Association Between Bronchiolitis Patient Volume and Continuous Pulse Oximetry Monitoring in 25 Hospitals

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Continuous pulse oximetry monitoring in children with bronchiolitis who don’t require supplemental oxygen is discouraged by practice guidelines and is recognized as a form of medical overuse.1-3 This practice can be associated with negative outcomes, including prolonged length of stay,4-6 increased cost of hospitalization,7 and alarm fatigue among nurses.8 Despite initiatives to reduce continuous pulse oximetry monitoring in stable patients with bronchiolitis,1,2 wide practice variation exists between hospitals.9,10 Previous studies have shown that higher prevalence of inpatient bronchiolitis admissions is associated with decreased utilization of unnecessary interventions.11 However, the relationship between pulse oximetry use and bronchiolitis prevalence has not been studied. The objective of this study is to test the hypothesis that hospital units with lower proportions of patients admitted for bronchiolitis and those with fewer general pediatrics patients relative to subspecialty patients would have higher rates of pulse oximetry overuse.

METHODS

Study Design

We conducted a substudy of the Pediatric Research in Inpatient Settings (PRIS) Network’s Eliminating Monitoring Overuse (EMO) pulse oximetry study,10,12 a 56-hospital cross-sectional study that used direct observation to measure the prevalence of continuous pulse oximetry monitoring in hospitalized infants with bronchiolitis who did not require supplemental oxygen between December 1, 2018, through March 31, 2019. This substudy was not included as part of the original aims of the project and was proposed as a separate analysis during data collection. For US sites, the Institutional Review Board (IRB) at Children’s Hospital of Philadelphia approved the study and served as the central IRB. The Research Ethics Board at University of Calgary also approved the study.

Site Selection

Hospitals with at least 60 observations were eligible for inclusion. Of the 32 hospitals that conducted the minimum observations, 25 agreed to participate (21 free-standing children’s hospitals, 3 children’s hospitals within general hospitals, and 1 community hospital).

Patient Population

The parent study included patients aged 8 weeks through 23 months with a primary diagnosis of bronchiolitis. Patients were included only if they were not receiving supplemental oxygen or nasal cannula flow at the time of data collection. The inclusion and exclusion criteria were for both the parent study and the substudy. Further inclusion and exclusion criteria have been described previously.10,12

Data Collection

In order to ascertain continuous pulse oximetry monitoring status, staff at each hospital performed observational rounds by walking to the bedside of each patient who met inclusion criteria. Additional methodology for the parent study has been published elsewhere.10,12

Bronchiolitis Admission Volume by Unit

Collaborators at each hospital gathered bronchiolitis census data from each unit that admitted patients with bronchiolitis. Units were identified prior to data collection and were characterized at the institution level based on previous local definitions. Each site was responsible for using institution-specific data collection methods for determining bronchiolitis and total admissions on each unit (eg, departmental reports or directly querying admissions data using International Classification of Diseases, Tenth Revision, diagnosis codes for bronchiolitis) over the same period as the parent study. Following data analysis, bronchiolitis admission burden was classified into five categories, based on less than 10%, 10% to less than 20%, 20% to less than 30%, 30% to less than 40%, or 40% or more of total admissions having a primary discharge diagnosis of bronchiolitis during the study period. This categorization allowed investigators to determine whether there was a dose-dependent response among categories.

Unit Composition

Site investigators also completed a survey identifying which patients were admitted to each unit (eg, general pediatrics only, medical subspecialty, surgical). Based on these results, units were further classified into seven types (Appendix Table). For the final analysis, units caring exclusively for general pediatrics patients were compared to all other unit types.

Analysis

Bronchiolitis admission burden and unit composition data were combined with observations of pulse oximetry monitoring use of patients not requiring supplemental oxygen from the parent study. We determined unadjusted observed monitoring proportions for each unit’s bronchiolitis admission burden category across all 25 hospitals. This was calculated as a simple proportion of the total number of observations during which patients were continuously monitored divided by the total number of observations performed within each unit’s admission category. We then calculated unadjusted odds ratios using the 40% and higher bronchiolitis admission burden category as a reference. We calculated similar proportions and odds ratios for the dichotomous unit composition variable. Next, we used mixed-effects logistic regression with a random intercept for each hospital to allow for differences in baseline monitoring rates, which varied widely between hospitals (2% to 92%),10 to calculate adjusted odds ratios for the unit’s admission category and unit’s composition. We also adjusted for the same covariates used in the primary study’s analysis (Table).10

Pulse Oximetry Monitoring by Bronchiolitis Admission Burden Category

RESULTS

We analyzed 2,366 observations of bronchiolitis patients from 25 hospitals. Most observations were concentrated in freestanding children’s hospitals (89%), and 50% were from hospitals with more than 250 pediatric beds. Observations were well distributed among the five categories of admit burden (Table).

In unadjusted regression, the relationship between admission burden and rate of pulse oximetry use did not appear to be dose-dependent, and 95% CIs were wide. We then analyzed the data accounting for baseline differences in hospital monitoring rates and adjusted for the covariates significantly associated with continuous pulse oximetry monitoring in the primary study’s analysis with use of a mixed-effects model. As shown in the Table, low-burden units in which bronchiolitis constituted less than 10% of total admissions had a 2.16-fold increased odds of unnecessary pulse oximetry monitoring compared to high-burden units in which bronchiolitis constituted 40% or more of total admissions (95% CI, 1.27-3.69; P = .01).

In examining the subspecialty unit composition, 596 observations (25.2%) were conducted on units exclusively caring for general pediatrics patients. In the mixed-effects model adjusted for bronchiolitis admission burden and the covariates used in the study’s primary analysis, units exclusively caring for general pediatrics patients did not have significantly different independent odds of pulse oximetry monitoring use compared to units with a mixed patient population (OR 1.01; 95% CI, 0.71-1.45; P = .95) (Appendix Table).

DISCUSSION

In this multicenter observational study of children hospitalized with bronchiolitis not concurrently receiving supplemental oxygen, units that only occasionally cared for bronchiolitis patients appeared to be more likely to overuse continuous pulse oximetry during bronchiolitis hospitalizations.

This finding was not immediately apparent when examining the raw data because of wide hospital-level variation in continuous pulse oximetry monitoring use. However, when the high degree of hospital-level variation in baseline overuse was accounted for with use of a random intercept for each hospital in the mixed-effects model, units that cared for higher proportions of bronchiolitis patients had significantly lower odds of continuous pulse oximetry monitoring use compared to units that cared for these infants infrequently.

As many institutions have subspecialized units to cultivate nursing expertise for care of certain diseases and patient populations, we hypothesized that units caring primarily for children on general pediatrics units would also have lower rates of monitoring overuse compared to mixed units. Interestingly, these units did not perform better, likely because potential cultural factors that might contribute to differences in monitoring are accounted for by bronchiolitis admission burden.

