the higher rate of opioid tapering in NF/SGVHS,¹⁸ this study aims to describe the pattern of overdose diagnosis (opioid overdose and nonopioid overdose) and pattern of suicide rates among veterans enrolled in NF/SGVHS, Veterans Integrated Service Network (VISN) 8, and the entire VA health care system during 2012 to 2016.The study reviewed and compared overdose diagnosis and suicide rates among veterans across NF/SGVHS and 2 other levels of the VA health care system to determine whether there were variances in the pattern of overdose/suicide rates and to explore these differences.

Methods

In this retrospective study, aggregate data were obtained from several sources. First, the drug overdose data were extracted from the VA Support Service Center (VSSC) medical diagnosis cube. We reviewed the literature for opioid codes reported in the literature and compared these reported opioid International Classification of Diseases, Ninth Revision (ICD-9) and International Classification of Diseases, 10th Revision (ICD-10) codes with the local facility patient-level comprehensive overdose diagnosis codes. Based on the comparison, we found 98 ICD-9 and ICD-10 overdose diagnosis codes and ran the modified codes against the VSSC national database. Overdose data were aggregated by facility and fiscal year, and the overdose rates (per 1,000) were calculated for unique veteran users at the 3 levels (NF/SGVHS, VISN 8, and VA national) as the denominator.

Each of the 18 VISNs comprise multiple VAMCs and clinics within a geographic region. VISN 8 encompasses most of Florida and portions of southern Georgia and the Caribbean (Puerto Rico, US Virgin Islands), including NF/SGVHS.

In this study, drug overdose refers to the overdose or poisoning from all drugs (ie, opioids, cocaine, amphetamines, sedatives, etc) and defined as any unintentional (accidental), deliberate, or intent undetermined drug poisoning.²⁴ The suicide data for this study were drawn from the VA Suicide Prevention Program at 3 different levels: NF/SGVHS, VISN 8, and VHA national. Suicide is death caused by an intentional act of injuring oneself with the intent to die.²⁵

This descriptive study compared the rate of annual drug overdoses (per 1,000 enrollees) between NF/SGVHS, VISN 8, and VHA national from 2012 to 2016. It also compared the annual rate of suicide per 100,000 enrollees across these 3 levels of the VHA. The overdose and suicide rates and numbers are mutually exclusive, meaning the VISN 8 data do not include the NF/SGVHS information, and the national data excluded data from VISN 8 and NF/SGVHS. This approach helped improve the quality of multiple level comparisons for different levels of the VHA system.

Results

Figure 1 shows the pattern of overdose diagnosis by rates (per 1,000) across the study period (2012 to 2016) and compares patterns at 3 levels of VHA (NF/SGVHS, VISN 8, and VHA national). The average annual rate of overdose diagnoses for NF/SGVHS during the study was slightly higher (16.8 per 1,000) than that of VISN 8 (16 per 1,000) and VHA national (15.3 per 1,000), but by the end of the study period the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than the VISN 8 rate (20.4 per 1,000). Additionally, NF/SGVHS had less variability (SD, 1.34) in yearly average overdose rates compared with VISN 8 (SD, 2.96), and VHA national (SD, 1.69).

From 2013 to 2014 the overdose diagnosis rate for NF/SGVHS remained the same (17.1 per 1,000). A similar pattern was observed for the VHA national data, whereas the VISN 8 data showed a steady increase during the same period. In 2015, the NF/SGVHS had 0.7 per 1,000 decrease in overdose diagnosis rate, whereas VISN 8 and VHA national data showed 1.7 per 1,000 and 0.9 per 1,000 increases, respectively. During the last year of the study (2016), there was a dramatic increase in overdose diagnosis for all the health care systems, ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8.

Figure 2 shows the annual rates (per 100,000 individuals) of suicide for NF/SGVHS, VISN 8, and VHA national. The suicide pattern for VISN 8 shows a cyclical acceleration and deceleration trend across the study period. From 2012 to 2014, the VHA national data show a steady increase of about 1 per 100,000 from year to year. On the contrary, NF/SGVHS shows a low suicide rate from year to year within the same period with a rate of 10 per 100,000 in 2013 compared with the previous year. Although the NF/SGVHS suicide rate increased in 2016 (10.4 per 100,000), it remained lower than that of VISN 8 (10.7 per 100,00) and VHA national (38.2 per 100,000).

Discussion

This study described and compared the distribution pattern of overdose (nonopioid and opioid) and suicide rates at different levels of the VHA system. Although VHA implemented systemwide opioid tapering in 2013, little is known about the association between opioid tapering and overdose and suicide. We believe a retrospective examination regarding overdose and suicide among VHA users at 3 different levels of the system from 2012 to 2016 could contribute to the discussion regarding the potential risks and benefits of discontinuing opioids.

First, the average annual rate of overdose diagnosis for NF/SGVHS during the study period was slightly higher (16.8 per 1,000) compared with those of VISN 8 (16.0 per 1,000) and VHA national (15.3 per 1,000) with a general pattern of increase and minimum variations in the rates observed during the study period among the 3 levels of the system. These increased overdose patterns are consistent with other reports in the literature.¹⁴ By the end of the study period, the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than VISN 8 (20.4 per 1,000). During the last year of the study period (2016), there was a dramatic increase in overdose diagnosis for all health care systems ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8, which might be because of the VHA systemwide change of diagnosis code from ICD-9 to ICD-10, which includes more detailed diagnosis codes.

Second, our results showed that NF/SGVHS had the lowest average annual suicide rate (9.1 per 100,000) during the study period, which is one-fourth the VHA national rate and 2.6 per 100,000 lower than the VISN 8 rate. According to Bohnert and Ilgen,programs that improve the quality of pain care, expand access to psychotherapy, and increase access to medication-assisted treatment for OUDs could reduce suicide by drug overdose.⁷ We suggest that the low suicide rate at NF/SGVHS and the difference in the suicide rates between the NF/SGVHS and VISN 8 and VHA national data might be associated with the practice-based biopsychosocial interventions implemented at NF/SGVHS.

Our data showed a rise in the incidence of suicide at the NF/SGVHS in 2016. We are not aware of a local change in conditions, policy, and practice that would account for this increase. Suicide is variable, and data are likely to show spikes and valleys. Based on the available data, although the incidence of suicides at the NF/SGVHS in 2016 was higher, it remained below the VISN 8 and national VHA rate. This study seems to support the practice of tapering or stopping opioids within the context of a multidisciplinary approach that offers frequent follow-up, nonopioid options, and treatment of opioid addiction/dependence.

Limitations

The research findings of this study are limited by the retrospective and descriptive nature of its design. However, the findings might provide important information for understanding variations of overdose and suicide among VHA enrollees. Studies that use more robust methodologies are warranted to clinically investigate the impact of a multispecialty opioid risk reduction program targeting chronic pain and addiction management and identify best practices of opioid reduction and any unintended consequences that might arise from opioid tapering.²⁶ Further, we did not have access to the VA national overdose and suicide data after 2016. Similar to most retrospective data studies, ours might be limited by availability of national overdose and suicide data after 2016. It is important for future studies to cross-validate our study findings.

Conclusions

The NF/SGVHS developed and implemented a biopsychosocial model of pain treatment that includes multicomponent primary care integrated with mental health and addiction services as well as the interventional pain and physical medicine and rehabilitation services. The presence of this program, during a period when the facility was tapering opioids is likely to account for at least part of the relative reduction in suicide.

Suicide is the 10th leading cause of death in the US. In 2017, there were 47,173 deaths by suicide (14 deaths per 100,000 people), representing a 33% increase from 1999.¹ In 2017 veterans accounted for 13.5% of all suicide deaths among US adults, although veterans comprised only 7.9% of the adult population; the age- and sex-adjusted suicide rate was 1.5 times higher for veterans than that of nonveteran adults.^2,3

Among veteran users of Veterans Health Administration (VHA) services, mental health and substance use disorders, chronic medical conditions, and chronic pain are associated with an increased risk for suicide.³ About one-half of VHA veterans have been diagnosed with chronic pain.⁴ A chronic pain diagnosis (eg, back pain, migraine, and psychogenic pain) increased the risk of death by suicide even after adjusting for comorbid psychiatric diagnoses, according to a study on pain and suicide among US veterans.⁵

One-quarter of veterans received an opioid prescription during VHA outpatient care in 2012.⁴ Increased prescribing of opioid medications has been associated with opioid overdose and suicides.^6-10 Opioids are the most common drugs found in suicide by overdose.¹¹ The rate of opioid-related suicide deaths is 13 times higher among individuals with opioid use disorder (OUD) than it is for those without OUD.¹² The rate of OUD diagnosis among VHA users was 7 times higher than that for non-VHA users.¹³

In the US the age-adjusted rate of drug overdose deaths increased from 6 per 100,000 persons in 1999 to 22 per 100,000 in 2017.¹⁴ Drug overdoses accounted for 52,404 US deaths in 2015; 33,091 (63.1%) were from opioids.¹⁵ In 2017, there were 70,237 drug overdose deaths; 67.8% involved opioids (ie, 5 per 100,000 population represent prescription opioids).¹⁶

The VHA is committed to reducing opioid use and veteran suicide prevention. In 2013 the VHA launched the Opioid Safety Initiative employing 4 strategies: education, pain management, risk management, and addiction treatment.¹⁷ To address the opioid epidemic, the North Florida/South Georgia Veteran Health System (NF/SGVHS) developed and implemented a multispecialty Opioid Risk Reduction Program that is fully integrated with mental health and addiction services. The purpose of the NF/SGVHS one-stop pain addiction clinic is to provide a treatment program for chronic pain and addiction. The program includes elements of a whole health approach to pain care, including battlefield and traditional acupuncture. The focus went beyond replacing pharmacologic treatments with a complementary integrative health approach to helping veterans regain control of their lives through empowerment, skill building, shared goal setting, and reinforcing self-management.

The self-management programs include a pain school for patient education, a pain psychology program, and a yoga program, all stressing self-management offered onsite and via telehealth. Special effort was directed to identify patients with OUD and opioid dependence. Many of these patients were transitioned to buprenorphine, a potent analgesic that suppresses opioid cravings and withdrawal symptoms associated with stopping opioids. The clinic was structured so that patients could be seen often for follow-up and support. In addition, open lines of communication and referral were set up between this clinic, the interventional pain clinic, and the physical medicine and rehabilitation service. A detailed description of this program has been published elsewhere.¹⁸

The number of veterans receiving opioid prescription across the VHA system decreased by 172,000 prescriptions quarterly between 2012 and 2016.¹⁹ Fewer veterans were prescribed high doses of opioids or concomitant interacting medicines and more veterans were receiving nonopioid therapies.¹⁹ The prescription reduction across the VHA has varied. For example, from 2012 to 2017 the NF/SGVHS reported an 87% reduction of opioid prescriptions (≥ 100 mg morphine equivalents/d), compared with the VHA national average reduction of 49%.¹⁸

Vigorous opioid reduction is controversial. In a systematic review on opioid reduction, Frank and colleagues reported some beneficial effects of opioid reduction, such as increased health-related quality of life.²⁰ However, another study suggested a risk of increased pain with opioid tapering.²¹ The literature findings on the association between prescription opioid use and suicide are mixed. The VHA Office of Mental Health and Suicide Prevention literature review reported that veterans were at increased risk of committing suicide within the first 6 months of discontinuing opioid therapy.²² Another study reported that veterans who discontinued long-term opioid treatment had an increased risk for suicidal ideation.²³ However, higher doses of opioids were associated with an increased risk for suicide among individuals with chronic pain.¹⁰ The link between opioid tapering and the risk of suicide or overdose is uncertain.

Bohnert and Ilgen suggested that discontinuing prescription opioids leads to suicide without examining the risk factors that influenced discontinuation is ill-informed.⁷ Strong evidence about the association or relationship among opioid use, overdose, and suicide is needed. To increase our understanding of that association, Bohnert and Ilgen argued for multifaceted interventions that simultaneously address the shared causes and risk factors for OUD,⁷ such as the multispecialty Opioid Risk Reduction Program at NF/SGVHS.

Because of the reported association between robust integrated mental health and addiction, primary care pain clinic intervention, and the higher rate of opioid tapering in NF/SGVHS,¹⁸ this study aims to describe the pattern of overdose diagnosis (opioid overdose and nonopioid overdose) and pattern of suicide rates among veterans enrolled in NF/SGVHS, Veterans Integrated Service Network (VISN) 8, and the entire VA health care system during 2012 to 2016.The study reviewed and compared overdose diagnosis and suicide rates among veterans across NF/SGVHS and 2 other levels of the VA health care system to determine whether there were variances in the pattern of overdose/suicide rates and to explore these differences.

Methods

In this retrospective study, aggregate data were obtained from several sources. First, the drug overdose data were extracted from the VA Support Service Center (VSSC) medical diagnosis cube. We reviewed the literature for opioid codes reported in the literature and compared these reported opioid International Classification of Diseases, Ninth Revision (ICD-9) and International Classification of Diseases, 10th Revision (ICD-10) codes with the local facility patient-level comprehensive overdose diagnosis codes. Based on the comparison, we found 98 ICD-9 and ICD-10 overdose diagnosis codes and ran the modified codes against the VSSC national database. Overdose data were aggregated by facility and fiscal year, and the overdose rates (per 1,000) were calculated for unique veteran users at the 3 levels (NF/SGVHS, VISN 8, and VA national) as the denominator.

Each of the 18 VISNs comprise multiple VAMCs and clinics within a geographic region. VISN 8 encompasses most of Florida and portions of southern Georgia and the Caribbean (Puerto Rico, US Virgin Islands), including NF/SGVHS.