Our findings build on prior literature by demonstrating that unit-level, as well as hospital-level, factors appear to drive overuse in healthcare. A prior single-site retrospective cohort study demonstrated an association between higher prevalence of inpatient bronchiolitis and decreased use of unnecessary interventions such as laboratory and radiographic testing, as well as steroid and antibiotic administration.11 Although study of the relationship between volume and quality is not new to healthcare, to our knowledge, this study is the first to examine the relationship between pulse oximetry overuse in bronchiolitis and unit-level factors like admission burden and subspecialty composition.

There are several limitations. First, because the study population included only children not receiving supplemental oxygen, both the parent study and this substudy assumed that all observed use of pulse oximetry monitoring was overuse. In some cases, however, there may have been other compelling clinical reasons, institutional policies, or differences in pulse oximetry availability that were not captured during data collection or in our adjusted model. Second, hospitals used convenience sampling. It is possible this resulted in samples that were not representative of each unit’s underlying patient population or monitoring practice. In addition, not all of the 32 eligible sites were able to provide data related to hospital admissions at the unit level and thus are not included in our analysis. This remains a potential source of hospital-level selection bias.

CONCLUSION

These findings demonstrate that high bronchiolitis admission burden correlates with lower rates of unnecessary pulse oximetry monitoring in bronchiolitis. We speculate that these outcomes might reflect differing degrees of nursing comfort, expertise, and unit-level norms in caring for bronchiolitis patients, although our study was not designed to establish underlying causes. Identification of operating principles that underpin low pulse oximetry monitoring on high-burden units will provide guidance for decreasing unnecessary monitoring and will inform future studies seeking ways to discourage continuous pulse oximetry monitoring in low-risk infants. Given the institutional variation in monitoring rates, future studies examining both institution-wide and unit-level interventions will be necessary to decrease unnecessary pulse oximetry monitoring in bronchiolitis. Furthermore, these findings may be relevant to studying care quality in other disease processes, with bronchiolitis serving as a model illness for overuse.

Acknowledgments

The authors acknowledge the National Heart, Lung, and Blood Institute of the National Institutes of Health scientists who contributed their expertise to this project as part of the U01 Cooperative Agreement funding mechanism as federal employees conducting their official job duties: Lora Reineck, MD, MS, Karen Bienstock, MS, and Cheryl Boyce, PhD. The authors thank the executive council of the Pediatric Research in Inpatient Settings Network for their contributions to the early scientific development of this project. The network assessed a Collaborative Support Fee for access to the hospitals and support of this project.

The authors thank the PRIS Network collaborators for their major contributions to data collection (see Appendix).

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References

1. Ralston SL, Lieberthal AS, Meissner HC, et al. Clinical practice guideline: the diagnosis, management, and prevention of bronchiolitis. Pediatrics. 2014;134(5):e1474-e1502. https://doi.org/10.1542/peds.2014-2742
2. Quinonez RA, Garber MD, Schroeder AR, et al. Choosing wisely in pediatric hospital medicine: Five opportunities for improved healthcare value. J Hosp Med. 2013;8(9):479-485. https://doi.org/10.1002/jhm.2064
3. Quinonez RA, Coon ER, Schroeder AR, Moyer VA. When technology creates uncertainty: pulse oximetry and overdiagnosis of hypoxaemia in bronchiolitis. BMJ. 2017;358:j3850. https://doi.org/10.1136/bmj.j3850
4. Cunningham S, Rodriguez A, Adams T, et al; Bronchiolitis of Infancy Discharge Study (BIDS) group. Oxygen saturation targets in infants with bronchiolitis (BIDS): a double-blind, randomised, equivalence trial. Lancet. 2015;386(9998):1041-1048. https://doi.org/10.1016/s0140-6736(15)00163-4
5. Schroeder AR, Marmor AK, Pantell RH, Newman TB. Impact of pulse oximetry and oxygen therapy on length of stay in bronchiolitis hospitalizations. Arch Pediatr Adolesc Med. 2004;158(6):527-530. https://doi.org/10.1001/archpedi.158.6.527
6. Cunningham S, McMurray A. Observational study of two oxygen saturation targets for discharge in bronchiolitis. Arch Dis Child. 2012;97(4):361-363. https://doi.org/10.1136/adc.2010.205211
7. Cunningham S, Rodriguez A, Boyd KA, McIntosh E, Lewis SC; BIDS Collaborators Group. Bronchiolitis of Infancy Discharge Study (BIDS): a multicentre, parallel-group, double-blind, randomised controlled, equivalence trial with economic evaluation. Health Technol Assess. 2015;19(71):i-172. https://doi.org/10.3310/hta19710
8. Bonafide CP, Lin R, Zander M, et al. Association between exposure to nonactionable physiologic monitor alarms and response time in a children’s hospital. J Hosp Med. 2015;10(6):345-351. https://doi.org/10.1002/jhm.2331
9. Ralston SL, Garber MD, Rice-Conboy E, et al. A multicenter collaborative to reduce unnecessary care in inpatient bronchiolitis. Pediatrics. 2016;137(1):e20150851. https://doi.org/10.1542/peds.2015-0851
10. Bonafide CP, Xiao R, Brady PW, et al; for the Pediatric Research in Inpatient Settings (PRIS) Network. Prevalence of continuous pulse oximetry monitoring in hospitalized children with bronchiolitis not requiring supplemental oxygen. JAMA. 2020;323(15):1467-1477. https://doi.org/10.1001/jama.2020.2998
11. Van Cleve WC, Christakis DA. Unnecessary care for bronchiolitis decreases with increasing inpatient prevalence of bronchiolitis. Pediatrics. 2011;128(5):e1106-e1112. https://doi.org/10.1542/peds.2011-0655
12. Rasooly IR, Beidas RS, Wolk CB, et al. Measuring overuse of continuous pulse oximetry in bronchiolitis and developing strategies for large-scale deimplementation: study protocol for a feasibility trial. Pilot Feasibility Stud. 2019;5(1):68. https://doi.org/10.1186/s40814-019-0453-2

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1Division of General Pediatrics, Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts; 2Harvard Medical School, Boston, Massachusetts; 3Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, Massachusetts; 4Section of Pediatric Hospital Medicine, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 5Center for Pediatric Clinical Effectiveness, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 6Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.

Disclosures

The authors have no conflicts of interest relevant to this article to disclose.

Funding

Research reported in this publication was supported by a Cooperative Agreement from the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number U01HL143475 (Dr Bonafide, Principal investigator). The funding organization had no role in the design of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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1Division of General Pediatrics, Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts; 2Harvard Medical School, Boston, Massachusetts; 3Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, Massachusetts; 4Section of Pediatric Hospital Medicine, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 5Center for Pediatric Clinical Effectiveness, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 6Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.

Disclosures

The authors have no conflicts of interest relevant to this article to disclose.

Funding

Research reported in this publication was supported by a Cooperative Agreement from the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number U01HL143475 (Dr Bonafide, Principal investigator). The funding organization had no role in the design of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Author and Disclosure Information

1Division of General Pediatrics, Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts; 2Harvard Medical School, Boston, Massachusetts; 3Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, Massachusetts; 4Section of Pediatric Hospital Medicine, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 5Center for Pediatric Clinical Effectiveness, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 6Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.

Disclosures

The authors have no conflicts of interest relevant to this article to disclose.

Funding

Research reported in this publication was supported by a Cooperative Agreement from the National Heart, Lung, and Blood Institute of the National Institutes of Health under award number U01HL143475 (Dr Bonafide, Principal investigator). The funding organization had no role in the design of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Related Articles

Continuous pulse oximetry monitoring in children with bronchiolitis who don’t require supplemental oxygen is discouraged by practice guidelines and is recognized as a form of medical overuse.1-3 This practice can be associated with negative outcomes, including prolonged length of stay,4-6 increased cost of hospitalization,7 and alarm fatigue among nurses.8 Despite initiatives to reduce continuous pulse oximetry monitoring in stable patients with bronchiolitis,1,2 wide practice variation exists between hospitals.9,10 Previous studies have shown that higher prevalence of inpatient bronchiolitis admissions is associated with decreased utilization of unnecessary interventions.11 However, the relationship between pulse oximetry use and bronchiolitis prevalence has not been studied. The objective of this study is to test the hypothesis that hospital units with lower proportions of patients admitted for bronchiolitis and those with fewer general pediatrics patients relative to subspecialty patients would have higher rates of pulse oximetry overuse.

METHODS

Study Design

We conducted a substudy of the Pediatric Research in Inpatient Settings (PRIS) Network’s Eliminating Monitoring Overuse (EMO) pulse oximetry study,10,12 a 56-hospital cross-sectional study that used direct observation to measure the prevalence of continuous pulse oximetry monitoring in hospitalized infants with bronchiolitis who did not require supplemental oxygen between December 1, 2018, through March 31, 2019. This substudy was not included as part of the original aims of the project and was proposed as a separate analysis during data collection. For US sites, the Institutional Review Board (IRB) at Children’s Hospital of Philadelphia approved the study and served as the central IRB. The Research Ethics Board at University of Calgary also approved the study.

Site Selection

Hospitals with at least 60 observations were eligible for inclusion. Of the 32 hospitals that conducted the minimum observations, 25 agreed to participate (21 free-standing children’s hospitals, 3 children’s hospitals within general hospitals, and 1 community hospital).

Patient Population

The parent study included patients aged 8 weeks through 23 months with a primary diagnosis of bronchiolitis. Patients were included only if they were not receiving supplemental oxygen or nasal cannula flow at the time of data collection. The inclusion and exclusion criteria were for both the parent study and the substudy. Further inclusion and exclusion criteria have been described previously.10,12

Data Collection

In order to ascertain continuous pulse oximetry monitoring status, staff at each hospital performed observational rounds by walking to the bedside of each patient who met inclusion criteria. Additional methodology for the parent study has been published elsewhere.10,12

Bronchiolitis Admission Volume by Unit

Collaborators at each hospital gathered bronchiolitis census data from each unit that admitted patients with bronchiolitis. Units were identified prior to data collection and were characterized at the institution level based on previous local definitions. Each site was responsible for using institution-specific data collection methods for determining bronchiolitis and total admissions on each unit (eg, departmental reports or directly querying admissions data using International Classification of Diseases, Tenth Revision, diagnosis codes for bronchiolitis) over the same period as the parent study. Following data analysis, bronchiolitis admission burden was classified into five categories, based on less than 10%, 10% to less than 20%, 20% to less than 30%, 30% to less than 40%, or 40% or more of total admissions having a primary discharge diagnosis of bronchiolitis during the study period. This categorization allowed investigators to determine whether there was a dose-dependent response among categories.

Unit Composition

Site investigators also completed a survey identifying which patients were admitted to each unit (eg, general pediatrics only, medical subspecialty, surgical). Based on these results, units were further classified into seven types (Appendix Table). For the final analysis, units caring exclusively for general pediatrics patients were compared to all other unit types.

Analysis

Bronchiolitis admission burden and unit composition data were combined with observations of pulse oximetry monitoring use of patients not requiring supplemental oxygen from the parent study. We determined unadjusted observed monitoring proportions for each unit’s bronchiolitis admission burden category across all 25 hospitals. This was calculated as a simple proportion of the total number of observations during which patients were continuously monitored divided by the total number of observations performed within each unit’s admission category. We then calculated unadjusted odds ratios using the 40% and higher bronchiolitis admission burden category as a reference. We calculated similar proportions and odds ratios for the dichotomous unit composition variable. Next, we used mixed-effects logistic regression with a random intercept for each hospital to allow for differences in baseline monitoring rates, which varied widely between hospitals (2% to 92%),10 to calculate adjusted odds ratios for the unit’s admission category and unit’s composition. We also adjusted for the same covariates used in the primary study’s analysis (Table).10

Pulse Oximetry Monitoring by Bronchiolitis Admission Burden Category

RESULTS

We analyzed 2,366 observations of bronchiolitis patients from 25 hospitals. Most observations were concentrated in freestanding children’s hospitals (89%), and 50% were from hospitals with more than 250 pediatric beds. Observations were well distributed among the five categories of admit burden (Table).

In unadjusted regression, the relationship between admission burden and rate of pulse oximetry use did not appear to be dose-dependent, and 95% CIs were wide. We then analyzed the data accounting for baseline differences in hospital monitoring rates and adjusted for the covariates significantly associated with continuous pulse oximetry monitoring in the primary study’s analysis with use of a mixed-effects model. As shown in the Table, low-burden units in which bronchiolitis constituted less than 10% of total admissions had a 2.16-fold increased odds of unnecessary pulse oximetry monitoring compared to high-burden units in which bronchiolitis constituted 40% or more of total admissions (95% CI, 1.27-3.69; P = .01).

In examining the subspecialty unit composition, 596 observations (25.2%) were conducted on units exclusively caring for general pediatrics patients. In the mixed-effects model adjusted for bronchiolitis admission burden and the covariates used in the study’s primary analysis, units exclusively caring for general pediatrics patients did not have significantly different independent odds of pulse oximetry monitoring use compared to units with a mixed patient population (OR 1.01; 95% CI, 0.71-1.45; P = .95) (Appendix Table).