In this study, drug overdose refers to the overdose or poisoning from all drugs (ie, opioids, cocaine, amphetamines, sedatives, etc) and defined as any unintentional (accidental), deliberate, or intent undetermined drug poisoning.²⁴ The suicide data for this study were drawn from the VA Suicide Prevention Program at 3 different levels: NF/SGVHS, VISN 8, and VHA national. Suicide is death caused by an intentional act of injuring oneself with the intent to die.²⁵

This descriptive study compared the rate of annual drug overdoses (per 1,000 enrollees) between NF/SGVHS, VISN 8, and VHA national from 2012 to 2016. It also compared the annual rate of suicide per 100,000 enrollees across these 3 levels of the VHA. The overdose and suicide rates and numbers are mutually exclusive, meaning the VISN 8 data do not include the NF/SGVHS information, and the national data excluded data from VISN 8 and NF/SGVHS. This approach helped improve the quality of multiple level comparisons for different levels of the VHA system.

Results

Figure 1 shows the pattern of overdose diagnosis by rates (per 1,000) across the study period (2012 to 2016) and compares patterns at 3 levels of VHA (NF/SGVHS, VISN 8, and VHA national). The average annual rate of overdose diagnoses for NF/SGVHS during the study was slightly higher (16.8 per 1,000) than that of VISN 8 (16 per 1,000) and VHA national (15.3 per 1,000), but by the end of the study period the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than the VISN 8 rate (20.4 per 1,000). Additionally, NF/SGVHS had less variability (SD, 1.34) in yearly average overdose rates compared with VISN 8 (SD, 2.96), and VHA national (SD, 1.69).

From 2013 to 2014 the overdose diagnosis rate for NF/SGVHS remained the same (17.1 per 1,000). A similar pattern was observed for the VHA national data, whereas the VISN 8 data showed a steady increase during the same period. In 2015, the NF/SGVHS had 0.7 per 1,000 decrease in overdose diagnosis rate, whereas VISN 8 and VHA national data showed 1.7 per 1,000 and 0.9 per 1,000 increases, respectively. During the last year of the study (2016), there was a dramatic increase in overdose diagnosis for all the health care systems, ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8.

Figure 2 shows the annual rates (per 100,000 individuals) of suicide for NF/SGVHS, VISN 8, and VHA national. The suicide pattern for VISN 8 shows a cyclical acceleration and deceleration trend across the study period. From 2012 to 2014, the VHA national data show a steady increase of about 1 per 100,000 from year to year. On the contrary, NF/SGVHS shows a low suicide rate from year to year within the same period with a rate of 10 per 100,000 in 2013 compared with the previous year. Although the NF/SGVHS suicide rate increased in 2016 (10.4 per 100,000), it remained lower than that of VISN 8 (10.7 per 100,00) and VHA national (38.2 per 100,000).

Discussion

This study described and compared the distribution pattern of overdose (nonopioid and opioid) and suicide rates at different levels of the VHA system. Although VHA implemented systemwide opioid tapering in 2013, little is known about the association between opioid tapering and overdose and suicide. We believe a retrospective examination regarding overdose and suicide among VHA users at 3 different levels of the system from 2012 to 2016 could contribute to the discussion regarding the potential risks and benefits of discontinuing opioids.

First, the average annual rate of overdose diagnosis for NF/SGVHS during the study period was slightly higher (16.8 per 1,000) compared with those of VISN 8 (16.0 per 1,000) and VHA national (15.3 per 1,000) with a general pattern of increase and minimum variations in the rates observed during the study period among the 3 levels of the system. These increased overdose patterns are consistent with other reports in the literature.¹⁴ By the end of the study period, the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than VISN 8 (20.4 per 1,000). During the last year of the study period (2016), there was a dramatic increase in overdose diagnosis for all health care systems ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8, which might be because of the VHA systemwide change of diagnosis code from ICD-9 to ICD-10, which includes more detailed diagnosis codes.

Second, our results showed that NF/SGVHS had the lowest average annual suicide rate (9.1 per 100,000) during the study period, which is one-fourth the VHA national rate and 2.6 per 100,000 lower than the VISN 8 rate. According to Bohnert and Ilgen,programs that improve the quality of pain care, expand access to psychotherapy, and increase access to medication-assisted treatment for OUDs could reduce suicide by drug overdose.⁷ We suggest that the low suicide rate at NF/SGVHS and the difference in the suicide rates between the NF/SGVHS and VISN 8 and VHA national data might be associated with the practice-based biopsychosocial interventions implemented at NF/SGVHS.

Our data showed a rise in the incidence of suicide at the NF/SGVHS in 2016. We are not aware of a local change in conditions, policy, and practice that would account for this increase. Suicide is variable, and data are likely to show spikes and valleys. Based on the available data, although the incidence of suicides at the NF/SGVHS in 2016 was higher, it remained below the VISN 8 and national VHA rate. This study seems to support the practice of tapering or stopping opioids within the context of a multidisciplinary approach that offers frequent follow-up, nonopioid options, and treatment of opioid addiction/dependence.

Limitations

The research findings of this study are limited by the retrospective and descriptive nature of its design. However, the findings might provide important information for understanding variations of overdose and suicide among VHA enrollees. Studies that use more robust methodologies are warranted to clinically investigate the impact of a multispecialty opioid risk reduction program targeting chronic pain and addiction management and identify best practices of opioid reduction and any unintended consequences that might arise from opioid tapering.²⁶ Further, we did not have access to the VA national overdose and suicide data after 2016. Similar to most retrospective data studies, ours might be limited by availability of national overdose and suicide data after 2016. It is important for future studies to cross-validate our study findings.

Conclusions

The NF/SGVHS developed and implemented a biopsychosocial model of pain treatment that includes multicomponent primary care integrated with mental health and addiction services as well as the interventional pain and physical medicine and rehabilitation services. The presence of this program, during a period when the facility was tapering opioids is likely to account for at least part of the relative reduction in suicide.

Suicide is the 10th leading cause of death in the US. In 2017, there were 47,173 deaths by suicide (14 deaths per 100,000 people), representing a 33% increase from 1999.¹ In 2017 veterans accounted for 13.5% of all suicide deaths among US adults, although veterans comprised only 7.9% of the adult population; the age- and sex-adjusted suicide rate was 1.5 times higher for veterans than that of nonveteran adults.^2,3

Among veteran users of Veterans Health Administration (VHA) services, mental health and substance use disorders, chronic medical conditions, and chronic pain are associated with an increased risk for suicide.³ About one-half of VHA veterans have been diagnosed with chronic pain.⁴ A chronic pain diagnosis (eg, back pain, migraine, and psychogenic pain) increased the risk of death by suicide even after adjusting for comorbid psychiatric diagnoses, according to a study on pain and suicide among US veterans.⁵

One-quarter of veterans received an opioid prescription during VHA outpatient care in 2012.⁴ Increased prescribing of opioid medications has been associated with opioid overdose and suicides.^6-10 Opioids are the most common drugs found in suicide by overdose.¹¹ The rate of opioid-related suicide deaths is 13 times higher among individuals with opioid use disorder (OUD) than it is for those without OUD.¹² The rate of OUD diagnosis among VHA users was 7 times higher than that for non-VHA users.¹³

In the US the age-adjusted rate of drug overdose deaths increased from 6 per 100,000 persons in 1999 to 22 per 100,000 in 2017.¹⁴ Drug overdoses accounted for 52,404 US deaths in 2015; 33,091 (63.1%) were from opioids.¹⁵ In 2017, there were 70,237 drug overdose deaths; 67.8% involved opioids (ie, 5 per 100,000 population represent prescription opioids).¹⁶

The VHA is committed to reducing opioid use and veteran suicide prevention. In 2013 the VHA launched the Opioid Safety Initiative employing 4 strategies: education, pain management, risk management, and addiction treatment.¹⁷ To address the opioid epidemic, the North Florida/South Georgia Veteran Health System (NF/SGVHS) developed and implemented a multispecialty Opioid Risk Reduction Program that is fully integrated with mental health and addiction services. The purpose of the NF/SGVHS one-stop pain addiction clinic is to provide a treatment program for chronic pain and addiction. The program includes elements of a whole health approach to pain care, including battlefield and traditional acupuncture. The focus went beyond replacing pharmacologic treatments with a complementary integrative health approach to helping veterans regain control of their lives through empowerment, skill building, shared goal setting, and reinforcing self-management.

The self-management programs include a pain school for patient education, a pain psychology program, and a yoga program, all stressing self-management offered onsite and via telehealth. Special effort was directed to identify patients with OUD and opioid dependence. Many of these patients were transitioned to buprenorphine, a potent analgesic that suppresses opioid cravings and withdrawal symptoms associated with stopping opioids. The clinic was structured so that patients could be seen often for follow-up and support. In addition, open lines of communication and referral were set up between this clinic, the interventional pain clinic, and the physical medicine and rehabilitation service. A detailed description of this program has been published elsewhere.¹⁸

The number of veterans receiving opioid prescription across the VHA system decreased by 172,000 prescriptions quarterly between 2012 and 2016.¹⁹ Fewer veterans were prescribed high doses of opioids or concomitant interacting medicines and more veterans were receiving nonopioid therapies.¹⁹ The prescription reduction across the VHA has varied. For example, from 2012 to 2017 the NF/SGVHS reported an 87% reduction of opioid prescriptions (≥ 100 mg morphine equivalents/d), compared with the VHA national average reduction of 49%.¹⁸

Vigorous opioid reduction is controversial. In a systematic review on opioid reduction, Frank and colleagues reported some beneficial effects of opioid reduction, such as increased health-related quality of life.²⁰ However, another study suggested a risk of increased pain with opioid tapering.²¹ The literature findings on the association between prescription opioid use and suicide are mixed. The VHA Office of Mental Health and Suicide Prevention literature review reported that veterans were at increased risk of committing suicide within the first 6 months of discontinuing opioid therapy.²² Another study reported that veterans who discontinued long-term opioid treatment had an increased risk for suicidal ideation.²³ However, higher doses of opioids were associated with an increased risk for suicide among individuals with chronic pain.¹⁰ The link between opioid tapering and the risk of suicide or overdose is uncertain.

Bohnert and Ilgen suggested that discontinuing prescription opioids leads to suicide without examining the risk factors that influenced discontinuation is ill-informed.⁷ Strong evidence about the association or relationship among opioid use, overdose, and suicide is needed. To increase our understanding of that association, Bohnert and Ilgen argued for multifaceted interventions that simultaneously address the shared causes and risk factors for OUD,⁷ such as the multispecialty Opioid Risk Reduction Program at NF/SGVHS.

Because of the reported association between robust integrated mental health and addiction, primary care pain clinic intervention, and the higher rate of opioid tapering in NF/SGVHS,¹⁸ this study aims to describe the pattern of overdose diagnosis (opioid overdose and nonopioid overdose) and pattern of suicide rates among veterans enrolled in NF/SGVHS, Veterans Integrated Service Network (VISN) 8, and the entire VA health care system during 2012 to 2016.The study reviewed and compared overdose diagnosis and suicide rates among veterans across NF/SGVHS and 2 other levels of the VA health care system to determine whether there were variances in the pattern of overdose/suicide rates and to explore these differences.

Methods

In this retrospective study, aggregate data were obtained from several sources. First, the drug overdose data were extracted from the VA Support Service Center (VSSC) medical diagnosis cube. We reviewed the literature for opioid codes reported in the literature and compared these reported opioid International Classification of Diseases, Ninth Revision (ICD-9) and International Classification of Diseases, 10th Revision (ICD-10) codes with the local facility patient-level comprehensive overdose diagnosis codes. Based on the comparison, we found 98 ICD-9 and ICD-10 overdose diagnosis codes and ran the modified codes against the VSSC national database. Overdose data were aggregated by facility and fiscal year, and the overdose rates (per 1,000) were calculated for unique veteran users at the 3 levels (NF/SGVHS, VISN 8, and VA national) as the denominator.

Each of the 18 VISNs comprise multiple VAMCs and clinics within a geographic region. VISN 8 encompasses most of Florida and portions of southern Georgia and the Caribbean (Puerto Rico, US Virgin Islands), including NF/SGVHS.

In this study, drug overdose refers to the overdose or poisoning from all drugs (ie, opioids, cocaine, amphetamines, sedatives, etc) and defined as any unintentional (accidental), deliberate, or intent undetermined drug poisoning.²⁴ The suicide data for this study were drawn from the VA Suicide Prevention Program at 3 different levels: NF/SGVHS, VISN 8, and VHA national. Suicide is death caused by an intentional act of injuring oneself with the intent to die.²⁵

This descriptive study compared the rate of annual drug overdoses (per 1,000 enrollees) between NF/SGVHS, VISN 8, and VHA national from 2012 to 2016. It also compared the annual rate of suicide per 100,000 enrollees across these 3 levels of the VHA. The overdose and suicide rates and numbers are mutually exclusive, meaning the VISN 8 data do not include the NF/SGVHS information, and the national data excluded data from VISN 8 and NF/SGVHS. This approach helped improve the quality of multiple level comparisons for different levels of the VHA system.

Results

Figure 1 shows the pattern of overdose diagnosis by rates (per 1,000) across the study period (2012 to 2016) and compares patterns at 3 levels of VHA (NF/SGVHS, VISN 8, and VHA national). The average annual rate of overdose diagnoses for NF/SGVHS during the study was slightly higher (16.8 per 1,000) than that of VISN 8 (16 per 1,000) and VHA national (15.3 per 1,000), but by the end of the study period the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than the VISN 8 rate (20.4 per 1,000). Additionally, NF/SGVHS had less variability (SD, 1.34) in yearly average overdose rates compared with VISN 8 (SD, 2.96), and VHA national (SD, 1.69).