DISCUSSION

In this multicenter observational study of children hospitalized with bronchiolitis not concurrently receiving supplemental oxygen, units that only occasionally cared for bronchiolitis patients appeared to be more likely to overuse continuous pulse oximetry during bronchiolitis hospitalizations.

This finding was not immediately apparent when examining the raw data because of wide hospital-level variation in continuous pulse oximetry monitoring use. However, when the high degree of hospital-level variation in baseline overuse was accounted for with use of a random intercept for each hospital in the mixed-effects model, units that cared for higher proportions of bronchiolitis patients had significantly lower odds of continuous pulse oximetry monitoring use compared to units that cared for these infants infrequently.

As many institutions have subspecialized units to cultivate nursing expertise for care of certain diseases and patient populations, we hypothesized that units caring primarily for children on general pediatrics units would also have lower rates of monitoring overuse compared to mixed units. Interestingly, these units did not perform better, likely because potential cultural factors that might contribute to differences in monitoring are accounted for by bronchiolitis admission burden.

Our findings build on prior literature by demonstrating that unit-level, as well as hospital-level, factors appear to drive overuse in healthcare. A prior single-site retrospective cohort study demonstrated an association between higher prevalence of inpatient bronchiolitis and decreased use of unnecessary interventions such as laboratory and radiographic testing, as well as steroid and antibiotic administration.11 Although study of the relationship between volume and quality is not new to healthcare, to our knowledge, this study is the first to examine the relationship between pulse oximetry overuse in bronchiolitis and unit-level factors like admission burden and subspecialty composition.

There are several limitations. First, because the study population included only children not receiving supplemental oxygen, both the parent study and this substudy assumed that all observed use of pulse oximetry monitoring was overuse. In some cases, however, there may have been other compelling clinical reasons, institutional policies, or differences in pulse oximetry availability that were not captured during data collection or in our adjusted model. Second, hospitals used convenience sampling. It is possible this resulted in samples that were not representative of each unit’s underlying patient population or monitoring practice. In addition, not all of the 32 eligible sites were able to provide data related to hospital admissions at the unit level and thus are not included in our analysis. This remains a potential source of hospital-level selection bias.

CONCLUSION

These findings demonstrate that high bronchiolitis admission burden correlates with lower rates of unnecessary pulse oximetry monitoring in bronchiolitis. We speculate that these outcomes might reflect differing degrees of nursing comfort, expertise, and unit-level norms in caring for bronchiolitis patients, although our study was not designed to establish underlying causes. Identification of operating principles that underpin low pulse oximetry monitoring on high-burden units will provide guidance for decreasing unnecessary monitoring and will inform future studies seeking ways to discourage continuous pulse oximetry monitoring in low-risk infants. Given the institutional variation in monitoring rates, future studies examining both institution-wide and unit-level interventions will be necessary to decrease unnecessary pulse oximetry monitoring in bronchiolitis. Furthermore, these findings may be relevant to studying care quality in other disease processes, with bronchiolitis serving as a model illness for overuse.

Acknowledgments

The authors acknowledge the National Heart, Lung, and Blood Institute of the National Institutes of Health scientists who contributed their expertise to this project as part of the U01 Cooperative Agreement funding mechanism as federal employees conducting their official job duties: Lora Reineck, MD, MS, Karen Bienstock, MS, and Cheryl Boyce, PhD. The authors thank the executive council of the Pediatric Research in Inpatient Settings Network for their contributions to the early scientific development of this project. The network assessed a Collaborative Support Fee for access to the hospitals and support of this project.

The authors thank the PRIS Network collaborators for their major contributions to data collection (see Appendix).

Continuous pulse oximetry monitoring in children with bronchiolitis who don’t require supplemental oxygen is discouraged by practice guidelines and is recognized as a form of medical overuse.1-3 This practice can be associated with negative outcomes, including prolonged length of stay,4-6 increased cost of hospitalization,7 and alarm fatigue among nurses.8 Despite initiatives to reduce continuous pulse oximetry monitoring in stable patients with bronchiolitis,1,2 wide practice variation exists between hospitals.9,10 Previous studies have shown that higher prevalence of inpatient bronchiolitis admissions is associated with decreased utilization of unnecessary interventions.11 However, the relationship between pulse oximetry use and bronchiolitis prevalence has not been studied. The objective of this study is to test the hypothesis that hospital units with lower proportions of patients admitted for bronchiolitis and those with fewer general pediatrics patients relative to subspecialty patients would have higher rates of pulse oximetry overuse.

METHODS

Study Design

We conducted a substudy of the Pediatric Research in Inpatient Settings (PRIS) Network’s Eliminating Monitoring Overuse (EMO) pulse oximetry study,10,12 a 56-hospital cross-sectional study that used direct observation to measure the prevalence of continuous pulse oximetry monitoring in hospitalized infants with bronchiolitis who did not require supplemental oxygen between December 1, 2018, through March 31, 2019. This substudy was not included as part of the original aims of the project and was proposed as a separate analysis during data collection. For US sites, the Institutional Review Board (IRB) at Children’s Hospital of Philadelphia approved the study and served as the central IRB. The Research Ethics Board at University of Calgary also approved the study.

Site Selection

Hospitals with at least 60 observations were eligible for inclusion. Of the 32 hospitals that conducted the minimum observations, 25 agreed to participate (21 free-standing children’s hospitals, 3 children’s hospitals within general hospitals, and 1 community hospital).

Patient Population

The parent study included patients aged 8 weeks through 23 months with a primary diagnosis of bronchiolitis. Patients were included only if they were not receiving supplemental oxygen or nasal cannula flow at the time of data collection. The inclusion and exclusion criteria were for both the parent study and the substudy. Further inclusion and exclusion criteria have been described previously.10,12

Data Collection

In order to ascertain continuous pulse oximetry monitoring status, staff at each hospital performed observational rounds by walking to the bedside of each patient who met inclusion criteria. Additional methodology for the parent study has been published elsewhere.10,12

Bronchiolitis Admission Volume by Unit

Collaborators at each hospital gathered bronchiolitis census data from each unit that admitted patients with bronchiolitis. Units were identified prior to data collection and were characterized at the institution level based on previous local definitions. Each site was responsible for using institution-specific data collection methods for determining bronchiolitis and total admissions on each unit (eg, departmental reports or directly querying admissions data using International Classification of Diseases, Tenth Revision, diagnosis codes for bronchiolitis) over the same period as the parent study. Following data analysis, bronchiolitis admission burden was classified into five categories, based on less than 10%, 10% to less than 20%, 20% to less than 30%, 30% to less than 40%, or 40% or more of total admissions having a primary discharge diagnosis of bronchiolitis during the study period. This categorization allowed investigators to determine whether there was a dose-dependent response among categories.

Unit Composition

Site investigators also completed a survey identifying which patients were admitted to each unit (eg, general pediatrics only, medical subspecialty, surgical). Based on these results, units were further classified into seven types (Appendix Table). For the final analysis, units caring exclusively for general pediatrics patients were compared to all other unit types.

Analysis

Bronchiolitis admission burden and unit composition data were combined with observations of pulse oximetry monitoring use of patients not requiring supplemental oxygen from the parent study. We determined unadjusted observed monitoring proportions for each unit’s bronchiolitis admission burden category across all 25 hospitals. This was calculated as a simple proportion of the total number of observations during which patients were continuously monitored divided by the total number of observations performed within each unit’s admission category. We then calculated unadjusted odds ratios using the 40% and higher bronchiolitis admission burden category as a reference. We calculated similar proportions and odds ratios for the dichotomous unit composition variable. Next, we used mixed-effects logistic regression with a random intercept for each hospital to allow for differences in baseline monitoring rates, which varied widely between hospitals (2% to 92%),10 to calculate adjusted odds ratios for the unit’s admission category and unit’s composition. We also adjusted for the same covariates used in the primary study’s analysis (Table).10

Pulse Oximetry Monitoring by Bronchiolitis Admission Burden Category

RESULTS

We analyzed 2,366 observations of bronchiolitis patients from 25 hospitals. Most observations were concentrated in freestanding children’s hospitals (89%), and 50% were from hospitals with more than 250 pediatric beds. Observations were well distributed among the five categories of admit burden (Table).

In unadjusted regression, the relationship between admission burden and rate of pulse oximetry use did not appear to be dose-dependent, and 95% CIs were wide. We then analyzed the data accounting for baseline differences in hospital monitoring rates and adjusted for the covariates significantly associated with continuous pulse oximetry monitoring in the primary study’s analysis with use of a mixed-effects model. As shown in the Table, low-burden units in which bronchiolitis constituted less than 10% of total admissions had a 2.16-fold increased odds of unnecessary pulse oximetry monitoring compared to high-burden units in which bronchiolitis constituted 40% or more of total admissions (95% CI, 1.27-3.69; P = .01).

In examining the subspecialty unit composition, 596 observations (25.2%) were conducted on units exclusively caring for general pediatrics patients. In the mixed-effects model adjusted for bronchiolitis admission burden and the covariates used in the study’s primary analysis, units exclusively caring for general pediatrics patients did not have significantly different independent odds of pulse oximetry monitoring use compared to units with a mixed patient population (OR 1.01; 95% CI, 0.71-1.45; P = .95) (Appendix Table).

DISCUSSION

In this multicenter observational study of children hospitalized with bronchiolitis not concurrently receiving supplemental oxygen, units that only occasionally cared for bronchiolitis patients appeared to be more likely to overuse continuous pulse oximetry during bronchiolitis hospitalizations.

This finding was not immediately apparent when examining the raw data because of wide hospital-level variation in continuous pulse oximetry monitoring use. However, when the high degree of hospital-level variation in baseline overuse was accounted for with use of a random intercept for each hospital in the mixed-effects model, units that cared for higher proportions of bronchiolitis patients had significantly lower odds of continuous pulse oximetry monitoring use compared to units that cared for these infants infrequently.

As many institutions have subspecialized units to cultivate nursing expertise for care of certain diseases and patient populations, we hypothesized that units caring primarily for children on general pediatrics units would also have lower rates of monitoring overuse compared to mixed units. Interestingly, these units did not perform better, likely because potential cultural factors that might contribute to differences in monitoring are accounted for by bronchiolitis admission burden.

Our findings build on prior literature by demonstrating that unit-level, as well as hospital-level, factors appear to drive overuse in healthcare. A prior single-site retrospective cohort study demonstrated an association between higher prevalence of inpatient bronchiolitis and decreased use of unnecessary interventions such as laboratory and radiographic testing, as well as steroid and antibiotic administration.11 Although study of the relationship between volume and quality is not new to healthcare, to our knowledge, this study is the first to examine the relationship between pulse oximetry overuse in bronchiolitis and unit-level factors like admission burden and subspecialty composition.

There are several limitations. First, because the study population included only children not receiving supplemental oxygen, both the parent study and this substudy assumed that all observed use of pulse oximetry monitoring was overuse. In some cases, however, there may have been other compelling clinical reasons, institutional policies, or differences in pulse oximetry availability that were not captured during data collection or in our adjusted model. Second, hospitals used convenience sampling. It is possible this resulted in samples that were not representative of each unit’s underlying patient population or monitoring practice. In addition, not all of the 32 eligible sites were able to provide data related to hospital admissions at the unit level and thus are not included in our analysis. This remains a potential source of hospital-level selection bias.

CONCLUSION

These findings demonstrate that high bronchiolitis admission burden correlates with lower rates of unnecessary pulse oximetry monitoring in bronchiolitis. We speculate that these outcomes might reflect differing degrees of nursing comfort, expertise, and unit-level norms in caring for bronchiolitis patients, although our study was not designed to establish underlying causes. Identification of operating principles that underpin low pulse oximetry monitoring on high-burden units will provide guidance for decreasing unnecessary monitoring and will inform future studies seeking ways to discourage continuous pulse oximetry monitoring in low-risk infants. Given the institutional variation in monitoring rates, future studies examining both institution-wide and unit-level interventions will be necessary to decrease unnecessary pulse oximetry monitoring in bronchiolitis. Furthermore, these findings may be relevant to studying care quality in other disease processes, with bronchiolitis serving as a model illness for overuse.

Acknowledgments

The authors acknowledge the National Heart, Lung, and Blood Institute of the National Institutes of Health scientists who contributed their expertise to this project as part of the U01 Cooperative Agreement funding mechanism as federal employees conducting their official job duties: Lora Reineck, MD, MS, Karen Bienstock, MS, and Cheryl Boyce, PhD. The authors thank the executive council of the Pediatric Research in Inpatient Settings Network for their contributions to the early scientific development of this project. The network assessed a Collaborative Support Fee for access to the hospitals and support of this project.

The authors thank the PRIS Network collaborators for their major contributions to data collection (see Appendix).