From 2013 to 2014 the overdose diagnosis rate for NF/SGVHS remained the same (17.1 per 1,000). A similar pattern was observed for the VHA national data, whereas the VISN 8 data showed a steady increase during the same period. In 2015, the NF/SGVHS had 0.7 per 1,000 decrease in overdose diagnosis rate, whereas VISN 8 and VHA national data showed 1.7 per 1,000 and 0.9 per 1,000 increases, respectively. During the last year of the study (2016), there was a dramatic increase in overdose diagnosis for all the health care systems, ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8.

Figure 2 shows the annual rates (per 100,000 individuals) of suicide for NF/SGVHS, VISN 8, and VHA national. The suicide pattern for VISN 8 shows a cyclical acceleration and deceleration trend across the study period. From 2012 to 2014, the VHA national data show a steady increase of about 1 per 100,000 from year to year. On the contrary, NF/SGVHS shows a low suicide rate from year to year within the same period with a rate of 10 per 100,000 in 2013 compared with the previous year. Although the NF/SGVHS suicide rate increased in 2016 (10.4 per 100,000), it remained lower than that of VISN 8 (10.7 per 100,00) and VHA national (38.2 per 100,000).

Discussion

This study described and compared the distribution pattern of overdose (nonopioid and opioid) and suicide rates at different levels of the VHA system. Although VHA implemented systemwide opioid tapering in 2013, little is known about the association between opioid tapering and overdose and suicide. We believe a retrospective examination regarding overdose and suicide among VHA users at 3 different levels of the system from 2012 to 2016 could contribute to the discussion regarding the potential risks and benefits of discontinuing opioids.

First, the average annual rate of overdose diagnosis for NF/SGVHS during the study period was slightly higher (16.8 per 1,000) compared with those of VISN 8 (16.0 per 1,000) and VHA national (15.3 per 1,000) with a general pattern of increase and minimum variations in the rates observed during the study period among the 3 levels of the system. These increased overdose patterns are consistent with other reports in the literature.¹⁴ By the end of the study period, the NF/SGVHS rate (18.6 per 1,000) nearly matched the national rate (18.2 per 1,000) and was lower than VISN 8 (20.4 per 1,000). During the last year of the study period (2016), there was a dramatic increase in overdose diagnosis for all health care systems ranging from 2.2 per 1,000 for NF/SGVHS to 3.3 per 1,000 for VISN 8, which might be because of the VHA systemwide change of diagnosis code from ICD-9 to ICD-10, which includes more detailed diagnosis codes.

Second, our results showed that NF/SGVHS had the lowest average annual suicide rate (9.1 per 100,000) during the study period, which is one-fourth the VHA national rate and 2.6 per 100,000 lower than the VISN 8 rate. According to Bohnert and Ilgen,programs that improve the quality of pain care, expand access to psychotherapy, and increase access to medication-assisted treatment for OUDs could reduce suicide by drug overdose.⁷ We suggest that the low suicide rate at NF/SGVHS and the difference in the suicide rates between the NF/SGVHS and VISN 8 and VHA national data might be associated with the practice-based biopsychosocial interventions implemented at NF/SGVHS.

Our data showed a rise in the incidence of suicide at the NF/SGVHS in 2016. We are not aware of a local change in conditions, policy, and practice that would account for this increase. Suicide is variable, and data are likely to show spikes and valleys. Based on the available data, although the incidence of suicides at the NF/SGVHS in 2016 was higher, it remained below the VISN 8 and national VHA rate. This study seems to support the practice of tapering or stopping opioids within the context of a multidisciplinary approach that offers frequent follow-up, nonopioid options, and treatment of opioid addiction/dependence.

Limitations

The research findings of this study are limited by the retrospective and descriptive nature of its design. However, the findings might provide important information for understanding variations of overdose and suicide among VHA enrollees. Studies that use more robust methodologies are warranted to clinically investigate the impact of a multispecialty opioid risk reduction program targeting chronic pain and addiction management and identify best practices of opioid reduction and any unintended consequences that might arise from opioid tapering.²⁶ Further, we did not have access to the VA national overdose and suicide data after 2016. Similar to most retrospective data studies, ours might be limited by availability of national overdose and suicide data after 2016. It is important for future studies to cross-validate our study findings.

Conclusions

The NF/SGVHS developed and implemented a biopsychosocial model of pain treatment that includes multicomponent primary care integrated with mental health and addiction services as well as the interventional pain and physical medicine and rehabilitation services. The presence of this program, during a period when the facility was tapering opioids is likely to account for at least part of the relative reduction in suicide.

While private or other public health care organizations can refuse to care for patients who have displayed disruptive behavior (DB), the VA Response to Disruptive Behavior of Patients law (38 CFR §17.107) prohibits the Veterans Health Administration (VHA) of the Department of Veterans Affairs (VA) from refusing care to veterans who display DB.¹ The VHA defines DB as any behavior that is intimidating, threatening, or dangerous or that has, or could, jeopardize the health or safety of patients, VHA staff, or others.²

VA Response to DB Law

The VA Response to Disruptive Behavior of Patients requires the VHA to provide alternative care options that minimize risk while ensuring services; for example, providing care at a different location and/or time when additional staff are available to assist and monitor the patient. This can provide a unique opportunity to capture data on DB and the results of alternative forms of caring for this population. DB may represent a symptom of a health problem. Further, patients who are refused care because of DB may pose a threat to the community if their medical conditions are not treated or managed properly.

The reason public health care organizations refuse care to persons who display DB is clear: DBs hinder business operations, are financially taxing, and put health care workers at risk.^3-10 “In 2009, the VHA spent close to $5.5 million on workers’ compensation and medical expenditures for 425 incidents–or about $130,000 per DB incident (Hodgson M, Drummond D, Van Male L. Unpublished data, 2010).” In another study, 106 of 762 nurses in 1 hospital system reported an assault by a patient, and 30 required medical attention, which resulted in a total cost of $94,156.⁸ From 2002 to 2013, incidents of serious workplace violence requiring days off for an injured worker to recover on average were 4 times more common in health care than in other industries.^6-11 Incidents of patient violence and aggression toward staff transcend specialization; however, hospital nurses and staff from the emergency, rehabilitation and gerontology departments, psychiatric unit, and home-based services are more susceptible and vulnerable to DB incidents than are other types of employees.^8,10-19

Data reported by health care staff suggest that patients rather than staff members or visitors initiate > 70% of serious physical attacks against health care workers.^9,13,20-23 A 2015 study of VHA health care providers (HCPs) found that > 60% had experienced some form of DB, verbal abuse being the most prevalent, followed by sexual abuse and physical abuse.²⁰ Of 72,000 VHA staff responding to a nationwide survey, 13% experienced, on average, ≥ 1 assault by a veteran (eg, something was thrown at them; they were pushed, kicked, slapped; or were threatened or injured by a weapon).^8,21Although 13% may seem small, the incidents may have lasting financial and emotional distress. Risk factors associated with DB include medication nonadherence, history of drug and alcohol use, disappointment with care, history of violence, and untreated mental health concerns.^19,24,25 Also, unmarried and young patients are more likely to display violence against health care workers.²⁶

To meet its legal obligations and deliver empathetic care, the VHA documents and analyzes data on all patients who exhibit DB. A local DB Committee (DBC) reviews the data, whether it occurs in an inpatient or outpatient setting, such as community-based outpatient clinics. Once a DB incident is reported, the DBC begins an evidence-based risk evaluation, including the option of contacting the persons who displayed or experienced the DB. Goals are to (1) prevent future DB incidents; (2) detect vulnerabilities in the environment; and (3) collaborate with HCPs and patients to provide optimal care while improving the patient/provider interactions.

Effects of Disruptive Behavior

DB has negative consequences for both patients and health care workers and results in poor evaluations of care from both groups.^27-32 Aside from interfering with safe medical care, DB also impacts care for other patients by delaying access to care and increasing appointment wait times due to employee absenteeism and staff shortages.^3,4,20,32,33 For HCPs, patient violence is associated with unwillingness to provide care, briefer treatment periods, and decreases in occupational satisfaction, performance, and commitment.^10,28,31 Coping with DB can compromise the HCP’s ability to stay focused and engaged in providing health care, increasing errors.^9,15,31

Harmful health effects experienced by HCPs who have been victims of DB include fear, mood disorders, anxiety, all symptoms of psychological distress and posttraumatic stress disorder (PTSD).^{10,22,30,34-36} In a study of the impact on productivity of PTSD triggered by job-related DB, PTSD symptoms were associated with withdrawal from or minimizing encounters with patients, job turnover, and troubles with thinking.^35,36 Nurses with PTSD symptoms who stayed on the job had difficulty staying cognitively focused and managing “higher level work demands that required attention to detail or communication skills.”³⁶ Due to the detrimental impact of DB, it is reasonable to expect a decrease in the quality of care rendered to patients by impacted employees. The quality of care for all patients of HCPs who have experienced a DB is poorer than that of patients of HCPs who have not experienced a DB.²⁹

Reporting Disruptive Behavior

The literature suggests that consistent and effective DB reporting is pivotal to improving the outcome and quality of care for those displaying DB.^37-39 To provide high-quality health services to veterans who display DB, the VHA must promote the management and reporting of DB. Without knowledge of the full spectrum of DB events at VHA facilities, efforts to prevent or manage DB and ensure safety may have limited impact.^7,37 Reports can be used for clinical decision making to optimize staff training in delivery of quality care while assuring staff safety. More than 80% of DB incidents occur during interactions with patients, thus this is a clinical issue that can affect the outcome of patient care.^8,21

Documented DB reports are used to analyze the degree, frequency, and nature of incidents, which might reveal risk factors and develop preventive efforts and training for specific hazards.^8,39 Some have argued that implementing a standardized DB reporting system is a crucial first step toward minimizing hazards and improving health care.^38,40,41

When DB incidents were recorded through a hospital electronic reporting system and discussed in meetings, staff reported: (1) increased awareness of DB; (2) improved ability to manage DB incidents; and (3) amplified reporting of incidents.^38,41,42 These findings support similar results from studies of an intervention implemented at VA Community Living Centers (CLCs) from 2013 to 2017: Staff Training in Assisted Living Residences (STAR-VA).^4,12,19 The aim of STAR-VA was to minimize challenging dementia-related DB in CLCs. The intervention initially was established to train direct-care, assisted-living staff to provide better care to older patients displaying DB. Data revealed that documentation of DBs was, the first step to ensuring staff and patient safety.^18,40

VHA Reporting System

In 2013, the VA Office of Inspector General (OIG) found no standardized documentation of DB events across the VA health care system.⁴² Instead, DB events were documented in multiple records in various locations, including administrative and progress notes in the electronic health record (EHR), police reports, e-mails, or letters submitted to DBC chairs.⁴² This situation reduced administrators’ ability to consider all relevant information and render appropriate decisions in DB cases.⁴² In 2015, based on OIG recommendations, the VHA implemented the Disruptive Behavior Reporting System (DBRS) nationwide, which allowed all VHA staff to report DB events. The DBRS was designed to address factors likely to impede reporting and management of DB, namely, complexity of and lack of access to a central reporting system.^43,44 The DBRS is currently the primary VHA tool to document DB events.

The DBRS consists of 32 questions in 5 sections relating to the (1) location and time of DB event; (2) reporter; (3) disrupter; (4) DB event details; and (5) the person who experienced (experiencer) the event. The system also provides a list of the types of DB, such as inappropriate communication, bullying and/or intimidation, verbal or written threat of physical harm, physical violence, sexual harassment, sexual assault, and property damage. The DBRS has the potential to provide useful data on DB and DB reporting, such as the typical staff entering data and the number and/or types of DB occurring.

The DBRS complements the preexisting VHA policies and committees for care of veterans who display DB.^{1-3,14,21,24,25} The VHA Workplace Violence Prevention Program (WVPP) required facilities to submit data on DB events through a Workplace Behavioral Risk report. Data for the report were obtained from police reports, patient safety reports, DBC records, and notes in the EHR. Following implementations of DBRS, the number of DB events per year became a part of facility performance standards.

VHA is creating novel approaches to handling DB that allow health care workers to render care in a safe and effective manner guided by documented information. For example, DBCs can recommend the use of Category I Patient Record Flags (PRFs) following documented DB, which informs staff of the potential risk of DB and provides guidance on protective methods to use when meeting with the patient.^2,21,24 A survey of 140 VA hospital chiefs of staff indicated that DBC procedures were related to a decrease in the rates of assaults.¹ Additionally, VA provides training for staff in techniques to promote personal safety, such as identifying signs that precede DB, using verbal deescalation, and practicing therapeutic containment.

Resistance to Reporting

Many health care employees and employers are reticent to report DBs.^{22,31,43,45-48} Studies suggest health care organizations can cultivate a culture that is resistant to reporting DB.^49,50 This complicates the ability of the health care system to design and maintain safety protocols and safer treatment plans.^3,41,51 Worldwide, < 30% of DBs are reported.⁴⁷ One barrier may be that supervisors may not wish to acknowledge DBs on their units or may not provide sufficient staff time for training or reporting.^31,46,47 HCPs may worry that a DB report will stigmatize patients, especially those who are elderly or have cognitive impairment, brain injury, psychological illness, or developmental disability. Patients with cognitive conditions are reportedly 20% more likely to be violent toward caregivers and providers.³¹ A dementia diagnosis, for example, is associated with a high likelihood for DB.^30,52 More than 80% of DB events displayed by patients with dementia may go unreported.^26,31,50,52

Some clinicians may attribute DB to physiologic conditions that need to be treated, not reported. However, employers can face various legal liabilities if steps are not taken to protect employees.^47,51 Federal and state statutes require that organizations provide a healthy and safe employment environment for workers. This requires that employers institute reasonable protective measures, such as procedures to intervene, policies on addressing DB incidents, and/or training to minimize or deescalate DB.^51,53 Also, employees may sue employers if security measures are inadequate or deficient in properly investigating current and past evidence of DB or identifying vulnerabilities in the workplace. Unwillingness to investigate DB and safety-related workplace concerns have contributed to increased workplace violence and legal liability.^52,53 The mission of caring and trust is consistent with assuring a safe environment.

Training and Empathetic Care

To combat cultural resistance to reporting DBs, more and perhaps different contextual approaches to education and training may be needed that address ethical dilemmas and concerns of providers. The success of training relies on administrators supporting staff in reporting DB. Training must address providers’ conflicting beliefs and assist with identifying strategies to provide the best possible care for patients who display DB.^1,38 HCPs are less likely to document a DB if they feel that administrators are creating documentation that will have negative consequences for a patient. Thus, leadership is responsible for ensuring that misconceptions are dispelled through training and other efforts and information on how reported DB data will be used is communicated through strategic channels.

Education and training must consider empathic care that attempts to understand why patients behave as they do through the information gathered.⁵⁵ Empathy in health care is multifaceted: It involves comprehending a patient’s viewpoint, circumstances, and feelings and the capacity to analyze whether one is comprehending these accurately in order to demonstrate supportive care.^54,55

Improving patient and staff interaction once a problematic behavior is identified is the aim of empathic care. Increasing empathic care can improve compassionate, patient-centered interactions that begin once the patient seeks care. This approach has proven to decrease DB by patients with dementia and improve their care, lessen staff problems during interactions, and increase staff morale.²⁰ Experts call for the adoption of an interpersonal approach to patient encounters, and there is evidence that creating organizational change by moving toward compassionate care can lead to a positive impact for patients.^54,55

Future Studies

There are growth opportunities in utilization of the DBRS. Analysis of the DBRS database by the VA Central Office (VACO) showed that the system is underutilized by facilities across the VA system.⁵⁶ In response to this current underutilization, VACO is taking steps to close these gaps through increasing training to staff and promotion of the use of the DBRS. A 2015 pilot study of VHA providers showed that > 70% of providers had experienced a DB as defined by VHA, but only 34% of them reported their most recently experienced DB within the past 12 months.²⁰ Thus, DBRS use must be studied within the context that patient-perpetrated DB is underreported in health care organizations.^{5,9,29,41,43,57,58} Studies addressing national DBRS utilization patterns and the cost associated with implementing the DBRS also are needed. One study suggests that there is an association between measures of facility complexity and staff perceptions of safety, which should be considered in analyzing DBRS usage.⁵⁷ Studies addressing the role of the DBRS and misconceptions that the tool may represent a punitive tool also are needed. VHA should consider how the attribution “disruptive behavior” assigns a negative connotation and leads HCPs to avoid using the DBRS. Additionally, DB reporting may increase when HCPs understand that DB reporting is part of the comprehensive, consultative strategy to provide the best care to patients.

Conclusion

Accurate reporting of DB events enables the development of strategies for multidisciplinary teams to work together to minimize hazards and to provide interventions that provide for the safe delivery of health care to all patients. Improving reporting ensures there is an accurate representation of how disruptive events impact care provided within a facility—and what types of variables may be associated with increased risk for these types of events.

Additionally, ensuring that reporting is maximized also provides the VHA with opportunities for DBCs to offer evidence-based risk assessment of violence and consultation to staff members who may benefit from improved competencies in working with patients who display DB. These potential improvements are consistent with the VHA I CARE values and will provide data that can inform recommendations for health care in other agencies/health care organizations.

Acknowledgments
This work was supported by the Center of Innovation on Disability and Rehabilitation Research (CINDRR) of the Health Services Research and Development Service, Office of Research and Development, Department of Veterans Affairs.

While private or other public health care organizations can refuse to care for patients who have displayed disruptive behavior (DB), the VA Response to Disruptive Behavior of Patients law (38 CFR §17.107) prohibits the Veterans Health Administration (VHA) of the Department of Veterans Affairs (VA) from refusing care to veterans who display DB.¹ The VHA defines DB as any behavior that is intimidating, threatening, or dangerous or that has, or could, jeopardize the health or safety of patients, VHA staff, or others.²

VA Response to DB Law

The VA Response to Disruptive Behavior of Patients requires the VHA to provide alternative care options that minimize risk while ensuring services; for example, providing care at a different location and/or time when additional staff are available to assist and monitor the patient. This can provide a unique opportunity to capture data on DB and the results of alternative forms of caring for this population. DB may represent a symptom of a health problem. Further, patients who are refused care because of DB may pose a threat to the community if their medical conditions are not treated or managed properly.

The reason public health care organizations refuse care to persons who display DB is clear: DBs hinder business operations, are financially taxing, and put health care workers at risk.^3-10 “In 2009, the VHA spent close to $5.5 million on workers’ compensation and medical expenditures for 425 incidents–or about $130,000 per DB incident (Hodgson M, Drummond D, Van Male L. Unpublished data, 2010).” In another study, 106 of 762 nurses in 1 hospital system reported an assault by a patient, and 30 required medical attention, which resulted in a total cost of $94,156.⁸ From 2002 to 2013, incidents of serious workplace violence requiring days off for an injured worker to recover on average were 4 times more common in health care than in other industries.^6-11 Incidents of patient violence and aggression toward staff transcend specialization; however, hospital nurses and staff from the emergency, rehabilitation and gerontology departments, psychiatric unit, and home-based services are more susceptible and vulnerable to DB incidents than are other types of employees.^8,10-19

Data reported by health care staff suggest that patients rather than staff members or visitors initiate > 70% of serious physical attacks against health care workers.^9,13,20-23 A 2015 study of VHA health care providers (HCPs) found that > 60% had experienced some form of DB, verbal abuse being the most prevalent, followed by sexual abuse and physical abuse.²⁰ Of 72,000 VHA staff responding to a nationwide survey, 13% experienced, on average, ≥ 1 assault by a veteran (eg, something was thrown at them; they were pushed, kicked, slapped; or were threatened or injured by a weapon).^8,21Although 13% may seem small, the incidents may have lasting financial and emotional distress. Risk factors associated with DB include medication nonadherence, history of drug and alcohol use, disappointment with care, history of violence, and untreated mental health concerns.^19,24,25 Also, unmarried and young patients are more likely to display violence against health care workers.²⁶

To meet its legal obligations and deliver empathetic care, the VHA documents and analyzes data on all patients who exhibit DB. A local DB Committee (DBC) reviews the data, whether it occurs in an inpatient or outpatient setting, such as community-based outpatient clinics. Once a DB incident is reported, the DBC begins an evidence-based risk evaluation, including the option of contacting the persons who displayed or experienced the DB. Goals are to (1) prevent future DB incidents; (2) detect vulnerabilities in the environment; and (3) collaborate with HCPs and patients to provide optimal care while improving the patient/provider interactions.

Effects of Disruptive Behavior

DB has negative consequences for both patients and health care workers and results in poor evaluations of care from both groups.^27-32 Aside from interfering with safe medical care, DB also impacts care for other patients by delaying access to care and increasing appointment wait times due to employee absenteeism and staff shortages.^3,4,20,32,33 For HCPs, patient violence is associated with unwillingness to provide care, briefer treatment periods, and decreases in occupational satisfaction, performance, and commitment.^10,28,31 Coping with DB can compromise the HCP’s ability to stay focused and engaged in providing health care, increasing errors.^9,15,31

Harmful health effects experienced by HCPs who have been victims of DB include fear, mood disorders, anxiety, all symptoms of psychological distress and posttraumatic stress disorder (PTSD).^{10,22,30,34-36} In a study of the impact on productivity of PTSD triggered by job-related DB, PTSD symptoms were associated with withdrawal from or minimizing encounters with patients, job turnover, and troubles with thinking.^35,36 Nurses with PTSD symptoms who stayed on the job had difficulty staying cognitively focused and managing “higher level work demands that required attention to detail or communication skills.”³⁶ Due to the detrimental impact of DB, it is reasonable to expect a decrease in the quality of care rendered to patients by impacted employees. The quality of care for all patients of HCPs who have experienced a DB is poorer than that of patients of HCPs who have not experienced a DB.²⁹

Reporting Disruptive Behavior

The literature suggests that consistent and effective DB reporting is pivotal to improving the outcome and quality of care for those displaying DB.^37-39 To provide high-quality health services to veterans who display DB, the VHA must promote the management and reporting of DB. Without knowledge of the full spectrum of DB events at VHA facilities, efforts to prevent or manage DB and ensure safety may have limited impact.^7,37 Reports can be used for clinical decision making to optimize staff training in delivery of quality care while assuring staff safety. More than 80% of DB incidents occur during interactions with patients, thus this is a clinical issue that can affect the outcome of patient care.^8,21

Documented DB reports are used to analyze the degree, frequency, and nature of incidents, which might reveal risk factors and develop preventive efforts and training for specific hazards.^8,39 Some have argued that implementing a standardized DB reporting system is a crucial first step toward minimizing hazards and improving health care.^38,40,41

When DB incidents were recorded through a hospital electronic reporting system and discussed in meetings, staff reported: (1) increased awareness of DB; (2) improved ability to manage DB incidents; and (3) amplified reporting of incidents.^38,41,42 These findings support similar results from studies of an intervention implemented at VA Community Living Centers (CLCs) from 2013 to 2017: Staff Training in Assisted Living Residences (STAR-VA).^4,12,19 The aim of STAR-VA was to minimize challenging dementia-related DB in CLCs. The intervention initially was established to train direct-care, assisted-living staff to provide better care to older patients displaying DB. Data revealed that documentation of DBs was, the first step to ensuring staff and patient safety.^18,40

VHA Reporting System

In 2013, the VA Office of Inspector General (OIG) found no standardized documentation of DB events across the VA health care system.⁴² Instead, DB events were documented in multiple records in various locations, including administrative and progress notes in the electronic health record (EHR), police reports, e-mails, or letters submitted to DBC chairs.⁴² This situation reduced administrators’ ability to consider all relevant information and render appropriate decisions in DB cases.⁴² In 2015, based on OIG recommendations, the VHA implemented the Disruptive Behavior Reporting System (DBRS) nationwide, which allowed all VHA staff to report DB events. The DBRS was designed to address factors likely to impede reporting and management of DB, namely, complexity of and lack of access to a central reporting system.^43,44 The DBRS is currently the primary VHA tool to document DB events.

The DBRS consists of 32 questions in 5 sections relating to the (1) location and time of DB event; (2) reporter; (3) disrupter; (4) DB event details; and (5) the person who experienced (experiencer) the event. The system also provides a list of the types of DB, such as inappropriate communication, bullying and/or intimidation, verbal or written threat of physical harm, physical violence, sexual harassment, sexual assault, and property damage. The DBRS has the potential to provide useful data on DB and DB reporting, such as the typical staff entering data and the number and/or types of DB occurring.

The DBRS complements the preexisting VHA policies and committees for care of veterans who display DB.^{1-3,14,21,24,25} The VHA Workplace Violence Prevention Program (WVPP) required facilities to submit data on DB events through a Workplace Behavioral Risk report. Data for the report were obtained from police reports, patient safety reports, DBC records, and notes in the EHR. Following implementations of DBRS, the number of DB events per year became a part of facility performance standards.

VHA is creating novel approaches to handling DB that allow health care workers to render care in a safe and effective manner guided by documented information. For example, DBCs can recommend the use of Category I Patient Record Flags (PRFs) following documented DB, which informs staff of the potential risk of DB and provides guidance on protective methods to use when meeting with the patient.^2,21,24 A survey of 140 VA hospital chiefs of staff indicated that DBC procedures were related to a decrease in the rates of assaults.¹ Additionally, VA provides training for staff in techniques to promote personal safety, such as identifying signs that precede DB, using verbal deescalation, and practicing therapeutic containment.

Resistance to Reporting

Many health care employees and employers are reticent to report DBs.^{22,31,43,45-48} Studies suggest health care organizations can cultivate a culture that is resistant to reporting DB.^49,50 This complicates the ability of the health care system to design and maintain safety protocols and safer treatment plans.^3,41,51 Worldwide, < 30% of DBs are reported.⁴⁷ One barrier may be that supervisors may not wish to acknowledge DBs on their units or may not provide sufficient staff time for training or reporting.^31,46,47 HCPs may worry that a DB report will stigmatize patients, especially those who are elderly or have cognitive impairment, brain injury, psychological illness, or developmental disability. Patients with cognitive conditions are reportedly 20% more likely to be violent toward caregivers and providers.³¹ A dementia diagnosis, for example, is associated with a high likelihood for DB.^30,52 More than 80% of DB events displayed by patients with dementia may go unreported.^26,31,50,52

Some clinicians may attribute DB to physiologic conditions that need to be treated, not reported. However, employers can face various legal liabilities if steps are not taken to protect employees.^47,51 Federal and state statutes require that organizations provide a healthy and safe employment environment for workers. This requires that employers institute reasonable protective measures, such as procedures to intervene, policies on addressing DB incidents, and/or training to minimize or deescalate DB.^51,53 Also, employees may sue employers if security measures are inadequate or deficient in properly investigating current and past evidence of DB or identifying vulnerabilities in the workplace. Unwillingness to investigate DB and safety-related workplace concerns have contributed to increased workplace violence and legal liability.^52,53 The mission of caring and trust is consistent with assuring a safe environment.