References

1. Ralston SL, Lieberthal AS, Meissner HC, et al. Clinical practice guideline: the diagnosis, management, and prevention of bronchiolitis. Pediatrics. 2014;134(5):e1474-e1502. https://doi.org/10.1542/peds.2014-2742
2. Quinonez RA, Garber MD, Schroeder AR, et al. Choosing wisely in pediatric hospital medicine: Five opportunities for improved healthcare value. J Hosp Med. 2013;8(9):479-485. https://doi.org/10.1002/jhm.2064
3. Quinonez RA, Coon ER, Schroeder AR, Moyer VA. When technology creates uncertainty: pulse oximetry and overdiagnosis of hypoxaemia in bronchiolitis. BMJ. 2017;358:j3850. https://doi.org/10.1136/bmj.j3850
4. Cunningham S, Rodriguez A, Adams T, et al; Bronchiolitis of Infancy Discharge Study (BIDS) group. Oxygen saturation targets in infants with bronchiolitis (BIDS): a double-blind, randomised, equivalence trial. Lancet. 2015;386(9998):1041-1048. https://doi.org/10.1016/s0140-6736(15)00163-4
5. Schroeder AR, Marmor AK, Pantell RH, Newman TB. Impact of pulse oximetry and oxygen therapy on length of stay in bronchiolitis hospitalizations. Arch Pediatr Adolesc Med. 2004;158(6):527-530. https://doi.org/10.1001/archpedi.158.6.527
6. Cunningham S, McMurray A. Observational study of two oxygen saturation targets for discharge in bronchiolitis. Arch Dis Child. 2012;97(4):361-363. https://doi.org/10.1136/adc.2010.205211
7. Cunningham S, Rodriguez A, Boyd KA, McIntosh E, Lewis SC; BIDS Collaborators Group. Bronchiolitis of Infancy Discharge Study (BIDS): a multicentre, parallel-group, double-blind, randomised controlled, equivalence trial with economic evaluation. Health Technol Assess. 2015;19(71):i-172. https://doi.org/10.3310/hta19710
8. Bonafide CP, Lin R, Zander M, et al. Association between exposure to nonactionable physiologic monitor alarms and response time in a children’s hospital. J Hosp Med. 2015;10(6):345-351. https://doi.org/10.1002/jhm.2331
9. Ralston SL, Garber MD, Rice-Conboy E, et al. A multicenter collaborative to reduce unnecessary care in inpatient bronchiolitis. Pediatrics. 2016;137(1):e20150851. https://doi.org/10.1542/peds.2015-0851
10. Bonafide CP, Xiao R, Brady PW, et al; for the Pediatric Research in Inpatient Settings (PRIS) Network. Prevalence of continuous pulse oximetry monitoring in hospitalized children with bronchiolitis not requiring supplemental oxygen. JAMA. 2020;323(15):1467-1477. https://doi.org/10.1001/jama.2020.2998
11. Van Cleve WC, Christakis DA. Unnecessary care for bronchiolitis decreases with increasing inpatient prevalence of bronchiolitis. Pediatrics. 2011;128(5):e1106-e1112. https://doi.org/10.1542/peds.2011-0655
12. Rasooly IR, Beidas RS, Wolk CB, et al. Measuring overuse of continuous pulse oximetry in bronchiolitis and developing strategies for large-scale deimplementation: study protocol for a feasibility trial. Pilot Feasibility Stud. 2019;5(1):68. https://doi.org/10.1186/s40814-019-0453-2

References

1. Ralston SL, Lieberthal AS, Meissner HC, et al. Clinical practice guideline: the diagnosis, management, and prevention of bronchiolitis. Pediatrics. 2014;134(5):e1474-e1502. https://doi.org/10.1542/peds.2014-2742
2. Quinonez RA, Garber MD, Schroeder AR, et al. Choosing wisely in pediatric hospital medicine: Five opportunities for improved healthcare value. J Hosp Med. 2013;8(9):479-485. https://doi.org/10.1002/jhm.2064
3. Quinonez RA, Coon ER, Schroeder AR, Moyer VA. When technology creates uncertainty: pulse oximetry and overdiagnosis of hypoxaemia in bronchiolitis. BMJ. 2017;358:j3850. https://doi.org/10.1136/bmj.j3850
4. Cunningham S, Rodriguez A, Adams T, et al; Bronchiolitis of Infancy Discharge Study (BIDS) group. Oxygen saturation targets in infants with bronchiolitis (BIDS): a double-blind, randomised, equivalence trial. Lancet. 2015;386(9998):1041-1048. https://doi.org/10.1016/s0140-6736(15)00163-4
5. Schroeder AR, Marmor AK, Pantell RH, Newman TB. Impact of pulse oximetry and oxygen therapy on length of stay in bronchiolitis hospitalizations. Arch Pediatr Adolesc Med. 2004;158(6):527-530. https://doi.org/10.1001/archpedi.158.6.527
6. Cunningham S, McMurray A. Observational study of two oxygen saturation targets for discharge in bronchiolitis. Arch Dis Child. 2012;97(4):361-363. https://doi.org/10.1136/adc.2010.205211
7. Cunningham S, Rodriguez A, Boyd KA, McIntosh E, Lewis SC; BIDS Collaborators Group. Bronchiolitis of Infancy Discharge Study (BIDS): a multicentre, parallel-group, double-blind, randomised controlled, equivalence trial with economic evaluation. Health Technol Assess. 2015;19(71):i-172. https://doi.org/10.3310/hta19710
8. Bonafide CP, Lin R, Zander M, et al. Association between exposure to nonactionable physiologic monitor alarms and response time in a children’s hospital. J Hosp Med. 2015;10(6):345-351. https://doi.org/10.1002/jhm.2331
9. Ralston SL, Garber MD, Rice-Conboy E, et al. A multicenter collaborative to reduce unnecessary care in inpatient bronchiolitis. Pediatrics. 2016;137(1):e20150851. https://doi.org/10.1542/peds.2015-0851
10. Bonafide CP, Xiao R, Brady PW, et al; for the Pediatric Research in Inpatient Settings (PRIS) Network. Prevalence of continuous pulse oximetry monitoring in hospitalized children with bronchiolitis not requiring supplemental oxygen. JAMA. 2020;323(15):1467-1477. https://doi.org/10.1001/jama.2020.2998
11. Van Cleve WC, Christakis DA. Unnecessary care for bronchiolitis decreases with increasing inpatient prevalence of bronchiolitis. Pediatrics. 2011;128(5):e1106-e1112. https://doi.org/10.1542/peds.2011-0655
12. Rasooly IR, Beidas RS, Wolk CB, et al. Measuring overuse of continuous pulse oximetry in bronchiolitis and developing strategies for large-scale deimplementation: study protocol for a feasibility trial. Pilot Feasibility Stud. 2019;5(1):68. https://doi.org/10.1186/s40814-019-0453-2

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Validity of Continuous Pulse Oximetry Orders for Identification of Actual Monitoring Status in Bronchiolitis

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As part of improvement collaboratives that aimed to reduce overuse of continuous pulse oximetry in children hospitalized with bronchiolitis, researchers used the presence of an active order for it as a proxy for the actual use of such monitoring.1,2 With use of this proxy, investigators on a national study documented a high burden of continuous oximetry overuse (86.5% before quality improvement interventions and 45.5% after),1 but the validity of orders in representing actual monitoring practice is unknown. If the presence of an active pulse oximetry order accurately identifies infants on monitors, electronic health record data could inform epidemiologic estimates of monitoring overuse and measure the success of quality improvement and deimplementation interventions. Alternatively, if nurses commonly begin and/or discontinue pulse oximetry without updated orders, a pulse oximetry order would not be an accurate proxy, and additional data capture methods (eg, bedside observation or data capture from bedside monitors) would be needed.