Training and Empathetic Care

To combat cultural resistance to reporting DBs, more and perhaps different contextual approaches to education and training may be needed that address ethical dilemmas and concerns of providers. The success of training relies on administrators supporting staff in reporting DB. Training must address providers’ conflicting beliefs and assist with identifying strategies to provide the best possible care for patients who display DB.^1,38 HCPs are less likely to document a DB if they feel that administrators are creating documentation that will have negative consequences for a patient. Thus, leadership is responsible for ensuring that misconceptions are dispelled through training and other efforts and information on how reported DB data will be used is communicated through strategic channels.

Education and training must consider empathic care that attempts to understand why patients behave as they do through the information gathered.⁵⁵ Empathy in health care is multifaceted: It involves comprehending a patient’s viewpoint, circumstances, and feelings and the capacity to analyze whether one is comprehending these accurately in order to demonstrate supportive care.^54,55

Improving patient and staff interaction once a problematic behavior is identified is the aim of empathic care. Increasing empathic care can improve compassionate, patient-centered interactions that begin once the patient seeks care. This approach has proven to decrease DB by patients with dementia and improve their care, lessen staff problems during interactions, and increase staff morale.²⁰ Experts call for the adoption of an interpersonal approach to patient encounters, and there is evidence that creating organizational change by moving toward compassionate care can lead to a positive impact for patients.^54,55

Future Studies

There are growth opportunities in utilization of the DBRS. Analysis of the DBRS database by the VA Central Office (VACO) showed that the system is underutilized by facilities across the VA system.⁵⁶ In response to this current underutilization, VACO is taking steps to close these gaps through increasing training to staff and promotion of the use of the DBRS. A 2015 pilot study of VHA providers showed that > 70% of providers had experienced a DB as defined by VHA, but only 34% of them reported their most recently experienced DB within the past 12 months.²⁰ Thus, DBRS use must be studied within the context that patient-perpetrated DB is underreported in health care organizations.^{5,9,29,41,43,57,58} Studies addressing national DBRS utilization patterns and the cost associated with implementing the DBRS also are needed. One study suggests that there is an association between measures of facility complexity and staff perceptions of safety, which should be considered in analyzing DBRS usage.⁵⁷ Studies addressing the role of the DBRS and misconceptions that the tool may represent a punitive tool also are needed. VHA should consider how the attribution “disruptive behavior” assigns a negative connotation and leads HCPs to avoid using the DBRS. Additionally, DB reporting may increase when HCPs understand that DB reporting is part of the comprehensive, consultative strategy to provide the best care to patients.

Conclusion

Accurate reporting of DB events enables the development of strategies for multidisciplinary teams to work together to minimize hazards and to provide interventions that provide for the safe delivery of health care to all patients. Improving reporting ensures there is an accurate representation of how disruptive events impact care provided within a facility—and what types of variables may be associated with increased risk for these types of events.

Additionally, ensuring that reporting is maximized also provides the VHA with opportunities for DBCs to offer evidence-based risk assessment of violence and consultation to staff members who may benefit from improved competencies in working with patients who display DB. These potential improvements are consistent with the VHA I CARE values and will provide data that can inform recommendations for health care in other agencies/health care organizations.

Acknowledgments
This work was supported by the Center of Innovation on Disability and Rehabilitation Research (CINDRR) of the Health Services Research and Development Service, Office of Research and Development, Department of Veterans Affairs.

While private or other public health care organizations can refuse to care for patients who have displayed disruptive behavior (DB), the VA Response to Disruptive Behavior of Patients law (38 CFR §17.107) prohibits the Veterans Health Administration (VHA) of the Department of Veterans Affairs (VA) from refusing care to veterans who display DB.¹ The VHA defines DB as any behavior that is intimidating, threatening, or dangerous or that has, or could, jeopardize the health or safety of patients, VHA staff, or others.²

VA Response to DB Law

The VA Response to Disruptive Behavior of Patients requires the VHA to provide alternative care options that minimize risk while ensuring services; for example, providing care at a different location and/or time when additional staff are available to assist and monitor the patient. This can provide a unique opportunity to capture data on DB and the results of alternative forms of caring for this population. DB may represent a symptom of a health problem. Further, patients who are refused care because of DB may pose a threat to the community if their medical conditions are not treated or managed properly.

The reason public health care organizations refuse care to persons who display DB is clear: DBs hinder business operations, are financially taxing, and put health care workers at risk.^3-10 “In 2009, the VHA spent close to $5.5 million on workers’ compensation and medical expenditures for 425 incidents–or about $130,000 per DB incident (Hodgson M, Drummond D, Van Male L. Unpublished data, 2010).” In another study, 106 of 762 nurses in 1 hospital system reported an assault by a patient, and 30 required medical attention, which resulted in a total cost of $94,156.⁸ From 2002 to 2013, incidents of serious workplace violence requiring days off for an injured worker to recover on average were 4 times more common in health care than in other industries.^6-11 Incidents of patient violence and aggression toward staff transcend specialization; however, hospital nurses and staff from the emergency, rehabilitation and gerontology departments, psychiatric unit, and home-based services are more susceptible and vulnerable to DB incidents than are other types of employees.^8,10-19

Data reported by health care staff suggest that patients rather than staff members or visitors initiate > 70% of serious physical attacks against health care workers.^9,13,20-23 A 2015 study of VHA health care providers (HCPs) found that > 60% had experienced some form of DB, verbal abuse being the most prevalent, followed by sexual abuse and physical abuse.²⁰ Of 72,000 VHA staff responding to a nationwide survey, 13% experienced, on average, ≥ 1 assault by a veteran (eg, something was thrown at them; they were pushed, kicked, slapped; or were threatened or injured by a weapon).^8,21Although 13% may seem small, the incidents may have lasting financial and emotional distress. Risk factors associated with DB include medication nonadherence, history of drug and alcohol use, disappointment with care, history of violence, and untreated mental health concerns.^19,24,25 Also, unmarried and young patients are more likely to display violence against health care workers.²⁶

To meet its legal obligations and deliver empathetic care, the VHA documents and analyzes data on all patients who exhibit DB. A local DB Committee (DBC) reviews the data, whether it occurs in an inpatient or outpatient setting, such as community-based outpatient clinics. Once a DB incident is reported, the DBC begins an evidence-based risk evaluation, including the option of contacting the persons who displayed or experienced the DB. Goals are to (1) prevent future DB incidents; (2) detect vulnerabilities in the environment; and (3) collaborate with HCPs and patients to provide optimal care while improving the patient/provider interactions.

Effects of Disruptive Behavior

DB has negative consequences for both patients and health care workers and results in poor evaluations of care from both groups.^27-32 Aside from interfering with safe medical care, DB also impacts care for other patients by delaying access to care and increasing appointment wait times due to employee absenteeism and staff shortages.^3,4,20,32,33 For HCPs, patient violence is associated with unwillingness to provide care, briefer treatment periods, and decreases in occupational satisfaction, performance, and commitment.^10,28,31 Coping with DB can compromise the HCP’s ability to stay focused and engaged in providing health care, increasing errors.^9,15,31

Harmful health effects experienced by HCPs who have been victims of DB include fear, mood disorders, anxiety, all symptoms of psychological distress and posttraumatic stress disorder (PTSD).^{10,22,30,34-36} In a study of the impact on productivity of PTSD triggered by job-related DB, PTSD symptoms were associated with withdrawal from or minimizing encounters with patients, job turnover, and troubles with thinking.^35,36 Nurses with PTSD symptoms who stayed on the job had difficulty staying cognitively focused and managing “higher level work demands that required attention to detail or communication skills.”³⁶ Due to the detrimental impact of DB, it is reasonable to expect a decrease in the quality of care rendered to patients by impacted employees. The quality of care for all patients of HCPs who have experienced a DB is poorer than that of patients of HCPs who have not experienced a DB.²⁹

Reporting Disruptive Behavior

The literature suggests that consistent and effective DB reporting is pivotal to improving the outcome and quality of care for those displaying DB.^37-39 To provide high-quality health services to veterans who display DB, the VHA must promote the management and reporting of DB. Without knowledge of the full spectrum of DB events at VHA facilities, efforts to prevent or manage DB and ensure safety may have limited impact.^7,37 Reports can be used for clinical decision making to optimize staff training in delivery of quality care while assuring staff safety. More than 80% of DB incidents occur during interactions with patients, thus this is a clinical issue that can affect the outcome of patient care.^8,21

Documented DB reports are used to analyze the degree, frequency, and nature of incidents, which might reveal risk factors and develop preventive efforts and training for specific hazards.^8,39 Some have argued that implementing a standardized DB reporting system is a crucial first step toward minimizing hazards and improving health care.^38,40,41

When DB incidents were recorded through a hospital electronic reporting system and discussed in meetings, staff reported: (1) increased awareness of DB; (2) improved ability to manage DB incidents; and (3) amplified reporting of incidents.^38,41,42 These findings support similar results from studies of an intervention implemented at VA Community Living Centers (CLCs) from 2013 to 2017: Staff Training in Assisted Living Residences (STAR-VA).^4,12,19 The aim of STAR-VA was to minimize challenging dementia-related DB in CLCs. The intervention initially was established to train direct-care, assisted-living staff to provide better care to older patients displaying DB. Data revealed that documentation of DBs was, the first step to ensuring staff and patient safety.^18,40

VHA Reporting System

In 2013, the VA Office of Inspector General (OIG) found no standardized documentation of DB events across the VA health care system.⁴² Instead, DB events were documented in multiple records in various locations, including administrative and progress notes in the electronic health record (EHR), police reports, e-mails, or letters submitted to DBC chairs.⁴² This situation reduced administrators’ ability to consider all relevant information and render appropriate decisions in DB cases.⁴² In 2015, based on OIG recommendations, the VHA implemented the Disruptive Behavior Reporting System (DBRS) nationwide, which allowed all VHA staff to report DB events. The DBRS was designed to address factors likely to impede reporting and management of DB, namely, complexity of and lack of access to a central reporting system.^43,44 The DBRS is currently the primary VHA tool to document DB events.

The DBRS consists of 32 questions in 5 sections relating to the (1) location and time of DB event; (2) reporter; (3) disrupter; (4) DB event details; and (5) the person who experienced (experiencer) the event. The system also provides a list of the types of DB, such as inappropriate communication, bullying and/or intimidation, verbal or written threat of physical harm, physical violence, sexual harassment, sexual assault, and property damage. The DBRS has the potential to provide useful data on DB and DB reporting, such as the typical staff entering data and the number and/or types of DB occurring.

The DBRS complements the preexisting VHA policies and committees for care of veterans who display DB.^{1-3,14,21,24,25} The VHA Workplace Violence Prevention Program (WVPP) required facilities to submit data on DB events through a Workplace Behavioral Risk report. Data for the report were obtained from police reports, patient safety reports, DBC records, and notes in the EHR. Following implementations of DBRS, the number of DB events per year became a part of facility performance standards.

VHA is creating novel approaches to handling DB that allow health care workers to render care in a safe and effective manner guided by documented information. For example, DBCs can recommend the use of Category I Patient Record Flags (PRFs) following documented DB, which informs staff of the potential risk of DB and provides guidance on protective methods to use when meeting with the patient.^2,21,24 A survey of 140 VA hospital chiefs of staff indicated that DBC procedures were related to a decrease in the rates of assaults.¹ Additionally, VA provides training for staff in techniques to promote personal safety, such as identifying signs that precede DB, using verbal deescalation, and practicing therapeutic containment.

Resistance to Reporting

Many health care employees and employers are reticent to report DBs.^{22,31,43,45-48} Studies suggest health care organizations can cultivate a culture that is resistant to reporting DB.^49,50 This complicates the ability of the health care system to design and maintain safety protocols and safer treatment plans.^3,41,51 Worldwide, < 30% of DBs are reported.⁴⁷ One barrier may be that supervisors may not wish to acknowledge DBs on their units or may not provide sufficient staff time for training or reporting.^31,46,47 HCPs may worry that a DB report will stigmatize patients, especially those who are elderly or have cognitive impairment, brain injury, psychological illness, or developmental disability. Patients with cognitive conditions are reportedly 20% more likely to be violent toward caregivers and providers.³¹ A dementia diagnosis, for example, is associated with a high likelihood for DB.^30,52 More than 80% of DB events displayed by patients with dementia may go unreported.^26,31,50,52

Some clinicians may attribute DB to physiologic conditions that need to be treated, not reported. However, employers can face various legal liabilities if steps are not taken to protect employees.^47,51 Federal and state statutes require that organizations provide a healthy and safe employment environment for workers. This requires that employers institute reasonable protective measures, such as procedures to intervene, policies on addressing DB incidents, and/or training to minimize or deescalate DB.^51,53 Also, employees may sue employers if security measures are inadequate or deficient in properly investigating current and past evidence of DB or identifying vulnerabilities in the workplace. Unwillingness to investigate DB and safety-related workplace concerns have contributed to increased workplace violence and legal liability.^52,53 The mission of caring and trust is consistent with assuring a safe environment.

Training and Empathetic Care

To combat cultural resistance to reporting DBs, more and perhaps different contextual approaches to education and training may be needed that address ethical dilemmas and concerns of providers. The success of training relies on administrators supporting staff in reporting DB. Training must address providers’ conflicting beliefs and assist with identifying strategies to provide the best possible care for patients who display DB.^1,38 HCPs are less likely to document a DB if they feel that administrators are creating documentation that will have negative consequences for a patient. Thus, leadership is responsible for ensuring that misconceptions are dispelled through training and other efforts and information on how reported DB data will be used is communicated through strategic channels.

Education and training must consider empathic care that attempts to understand why patients behave as they do through the information gathered.⁵⁵ Empathy in health care is multifaceted: It involves comprehending a patient’s viewpoint, circumstances, and feelings and the capacity to analyze whether one is comprehending these accurately in order to demonstrate supportive care.^54,55

Improving patient and staff interaction once a problematic behavior is identified is the aim of empathic care. Increasing empathic care can improve compassionate, patient-centered interactions that begin once the patient seeks care. This approach has proven to decrease DB by patients with dementia and improve their care, lessen staff problems during interactions, and increase staff morale.²⁰ Experts call for the adoption of an interpersonal approach to patient encounters, and there is evidence that creating organizational change by moving toward compassionate care can lead to a positive impact for patients.^54,55

Future Studies

There are growth opportunities in utilization of the DBRS. Analysis of the DBRS database by the VA Central Office (VACO) showed that the system is underutilized by facilities across the VA system.⁵⁶ In response to this current underutilization, VACO is taking steps to close these gaps through increasing training to staff and promotion of the use of the DBRS. A 2015 pilot study of VHA providers showed that > 70% of providers had experienced a DB as defined by VHA, but only 34% of them reported their most recently experienced DB within the past 12 months.²⁰ Thus, DBRS use must be studied within the context that patient-perpetrated DB is underreported in health care organizations.^{5,9,29,41,43,57,58} Studies addressing national DBRS utilization patterns and the cost associated with implementing the DBRS also are needed. One study suggests that there is an association between measures of facility complexity and staff perceptions of safety, which should be considered in analyzing DBRS usage.⁵⁷ Studies addressing the role of the DBRS and misconceptions that the tool may represent a punitive tool also are needed. VHA should consider how the attribution “disruptive behavior” assigns a negative connotation and leads HCPs to avoid using the DBRS. Additionally, DB reporting may increase when HCPs understand that DB reporting is part of the comprehensive, consultative strategy to provide the best care to patients.

Conclusion

Accurate reporting of DB events enables the development of strategies for multidisciplinary teams to work together to minimize hazards and to provide interventions that provide for the safe delivery of health care to all patients. Improving reporting ensures there is an accurate representation of how disruptive events impact care provided within a facility—and what types of variables may be associated with increased risk for these types of events.

Additionally, ensuring that reporting is maximized also provides the VHA with opportunities for DBCs to offer evidence-based risk assessment of violence and consultation to staff members who may benefit from improved competencies in working with patients who display DB. These potential improvements are consistent with the VHA I CARE values and will provide data that can inform recommendations for health care in other agencies/health care organizations.

Acknowledgments
This work was supported by the Center of Innovation on Disability and Rehabilitation Research (CINDRR) of the Health Services Research and Development Service, Office of Research and Development, Department of Veterans Affairs.

Historically, the Veterans Health Administration (VHA) has excelled at improving veterans’ access to health care and enhancing foundational services, such as prosthetics and other veteran-centric services, and this continues to be the VHA’s top priority.¹ Travel distance and time are often barriers to accessing health care for many veterans.^2-11 For veterans with disabilities who must overcome additional physical, cognitive, and emotional obstacles to access vital rehabilitation services, these geographic obstacles are magnified. Further compounding the challenge is that rehabilitation therapies frequently require multiple encounters. Telerehabilitation is a promising solution for veterans in need of rehabilitation to regain optimal functioning. This alternative mode of service delivery can help veterans overcome geographic access barriers by delivering health care directly to veterans in their homes or nearby community-based outpatient clinics.^12,13

A growing body of evidence supports telerehabilitation. In a 2017 systematic review and meta-analysis, Cottrell and colleagues reviewed and analyzed data from 13 studies that met their inclusion criteria; specifically, their meta-analytic sample comprised adults aged ≥ 18 years presenting with any diagnosed primary musculoskeletal condition; treatment interventions via a real-time telerehabilitation medium, trials that had a comparison group with the same condition; provided clinical outcomes data, and included published randomized and nonrandomized controlled trials.¹⁴ Based on their aggregated results, they concluded that real-time telerehabilitation was effective in improving physical function (standardized mean difference [SMD], 0.63; 95% CI, 0.92-2.33; I², 93%), and reducing pain (SMD, 0.66; 95% CI, −0.27- .60; I², 96%) in patients with any diagnosed primary musculoskeletal condition.¹⁴

Two other systematic reviews conducted by Pietrzak and colleagues and Agostini and colleagues also demonstrated the clinical effectiveness of telerehabilitation.^15,16 Clinical effectiveness was defined as changes in health, functional status, and satisfaction with the telerehabilitation services delivered. The studies examined in the review included those that provided online self-management and education in addition to exercise via teleconferencing in real time.

Pietrzak and colleagues found that Internet-based osteoarthritis self-management interventions significantly improved 4 of 6 health status measures reviewed (ie, pain, fatigue, activity limitation, health distress, disability, and self‐reported global health).¹⁵ User acceptance and satisfaction were high (≥ 70% satisfied) in all studies meeting the inclusion criteria.

Agostini and colleagues found that telerehabilitation was more effective than other modes of delivering rehabilitation to regain motor function in cardiac (SMD, 0.24; 95% CI, 0.04-0.43) and total knee arthroplasty (Timed Up and Go test: SMD, −5.17; 95% CI, −9.79- −0.55) patients.¹⁶ Some evidence from VHA and non-VHA studies also support the use of telerehabilitation to reduce health care costs,^17-19 improve treatment adherence,^12,20 and enhance patient physical, cognitive and mobility function, as well as patient satisfaction and health-related quality of life.^13,21-24

Since the first recorded use of telehealth in 1959, the application of technology to deliver health care, including rehabilitation services, has increased exponentially.¹⁴ In fiscal year (FY) 2017 alone, the VA provided > 2 million episodes of care for > 700,000 veterans using telehealth services.²⁵

Although the process for accessing telerehabilitation may vary throughout the VA, typically a few common factors make a veteran eligible for this mode of rehabilitation care delivery: Veterans must meet criteria for a specific program (eg, amputation, occupational therapy, and physical therapy) and receive VA care from a VA medical facility or clinic that offers telehealth services. Care providers must believe that the veteran would benefit from telerehabilitation (eg, limited mobility and long-distance travel to the facility) and that they would be able to receive an appropriate consult. The veteran must meet the following requirements: (1) willingness to consent to a visit via telehealth; (2) access to required equipment/e-mail; and (3) a caregiver to assist if they are unable to complete a visit independently.

In this article, we provide an overview of the growth of telerehabilitation in the VHA. Data are presented for specific telerehabilitation programs over time and by rurality.

Methods

The VHA Support Service Center works with VHA program offices and field users to provide field-focused business, clinical, and special topic reports. An online portal provides access to these customizable reports organized as data cubes, which represent data dimensions (ie, clinic type) and measures (ie, number of unique patients). For this study, we used the Connected Care, Telehealth, Call Centers Clinical Video Telehealth/Store and Forward Telehealth data cube clinical stop codes to identify the numbers of telerehabilitation veteran users and encounters across time. The following telerehabilitation clinic-stop codes were selected: 197 (polytrauma/traumatic brain injury [TBI]–individuals), 201 (Physical Medicine and Rehabilitation [PM&R] Service), 205 (physical therapy), 206 (occupational therapy), 211 (PM&R amputation clinic), 418 (amputation clinic), 214 (kinesiotherapy), and 240 (PM&R assistive technology clinic). Data for total unique patients served and the total number of encounters were extracted at the national level and by rurality from FY 2012 to FY 2017, providing the past 5 years of VHA telerehabilitation data.

It is important to note that in FY 2015, the VHA changed its definition of rurality to a rural-urban commuting areas (RUCA)-based system (www.ruralhealth.va.gov/rural-definition.asp). Prior to FY 2015, the VHA used the US Census Bureau (CB) urbanized area definitions. According to CB, an urbanized area contains a central city and surrounding area that totals > 50,000 in population. It also includes places outside of urbanized areas with populations > 2,500. Rural areas are defined as all other areas. VHA added a third category, highly rural, which is defined as areas that had < 7 people per square mile. In the RUCA system, each census tract defined by the CB is given a score. The VHA definitions are as follows:

• Urban (U)—census tracts with RUCA scores of 1.0 or 1.1. These tracts are determined by the CB as being in an urban core and having the majority of their workers commute within that same core (1.0). If 30% to 49% commute to an even larger urban core, then the code is 1.1;
• Rural (R)—all tracts not receiving scores in the urban or highly rural tiers; and
• Highly rural (H)—tracts with a RUCA score of 10.0. These are the most remote occupied land areas. Less than 10% of workers travel to CB-defined urbanized areas or urban clusters.

In addition, VHA recently added an “I” category to complement “U,” “R,” and “H.” The “I” value is assigned to veterans living on the US insular islands (ie, territories): Guam, American Samoa, Northern Marianas, and US Virgin Islands. For the analysis by rurality in this study, we excluded veterans living in the insular islands and those of unknown rurality (< 1.0% of patients and encounters). Further, because the numbers of highly rural veterans were relatively small (< 2% of patients and encounters), the rural and highly rural categories were combined and compared with urban-dwelling veterans.

Results

Overall, the workload for telerehabilitation nearly quadrupled over the 5-year period (Table 1 and Figure 1). 

Interesting trends were seen by clinic type. Some clinics increased substantially, whereas others showed only moderate increases, and in 1 case (PM&R Service), a decrease. For example, there is significant growth in the number of patients and encounters involving physical therapy through telerehabilitation. This telerehabilitation clinic increased its workload from 1,676 patients with 3,016 encounters in FY 2012 to 9,136 patients with 11,834 encounters in FY 2017, accounting for 62.6% of total growth in patients and 56.8% of total growth in encounters.

Other clinics showing substantial growth over time included occupational therapy and polytrauma/TBI-individual secondary evaluation. Kinesiotherapy telerehabilitation was almost nonexistent in the VHA during FY 2012, with only 23 patients having 23 encounters. By FY 2017, there were 563 patients with 624 kinesiotherapy telerehabilitation encounters, equating to staggering increases in 5 years: 2,348% for patients and 2,613% for encounters. Similarly, the Physical Medicine and Rehabilitation Assistive Technology clinics had very low numbers in FY 2012 (patients, 2; encounters, 3) and increased over time; albeit, at a slow rate.

Trends by Rurality

Trends by rural location of patients and encounters must be interpreted with caution because of the changing rural definition between FY 2014 and FY 2015 (Tables 2 and 3; Figures 3 and 4). 

The increased total number of patients seen between FY 2012 and FY 2014 (old definition) was 225% for rural veterans vs 134% for urban veterans. Between FY 2015 and FY 2017 (new definition), the increase was lower for both groups (rural, 13.4%; urban, 7.3%), but rural veterans still increased at a higher rate than did urban dwellers.

Discussion

Our primary aim was to provide data on the growth of telerehabilitation in the VHA over the past 5 years. Our secondary aim was to examine growth in the use of telerehabilitation by rurality. Specifically, we provided an overview of telerehabilitation growth in terms of unique patients and overall encounters in the VHA by rurality from FY 2012 to FY 2014 and FY 2015 to FY 2017 using the following programs: Polytrauma/TBI, PM&R Service, physical therapy, occupational therapy, PM&R amputation clinic, amputation clinic, kinesiotherapy, and PM&R assistive technology clinic. Our findings demonstrated a noteworthy increase in telerehabilitation encounters and unique patients over time for these programs. These findings were consistent with the overall trend of continued growth and expansion of telehealth within the VHA.

Our findings reveal an upward trend in the total number of rural encounters and rural unique patients despite the change in the VA’s definition of rurality in FY 2015. To our knowledge, urban and rural use of telerehabilitation has not been examined previously. Under both definitions of rurality, encounters and unique patients show an important increase over time, and by year-end 2017, more than half of all patients and encounters were attributed to rural patients (53.7% and 53.9%, respectively). Indeed, the upward trend may have been more pronounced if the rural definition had not changed in FY 2015. Our early VHA stroke patients study on the difference between rural-urban patients and taxonomies showed that the RUCA definition was more likely to reduce the number of rural patients by 8.5% than the early definition used by the VHA.²⁶

It is notable that although the use of tele-delivery of rehabilitation has continually increased, the rate of this increase was steeper from FY 2012 to FY 2014 than FY 2015 to FY 2017. For the programs under consideration in this study, the total number of rural patients/encounters increased throughout the observed periods. However, urban patients and encounters increased through FY 2016 and experienced a slight decrease in FY 2017.

The appearance of a slower rate of increase may be due to a rapid initial rate of increase through early adopters and “crossing the diffusion chasm,” a well-documented process of slower diffusion between the time of invention to penetration that often characterizes the spread of successful telehealth innovations.²⁷ Integrating technology into care delivery innovation requires the integration of technical, clinical, and administrative processes and can take time to scale successfully.²⁸

With an emphasis on increasing access to rehabilitation services, the VHA can expect to see a continuing increase in both the number and the percentage of telerehabilitation rural patients and encounters. The VHA has several telerehabilitation initiatives underway through the VHA’s Physical Medicine and Rehabilitation Telerehabilitation Enterprise Wide Initiative (TREWI) and Rural Veterans Telerehabilitation Initiative. These projects demonstrate the feasibility of this delivery approach and facilitate integration of this modality in clinical workflows. However, to sustain these efforts, facilities will need more infrastructure and personnel resources dedicated to the delivery of services.