Understanding the validity of orders for detection of actual use is critical because continuous pulse oximetry monitoring is considered an overused practice in pediatric acute viral bronchiolitis,3 and national guidelines recommend against its use in low-risk hospitalized children.4,5 Continuous monitoring may identify trivial, self-resolving oxygen desaturation and its use is not associated with improved outcomes.6-9 When self-resolving desaturations are treated with additional supplemental oxygen, hospital stays may be unnecessarily prolonged.10 In order to reduce unnecessary continuous pulse oximetry use, measurement of the extent of the overused practice is necessary. In this 56-hospital study,11 we aimed to determine the validity of using active continuous pulse oximetry orders instead of bedside observation of actual monitor use.

METHODS

Design

In this multicenter, repeated cross-sectional study, investigators used direct bedside observation to determine continuous pulse oximetry monitor use and then assessed whether an active continuous monitoring order was present in the electronic health record. The study took place during one bronchiolitis season, December 1, 2018, through March 31, 2019.

Setting and Patients

Investigators at 56 freestanding children’s hospitals, children’s hospitals within general hospitals, and community hospitals in the Pediatric Research in Inpatient Settings (PRIS) Network collected data on infants aged 8 weeks to 23 months who were hospitalized with bronchiolitis. As this work was a substudy of the larger Eliminating Monitor Overuse study, only infants not currently receiving supplemental oxygen were included.11 Investigators observed eligible infants outside of the intensive care unit on general hospital medicine units. We excluded infants born premature (documented prematurity of <28 weeks’ gestation or documented “premature” without a gestational age listed), as well as those with a home oxygen requirement, cyanotic congenital heart disease, pulmonary hypertension, tracheostomy, primary neuromuscular disease, immunodeficiency, or cancer.

Data Collection

Investigators used the electronic health record to identify eligible infants. Investigators entered patient rooms to confirm the infant was not on supplemental oxygen (hence confirming eligibility for the study) and determine if continuous pulse oximetry was actively in use by examining the monitor display for a pulse oximetry waveform. Investigators then confirmed if active orders for pulse oximetry were present in the patient’s chart. Per study design, site investigators aimed to observe approximately half of eligible infants during the day (10 am to 5 pm) and the other half during the night (11 pm to 7 am).

Analysis

We excluded patients with conditional orders (eg, monitored only when certain conditions exist, such as when asleep) because of the time-varying and wide range of conditions that could be specified. Furthermore, conditional orders would not be useful as proxies to measure oximetry use because investigators would still need additional data (eg, bedside observation) to determine current monitoring status.

We calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of active orders using the reference standard of direct bedside observation, as well as corresponding 95% CIs that accounted for within-hospital clustering. We calculated these test characteristics overall and as stratified across four age groups: 8 weeks to 5 months, 6 months to 11 months, 12 months to 17 months, and 18 months to 23 months. We also calculated the test characteristics for each hospital. We decided a priori that a PPV and NPV of 80% would represent a reasonable threshold to use active orders as a proxy in multicenter research. For hospital-level analyses we included only hospitals with 60 or more total observations and more than 15 observations with active orders for PPV and more than 15 observations without active orders for NPV. We used Stata (StataCorp LLC, College Station, Texas) version 15.1 for analysis.

For US sites, the Institutional Review Board (IRB) at Children’s Hospital of Philadelphia approved the study as the single reviewing IRB, and the remaining US sites established reliance agreements with the reviewing IRB. Research Ethics Boards at the Canadian sites (University of Calgary and The Hospital for Sick Children) also reviewed and approved the study. All sites granted waivers of consent, assent, parental permission, and HIPAA authorization.

RESULTS

Investigators completed 3,612 observations in 56 hospitals. This included 33 freestanding children’s hospitals, 14 hospitals within large general hospitals, and 9 community hospitals. Of 3,612 completed observations, on 631 occasions (17%) patients had conditional orders (eg, continuous monitoring only when sleeping) and were excluded from further analysis.

Most pulse oximetry–monitored infants did not have an active monitoring order (670 out of 1,309; sensitivity of 49%). Test characteristics, stratified by age group, are presented in the Table. Across all observations, the overall PPV was 77% (95% CI, 72-82), and the overall NPV was 69% (95% CI, 61-77). Variation of all test characteristics across age group was small (eg, the sensitivity ranged from 43% to 51%).

Test Characteristics of the Relationship Between Active Orders and Actual Pulse Oximetry Monitoring, Both Overall and as Stratified by Age

With inclusion of only those hospitals with sufficient observations, hospital-level variation in the PPV and NPV of using active orders was substantial (PPV range of 48% to 96% and NPV range of 30% to 98%). Only two hospitals had both a PPV and NPV for using monitor orders that exceeded the 80% threshold.

DISCUSSION

Active continuous pulse oximetry orders did not accurately represent actual monitoring status in this study. Monitoring orders alone frequently misrepresent true monitoring status and, as such, should be interpreted with caution in research or quality improvement activities. If more valid estimates of monitoring use and overuse are needed, potential measurement options include direct observation, as used in our study, as well as the use of more complex data streams such as the output of monitoring devices or pulse oximetry data in the electronic health record. In only two of the hospitals, using active continuous monitoring orders was a reasonable proxy for detecting actual monitor use. Monitoring orders could potentially be validly used for deimplementation efforts at those centers; other hospitals could consider targeted improvement efforts (eg, morning huddles examining the discordance between monitoring orders and monitoring status) to improve the accuracy of using continuous pulse oximetry orders.

We acknowledge several limitations of this study. Site investigators employed a convenience sampling approach, so it is possible that some investigators observed sicker or less sick infants. Although the PRIS network includes a geographically diverse group of North American hospitals, community hospitals were underrepresented in this study. Our results hence generalize more precisely to freestanding children’s hospitals than to community hospitals. We did not observe infants currently on supplemental oxygen, so we do not know to what degree using orders is valid in that context. We did not collect data on why actual monitoring status differed from monitoring orders and hence cannot quantify to what extent different factors (eg, nurse belief that monitors are a safety net or infants inadvertently left on monitors after a spot check pulse oximetry reading) contributed to this discordance. Finally, our study only examined one electronic health record variable—the presence of an active order. It may be that other variables in the health record (eg, minute-by-minute pulse oximetry values in a vital sign flowsheet) are much better proxies of actual continuous monitor use.