In an ongoing evaluation of the TREWI, several factors seem to influence the uptake of the VHA Office of Rural Health TREWI programs. These factors are the presence or absence of a local site champion; the quality of hospital leadership support; the quality of past relationships between telerehabilitation sending sites and receiving sites; barriers to getting a telehealth service agreement in place; the availability of space; administrative know-how on setting up clinics appropriately; time involved to bring on staff; contracting issues; equipment availability and installation; cultural issues in embracing technologic innovation; training burden; hassle factors; and limited funds. Although early adopters may be able to negotiate and push through many of the barriers associated with the diffusion of telerehabilitation, the numerous barriers may slow its larger systemwide diffusion.

Telerehabilitation is a promising mode to deliver care to rural veterans who otherwise may not have access to this type of specialty care. Therefore, the identification of elements that foster telerehabilitation growth in future investigations can assist policy makers and key stakeholders in optimally leveraging program resources for maximal productivity. Future studies investigating the drivers of increases in telerehabilitation growth by rurality are warranted. Furthermore, more research is needed to examine telerehabilitation growth quality of care outcomes (eg, patient and provider satisfaction) to ensure that care is not only timely and accessible, but of high quality.

Conclusion

Disparities between rural and urban veterans compel a mode of expanding delivery of care. The VHA has embraced the use of telehealth modalities to extend its reach of rehabilitation services to veterans with disability and rehabilitation needs. Growth in telerehabilitation rural patient encounters increases access to rehabilitative care, reduces patient and caregiver travel burden, and helps ensure treatment adherence. Telerehabilitation utilization (unique patients and total encounters) is growing more rapidly for rural veterans than for their urban counterparts. Overall, telerehabilitation is filling a gap for rural veterans, as well as veterans in general with challenges in accessibility to health care. In order to make full use of the telerehabilitation services across its health care system, VA health care facilities may need to expand their effort in telerehabilitation dissemination and education among providers and veterans, particularly among providers who are less familiar with telerehabilitation services and among veterans who live in rural or highly rural areas and need special rehabilitation care.

Historically, the Veterans Health Administration (VHA) has excelled at improving veterans’ access to health care and enhancing foundational services, such as prosthetics and other veteran-centric services, and this continues to be the VHA’s top priority.¹ Travel distance and time are often barriers to accessing health care for many veterans.^2-11 For veterans with disabilities who must overcome additional physical, cognitive, and emotional obstacles to access vital rehabilitation services, these geographic obstacles are magnified. Further compounding the challenge is that rehabilitation therapies frequently require multiple encounters. Telerehabilitation is a promising solution for veterans in need of rehabilitation to regain optimal functioning. This alternative mode of service delivery can help veterans overcome geographic access barriers by delivering health care directly to veterans in their homes or nearby community-based outpatient clinics.^12,13

A growing body of evidence supports telerehabilitation. In a 2017 systematic review and meta-analysis, Cottrell and colleagues reviewed and analyzed data from 13 studies that met their inclusion criteria; specifically, their meta-analytic sample comprised adults aged ≥ 18 years presenting with any diagnosed primary musculoskeletal condition; treatment interventions via a real-time telerehabilitation medium, trials that had a comparison group with the same condition; provided clinical outcomes data, and included published randomized and nonrandomized controlled trials.¹⁴ Based on their aggregated results, they concluded that real-time telerehabilitation was effective in improving physical function (standardized mean difference [SMD], 0.63; 95% CI, 0.92-2.33; I², 93%), and reducing pain (SMD, 0.66; 95% CI, −0.27- .60; I², 96%) in patients with any diagnosed primary musculoskeletal condition.¹⁴

Two other systematic reviews conducted by Pietrzak and colleagues and Agostini and colleagues also demonstrated the clinical effectiveness of telerehabilitation.^15,16 Clinical effectiveness was defined as changes in health, functional status, and satisfaction with the telerehabilitation services delivered. The studies examined in the review included those that provided online self-management and education in addition to exercise via teleconferencing in real time.

Pietrzak and colleagues found that Internet-based osteoarthritis self-management interventions significantly improved 4 of 6 health status measures reviewed (ie, pain, fatigue, activity limitation, health distress, disability, and self‐reported global health).¹⁵ User acceptance and satisfaction were high (≥ 70% satisfied) in all studies meeting the inclusion criteria.

Agostini and colleagues found that telerehabilitation was more effective than other modes of delivering rehabilitation to regain motor function in cardiac (SMD, 0.24; 95% CI, 0.04-0.43) and total knee arthroplasty (Timed Up and Go test: SMD, −5.17; 95% CI, −9.79- −0.55) patients.¹⁶ Some evidence from VHA and non-VHA studies also support the use of telerehabilitation to reduce health care costs,^17-19 improve treatment adherence,^12,20 and enhance patient physical, cognitive and mobility function, as well as patient satisfaction and health-related quality of life.^13,21-24

Since the first recorded use of telehealth in 1959, the application of technology to deliver health care, including rehabilitation services, has increased exponentially.¹⁴ In fiscal year (FY) 2017 alone, the VA provided > 2 million episodes of care for > 700,000 veterans using telehealth services.²⁵

Although the process for accessing telerehabilitation may vary throughout the VA, typically a few common factors make a veteran eligible for this mode of rehabilitation care delivery: Veterans must meet criteria for a specific program (eg, amputation, occupational therapy, and physical therapy) and receive VA care from a VA medical facility or clinic that offers telehealth services. Care providers must believe that the veteran would benefit from telerehabilitation (eg, limited mobility and long-distance travel to the facility) and that they would be able to receive an appropriate consult. The veteran must meet the following requirements: (1) willingness to consent to a visit via telehealth; (2) access to required equipment/e-mail; and (3) a caregiver to assist if they are unable to complete a visit independently.

In this article, we provide an overview of the growth of telerehabilitation in the VHA. Data are presented for specific telerehabilitation programs over time and by rurality.

Methods

The VHA Support Service Center works with VHA program offices and field users to provide field-focused business, clinical, and special topic reports. An online portal provides access to these customizable reports organized as data cubes, which represent data dimensions (ie, clinic type) and measures (ie, number of unique patients). For this study, we used the Connected Care, Telehealth, Call Centers Clinical Video Telehealth/Store and Forward Telehealth data cube clinical stop codes to identify the numbers of telerehabilitation veteran users and encounters across time. The following telerehabilitation clinic-stop codes were selected: 197 (polytrauma/traumatic brain injury [TBI]–individuals), 201 (Physical Medicine and Rehabilitation [PM&R] Service), 205 (physical therapy), 206 (occupational therapy), 211 (PM&R amputation clinic), 418 (amputation clinic), 214 (kinesiotherapy), and 240 (PM&R assistive technology clinic). Data for total unique patients served and the total number of encounters were extracted at the national level and by rurality from FY 2012 to FY 2017, providing the past 5 years of VHA telerehabilitation data.

It is important to note that in FY 2015, the VHA changed its definition of rurality to a rural-urban commuting areas (RUCA)-based system (www.ruralhealth.va.gov/rural-definition.asp). Prior to FY 2015, the VHA used the US Census Bureau (CB) urbanized area definitions. According to CB, an urbanized area contains a central city and surrounding area that totals > 50,000 in population. It also includes places outside of urbanized areas with populations > 2,500. Rural areas are defined as all other areas. VHA added a third category, highly rural, which is defined as areas that had < 7 people per square mile. In the RUCA system, each census tract defined by the CB is given a score. The VHA definitions are as follows:

• Urban (U)—census tracts with RUCA scores of 1.0 or 1.1. These tracts are determined by the CB as being in an urban core and having the majority of their workers commute within that same core (1.0). If 30% to 49% commute to an even larger urban core, then the code is 1.1;
• Rural (R)—all tracts not receiving scores in the urban or highly rural tiers; and
• Highly rural (H)—tracts with a RUCA score of 10.0. These are the most remote occupied land areas. Less than 10% of workers travel to CB-defined urbanized areas or urban clusters.

In addition, VHA recently added an “I” category to complement “U,” “R,” and “H.” The “I” value is assigned to veterans living on the US insular islands (ie, territories): Guam, American Samoa, Northern Marianas, and US Virgin Islands. For the analysis by rurality in this study, we excluded veterans living in the insular islands and those of unknown rurality (< 1.0% of patients and encounters). Further, because the numbers of highly rural veterans were relatively small (< 2% of patients and encounters), the rural and highly rural categories were combined and compared with urban-dwelling veterans.

Results

Overall, the workload for telerehabilitation nearly quadrupled over the 5-year period (Table 1 and Figure 1). 

Interesting trends were seen by clinic type. Some clinics increased substantially, whereas others showed only moderate increases, and in 1 case (PM&R Service), a decrease. For example, there is significant growth in the number of patients and encounters involving physical therapy through telerehabilitation. This telerehabilitation clinic increased its workload from 1,676 patients with 3,016 encounters in FY 2012 to 9,136 patients with 11,834 encounters in FY 2017, accounting for 62.6% of total growth in patients and 56.8% of total growth in encounters.

Other clinics showing substantial growth over time included occupational therapy and polytrauma/TBI-individual secondary evaluation. Kinesiotherapy telerehabilitation was almost nonexistent in the VHA during FY 2012, with only 23 patients having 23 encounters. By FY 2017, there were 563 patients with 624 kinesiotherapy telerehabilitation encounters, equating to staggering increases in 5 years: 2,348% for patients and 2,613% for encounters. Similarly, the Physical Medicine and Rehabilitation Assistive Technology clinics had very low numbers in FY 2012 (patients, 2; encounters, 3) and increased over time; albeit, at a slow rate.

Trends by Rurality

Trends by rural location of patients and encounters must be interpreted with caution because of the changing rural definition between FY 2014 and FY 2015 (Tables 2 and 3; Figures 3 and 4). 

The increased total number of patients seen between FY 2012 and FY 2014 (old definition) was 225% for rural veterans vs 134% for urban veterans. Between FY 2015 and FY 2017 (new definition), the increase was lower for both groups (rural, 13.4%; urban, 7.3%), but rural veterans still increased at a higher rate than did urban dwellers.

Discussion

Our primary aim was to provide data on the growth of telerehabilitation in the VHA over the past 5 years. Our secondary aim was to examine growth in the use of telerehabilitation by rurality. Specifically, we provided an overview of telerehabilitation growth in terms of unique patients and overall encounters in the VHA by rurality from FY 2012 to FY 2014 and FY 2015 to FY 2017 using the following programs: Polytrauma/TBI, PM&R Service, physical therapy, occupational therapy, PM&R amputation clinic, amputation clinic, kinesiotherapy, and PM&R assistive technology clinic. Our findings demonstrated a noteworthy increase in telerehabilitation encounters and unique patients over time for these programs. These findings were consistent with the overall trend of continued growth and expansion of telehealth within the VHA.

Our findings reveal an upward trend in the total number of rural encounters and rural unique patients despite the change in the VA’s definition of rurality in FY 2015. To our knowledge, urban and rural use of telerehabilitation has not been examined previously. Under both definitions of rurality, encounters and unique patients show an important increase over time, and by year-end 2017, more than half of all patients and encounters were attributed to rural patients (53.7% and 53.9%, respectively). Indeed, the upward trend may have been more pronounced if the rural definition had not changed in FY 2015. Our early VHA stroke patients study on the difference between rural-urban patients and taxonomies showed that the RUCA definition was more likely to reduce the number of rural patients by 8.5% than the early definition used by the VHA.²⁶

It is notable that although the use of tele-delivery of rehabilitation has continually increased, the rate of this increase was steeper from FY 2012 to FY 2014 than FY 2015 to FY 2017. For the programs under consideration in this study, the total number of rural patients/encounters increased throughout the observed periods. However, urban patients and encounters increased through FY 2016 and experienced a slight decrease in FY 2017.

The appearance of a slower rate of increase may be due to a rapid initial rate of increase through early adopters and “crossing the diffusion chasm,” a well-documented process of slower diffusion between the time of invention to penetration that often characterizes the spread of successful telehealth innovations.²⁷ Integrating technology into care delivery innovation requires the integration of technical, clinical, and administrative processes and can take time to scale successfully.²⁸

With an emphasis on increasing access to rehabilitation services, the VHA can expect to see a continuing increase in both the number and the percentage of telerehabilitation rural patients and encounters. The VHA has several telerehabilitation initiatives underway through the VHA’s Physical Medicine and Rehabilitation Telerehabilitation Enterprise Wide Initiative (TREWI) and Rural Veterans Telerehabilitation Initiative. These projects demonstrate the feasibility of this delivery approach and facilitate integration of this modality in clinical workflows. However, to sustain these efforts, facilities will need more infrastructure and personnel resources dedicated to the delivery of services.

In an ongoing evaluation of the TREWI, several factors seem to influence the uptake of the VHA Office of Rural Health TREWI programs. These factors are the presence or absence of a local site champion; the quality of hospital leadership support; the quality of past relationships between telerehabilitation sending sites and receiving sites; barriers to getting a telehealth service agreement in place; the availability of space; administrative know-how on setting up clinics appropriately; time involved to bring on staff; contracting issues; equipment availability and installation; cultural issues in embracing technologic innovation; training burden; hassle factors; and limited funds. Although early adopters may be able to negotiate and push through many of the barriers associated with the diffusion of telerehabilitation, the numerous barriers may slow its larger systemwide diffusion.

Telerehabilitation is a promising mode to deliver care to rural veterans who otherwise may not have access to this type of specialty care. Therefore, the identification of elements that foster telerehabilitation growth in future investigations can assist policy makers and key stakeholders in optimally leveraging program resources for maximal productivity. Future studies investigating the drivers of increases in telerehabilitation growth by rurality are warranted. Furthermore, more research is needed to examine telerehabilitation growth quality of care outcomes (eg, patient and provider satisfaction) to ensure that care is not only timely and accessible, but of high quality.

Conclusion

Disparities between rural and urban veterans compel a mode of expanding delivery of care. The VHA has embraced the use of telehealth modalities to extend its reach of rehabilitation services to veterans with disability and rehabilitation needs. Growth in telerehabilitation rural patient encounters increases access to rehabilitative care, reduces patient and caregiver travel burden, and helps ensure treatment adherence. Telerehabilitation utilization (unique patients and total encounters) is growing more rapidly for rural veterans than for their urban counterparts. Overall, telerehabilitation is filling a gap for rural veterans, as well as veterans in general with challenges in accessibility to health care. In order to make full use of the telerehabilitation services across its health care system, VA health care facilities may need to expand their effort in telerehabilitation dissemination and education among providers and veterans, particularly among providers who are less familiar with telerehabilitation services and among veterans who live in rural or highly rural areas and need special rehabilitation care.

Historically, the Veterans Health Administration (VHA) has excelled at improving veterans’ access to health care and enhancing foundational services, such as prosthetics and other veteran-centric services, and this continues to be the VHA’s top priority.¹ Travel distance and time are often barriers to accessing health care for many veterans.^2-11 For veterans with disabilities who must overcome additional physical, cognitive, and emotional obstacles to access vital rehabilitation services, these geographic obstacles are magnified. Further compounding the challenge is that rehabilitation therapies frequently require multiple encounters. Telerehabilitation is a promising solution for veterans in need of rehabilitation to regain optimal functioning. This alternative mode of service delivery can help veterans overcome geographic access barriers by delivering health care directly to veterans in their homes or nearby community-based outpatient clinics.^12,13

A growing body of evidence supports telerehabilitation. In a 2017 systematic review and meta-analysis, Cottrell and colleagues reviewed and analyzed data from 13 studies that met their inclusion criteria; specifically, their meta-analytic sample comprised adults aged ≥ 18 years presenting with any diagnosed primary musculoskeletal condition; treatment interventions via a real-time telerehabilitation medium, trials that had a comparison group with the same condition; provided clinical outcomes data, and included published randomized and nonrandomized controlled trials.¹⁴ Based on their aggregated results, they concluded that real-time telerehabilitation was effective in improving physical function (standardized mean difference [SMD], 0.63; 95% CI, 0.92-2.33; I², 93%), and reducing pain (SMD, 0.66; 95% CI, −0.27- .60; I², 96%) in patients with any diagnosed primary musculoskeletal condition.¹⁴

Two other systematic reviews conducted by Pietrzak and colleagues and Agostini and colleagues also demonstrated the clinical effectiveness of telerehabilitation.^15,16 Clinical effectiveness was defined as changes in health, functional status, and satisfaction with the telerehabilitation services delivered. The studies examined in the review included those that provided online self-management and education in addition to exercise via teleconferencing in real time.

Pietrzak and colleagues found that Internet-based osteoarthritis self-management interventions significantly improved 4 of 6 health status measures reviewed (ie, pain, fatigue, activity limitation, health distress, disability, and self‐reported global health).¹⁵ User acceptance and satisfaction were high (≥ 70% satisfied) in all studies meeting the inclusion criteria.

Agostini and colleagues found that telerehabilitation was more effective than other modes of delivering rehabilitation to regain motor function in cardiac (SMD, 0.24; 95% CI, 0.04-0.43) and total knee arthroplasty (Timed Up and Go test: SMD, −5.17; 95% CI, −9.79- −0.55) patients.¹⁶ Some evidence from VHA and non-VHA studies also support the use of telerehabilitation to reduce health care costs,^17-19 improve treatment adherence,^12,20 and enhance patient physical, cognitive and mobility function, as well as patient satisfaction and health-related quality of life.^13,21-24

Since the first recorded use of telehealth in 1959, the application of technology to deliver health care, including rehabilitation services, has increased exponentially.¹⁴ In fiscal year (FY) 2017 alone, the VA provided > 2 million episodes of care for > 700,000 veterans using telehealth services.²⁵

Although the process for accessing telerehabilitation may vary throughout the VA, typically a few common factors make a veteran eligible for this mode of rehabilitation care delivery: Veterans must meet criteria for a specific program (eg, amputation, occupational therapy, and physical therapy) and receive VA care from a VA medical facility or clinic that offers telehealth services. Care providers must believe that the veteran would benefit from telerehabilitation (eg, limited mobility and long-distance travel to the facility) and that they would be able to receive an appropriate consult. The veteran must meet the following requirements: (1) willingness to consent to a visit via telehealth; (2) access to required equipment/e-mail; and (3) a caregiver to assist if they are unable to complete a visit independently.

In this article, we provide an overview of the growth of telerehabilitation in the VHA. Data are presented for specific telerehabilitation programs over time and by rurality.

Methods

The VHA Support Service Center works with VHA program offices and field users to provide field-focused business, clinical, and special topic reports. An online portal provides access to these customizable reports organized as data cubes, which represent data dimensions (ie, clinic type) and measures (ie, number of unique patients). For this study, we used the Connected Care, Telehealth, Call Centers Clinical Video Telehealth/Store and Forward Telehealth data cube clinical stop codes to identify the numbers of telerehabilitation veteran users and encounters across time. The following telerehabilitation clinic-stop codes were selected: 197 (polytrauma/traumatic brain injury [TBI]–individuals), 201 (Physical Medicine and Rehabilitation [PM&R] Service), 205 (physical therapy), 206 (occupational therapy), 211 (PM&R amputation clinic), 418 (amputation clinic), 214 (kinesiotherapy), and 240 (PM&R assistive technology clinic). Data for total unique patients served and the total number of encounters were extracted at the national level and by rurality from FY 2012 to FY 2017, providing the past 5 years of VHA telerehabilitation data.

It is important to note that in FY 2015, the VHA changed its definition of rurality to a rural-urban commuting areas (RUCA)-based system (www.ruralhealth.va.gov/rural-definition.asp). Prior to FY 2015, the VHA used the US Census Bureau (CB) urbanized area definitions. According to CB, an urbanized area contains a central city and surrounding area that totals > 50,000 in population. It also includes places outside of urbanized areas with populations > 2,500. Rural areas are defined as all other areas. VHA added a third category, highly rural, which is defined as areas that had < 7 people per square mile. In the RUCA system, each census tract defined by the CB is given a score. The VHA definitions are as follows:

• Urban (U)—census tracts with RUCA scores of 1.0 or 1.1. These tracts are determined by the CB as being in an urban core and having the majority of their workers commute within that same core (1.0). If 30% to 49% commute to an even larger urban core, then the code is 1.1;
• Rural (R)—all tracts not receiving scores in the urban or highly rural tiers; and
• Highly rural (H)—tracts with a RUCA score of 10.0. These are the most remote occupied land areas. Less than 10% of workers travel to CB-defined urbanized areas or urban clusters.

In addition, VHA recently added an “I” category to complement “U,” “R,” and “H.” The “I” value is assigned to veterans living on the US insular islands (ie, territories): Guam, American Samoa, Northern Marianas, and US Virgin Islands. For the analysis by rurality in this study, we excluded veterans living in the insular islands and those of unknown rurality (< 1.0% of patients and encounters). Further, because the numbers of highly rural veterans were relatively small (< 2% of patients and encounters), the rural and highly rural categories were combined and compared with urban-dwelling veterans.

Results

Overall, the workload for telerehabilitation nearly quadrupled over the 5-year period (Table 1 and Figure 1). 

Interesting trends were seen by clinic type. Some clinics increased substantially, whereas others showed only moderate increases, and in 1 case (PM&R Service), a decrease. For example, there is significant growth in the number of patients and encounters involving physical therapy through telerehabilitation. This telerehabilitation clinic increased its workload from 1,676 patients with 3,016 encounters in FY 2012 to 9,136 patients with 11,834 encounters in FY 2017, accounting for 62.6% of total growth in patients and 56.8% of total growth in encounters.

Other clinics showing substantial growth over time included occupational therapy and polytrauma/TBI-individual secondary evaluation. Kinesiotherapy telerehabilitation was almost nonexistent in the VHA during FY 2012, with only 23 patients having 23 encounters. By FY 2017, there were 563 patients with 624 kinesiotherapy telerehabilitation encounters, equating to staggering increases in 5 years: 2,348% for patients and 2,613% for encounters. Similarly, the Physical Medicine and Rehabilitation Assistive Technology clinics had very low numbers in FY 2012 (patients, 2; encounters, 3) and increased over time; albeit, at a slow rate.

Trends by Rurality

Trends by rural location of patients and encounters must be interpreted with caution because of the changing rural definition between FY 2014 and FY 2015 (Tables 2 and 3; Figures 3 and 4). 

The increased total number of patients seen between FY 2012 and FY 2014 (old definition) was 225% for rural veterans vs 134% for urban veterans. Between FY 2015 and FY 2017 (new definition), the increase was lower for both groups (rural, 13.4%; urban, 7.3%), but rural veterans still increased at a higher rate than did urban dwellers.

Discussion

Our primary aim was to provide data on the growth of telerehabilitation in the VHA over the past 5 years. Our secondary aim was to examine growth in the use of telerehabilitation by rurality. Specifically, we provided an overview of telerehabilitation growth in terms of unique patients and overall encounters in the VHA by rurality from FY 2012 to FY 2014 and FY 2015 to FY 2017 using the following programs: Polytrauma/TBI, PM&R Service, physical therapy, occupational therapy, PM&R amputation clinic, amputation clinic, kinesiotherapy, and PM&R assistive technology clinic. Our findings demonstrated a noteworthy increase in telerehabilitation encounters and unique patients over time for these programs. These findings were consistent with the overall trend of continued growth and expansion of telehealth within the VHA.

Our findings reveal an upward trend in the total number of rural encounters and rural unique patients despite the change in the VA’s definition of rurality in FY 2015. To our knowledge, urban and rural use of telerehabilitation has not been examined previously. Under both definitions of rurality, encounters and unique patients show an important increase over time, and by year-end 2017, more than half of all patients and encounters were attributed to rural patients (53.7% and 53.9%, respectively). Indeed, the upward trend may have been more pronounced if the rural definition had not changed in FY 2015. Our early VHA stroke patients study on the difference between rural-urban patients and taxonomies showed that the RUCA definition was more likely to reduce the number of rural patients by 8.5% than the early definition used by the VHA.²⁶

It is notable that although the use of tele-delivery of rehabilitation has continually increased, the rate of this increase was steeper from FY 2012 to FY 2014 than FY 2015 to FY 2017. For the programs under consideration in this study, the total number of rural patients/encounters increased throughout the observed periods. However, urban patients and encounters increased through FY 2016 and experienced a slight decrease in FY 2017.

The appearance of a slower rate of increase may be due to a rapid initial rate of increase through early adopters and “crossing the diffusion chasm,” a well-documented process of slower diffusion between the time of invention to penetration that often characterizes the spread of successful telehealth innovations.²⁷ Integrating technology into care delivery innovation requires the integration of technical, clinical, and administrative processes and can take time to scale successfully.²⁸

With an emphasis on increasing access to rehabilitation services, the VHA can expect to see a continuing increase in both the number and the percentage of telerehabilitation rural patients and encounters. The VHA has several telerehabilitation initiatives underway through the VHA’s Physical Medicine and Rehabilitation Telerehabilitation Enterprise Wide Initiative (TREWI) and Rural Veterans Telerehabilitation Initiative. These projects demonstrate the feasibility of this delivery approach and facilitate integration of this modality in clinical workflows. However, to sustain these efforts, facilities will need more infrastructure and personnel resources dedicated to the delivery of services.

In an ongoing evaluation of the TREWI, several factors seem to influence the uptake of the VHA Office of Rural Health TREWI programs. These factors are the presence or absence of a local site champion; the quality of hospital leadership support; the quality of past relationships between telerehabilitation sending sites and receiving sites; barriers to getting a telehealth service agreement in place; the availability of space; administrative know-how on setting up clinics appropriately; time involved to bring on staff; contracting issues; equipment availability and installation; cultural issues in embracing technologic innovation; training burden; hassle factors; and limited funds. Although early adopters may be able to negotiate and push through many of the barriers associated with the diffusion of telerehabilitation, the numerous barriers may slow its larger systemwide diffusion.

Telerehabilitation is a promising mode to deliver care to rural veterans who otherwise may not have access to this type of specialty care. Therefore, the identification of elements that foster telerehabilitation growth in future investigations can assist policy makers and key stakeholders in optimally leveraging program resources for maximal productivity. Future studies investigating the drivers of increases in telerehabilitation growth by rurality are warranted. Furthermore, more research is needed to examine telerehabilitation growth quality of care outcomes (eg, patient and provider satisfaction) to ensure that care is not only timely and accessible, but of high quality.

Conclusion

Disparities between rural and urban veterans compel a mode of expanding delivery of care. The VHA has embraced the use of telehealth modalities to extend its reach of rehabilitation services to veterans with disability and rehabilitation needs. Growth in telerehabilitation rural patient encounters increases access to rehabilitative care, reduces patient and caregiver travel burden, and helps ensure treatment adherence. Telerehabilitation utilization (unique patients and total encounters) is growing more rapidly for rural veterans than for their urban counterparts. Overall, telerehabilitation is filling a gap for rural veterans, as well as veterans in general with challenges in accessibility to health care. In order to make full use of the telerehabilitation services across its health care system, VA health care facilities may need to expand their effort in telerehabilitation dissemination and education among providers and veterans, particularly among providers who are less familiar with telerehabilitation services and among veterans who live in rural or highly rural areas and need special rehabilitation care.