CONCLUSION

Using an active order for continuous pulse oximetry has poor sensitivity, PPV, and NPV for detecting true monitoring status at the bedside. Teams intending to measure the actual use of pulse oximetry should be aware of the limitations of using active orders alone as an accurate measure of pulse oximetry monitoring.

Acknowledgments

We thank the NHLBI scientists who contributed to this project as part of the U01 Cooperative Agreement funding mechanism: Lora Reineck, MD, MS, Karen Bienstock, MS, and Cheryl Boyce, PhD.

We thank the Executive Council of the PRIS Network for their contributions to the early scientific development of this project. We thank the PRIS site investigators for their major contributions to the Eliminating Monitor Overuse (EMO) Study data collection. Each listed collaborator is a group author for the PRIS Network in this manuscript. Their names can be found in the online supplemental information.

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References

1. Ralston SL, Garber MD, Rice-Conboy E, et al. A multicenter collaborative to reduce unnecessary care in inpatient bronchiolitis. Pediatrics. 2016;137(1). https://doi.org/10.1542/peds.2015-0851
2. Mittal S, Marlowe L, Blakeslee S, et al. Successful use of quality improvement methodology to reduce inpatient length of stay in bronchiolitis through judicious use of intermittent pulse oximetry. Hosp Pediatr. 2019;9(2):73-78. https://doi.org/10.1542/hpeds.2018-0023
3. Quinonez RA, Coon ER, Schroeder AR, Moyer VA. When technology creates uncertainty: pulse oximetry and overdiagnosis of hypoxaemia in bronchiolitis. BMJ. 2017;358:j3850. https://doi.org/10.1136/bmj.j3850
4. Quinonez RA, Garber MD, Schroeder AR, et al. Choosing wisely in pediatric hospital medicine: five opportunities for improved healthcare value. J Hosp Med. 2013;8(9):479-485. https://doi.org/10.1002/jhm.2064
5. Ralston SL, Lieberthal AS, Meissner HC, et al. Clinical practice guideline: the diagnosis, management, and prevention of bronchiolitis. Pediatrics. 2014;134(5):e1474-e1502. https://doi.org/10.1542/peds.2014-2742
6. Principi T, Coates AL, Parkin PC, Stephens D, DaSilva Z, Schuh S. Effect of oxygen desaturations on subsequent medical visits in infants discharged from the emergency department with bronchiolitis. JAMA Pediatr. 2016;170(6):602-608. https://doi.org/10.1001/jamapediatrics.2016.0114
7. Cunningham S, Rodriguez A, Adams T, et al. Oxygen saturation targets in infants with bronchiolitis (BIDS): a double-blind, randomised, equivalence trial. Lancet. 2015;386(9998):1041-1048. https://doi.org/10.1016/s0140-6736(15)00163-4
8. McCulloh R, Koster M, Ralston S, et al. Use of intermittent vs continuous pulse oximetry for nonhypoxemic infants and young children hospitalized for bronchiolitis: a randomized clinical trial. JAMA Pediatr. 2015;169(10):898-904. https://doi.org/10.1001/jamapediatrics.2015.1746
9. Schuh S, Freedman S, Coates A, et al. Effect of oximetry on hospitalization in bronchiolitis: a randomized clinical trial. JAMA. 2014;312(7):712-718. https://doi.org/10.1001/jama.2014.8637
10. Schroeder AR, Marmor AK, Pantell RH, Newman TB. Impact of pulse oximetry and oxygen therapy on length of stay in bronchiolitis hospitalizations. Arch Pediatr Adolesc Med. 2004;158(6):527-530. https://doi.org/10.1001/archpedi.158.6.527
11. Rasooly IR, Beidas RS, Wolk CB, et al. Measuring overuse of continuous pulse oximetry in bronchiolitis and developing strategies for large-scale deimplementation: study protocol for a feasibility trial. Pilot Feasibility Stud. 2019;5:68. https://doi.org/10.1186/s40814-019-0453-2

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1Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; 2James M. Anderson Center for Health Systems Excellence, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; 3Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio; 4Division of General Pediatrics, Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts; 5Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, Massachusetts; 6Harvard Medical School, Boston, Massachusetts; 7Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; 8Section of Pediatric Hospital Medicine, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 9Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 10Center for Pediatric Clinical Effectiveness, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 11Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.

Disclosures

The authors have no financial or other conflicts of interest to disclose.

Previous presentation of the information reported in the manuscript: Presented at the Pediatric Hospital Annual Meeting in Seattle, Washington, on July 26, 2019.

Funding

This study was funded by a Cooperative Agreement from the National Heart, Lung, and Blood Institute of the National Institutes of Health (5U01HL143475) awarded to Dr Bonafide. Dr Brady’s contribution to this manuscript was supported by the Agency for Healthcare Research and Quality under Award Number K08HS23827. Dr Schondelmeyer’s contribution to this manuscript was supported by the Agency for Healthcare Research and Quality under Award Number K08HS026763. Dr Bonafide’s contribution to this manuscript was supported in part by the National Heart, Lung, and Blood Institute under award number K23HL116427. The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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1Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; 2James M. Anderson Center for Health Systems Excellence, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; 3Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio; 4Division of General Pediatrics, Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts; 5Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, Massachusetts; 6Harvard Medical School, Boston, Massachusetts; 7Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; 8Section of Pediatric Hospital Medicine, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 9Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 10Center for Pediatric Clinical Effectiveness, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 11Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.

Disclosures

The authors have no financial or other conflicts of interest to disclose.

Previous presentation of the information reported in the manuscript: Presented at the Pediatric Hospital Annual Meeting in Seattle, Washington, on July 26, 2019.

Funding

This study was funded by a Cooperative Agreement from the National Heart, Lung, and Blood Institute of the National Institutes of Health (5U01HL143475) awarded to Dr Bonafide. Dr Brady’s contribution to this manuscript was supported by the Agency for Healthcare Research and Quality under Award Number K08HS23827. Dr Schondelmeyer’s contribution to this manuscript was supported by the Agency for Healthcare Research and Quality under Award Number K08HS026763. Dr Bonafide’s contribution to this manuscript was supported in part by the National Heart, Lung, and Blood Institute under award number K23HL116427. The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Author and Disclosure Information

1Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; 2James M. Anderson Center for Health Systems Excellence, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; 3Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio; 4Division of General Pediatrics, Department of Pediatrics, Boston Children’s Hospital, Boston, Massachusetts; 5Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, Massachusetts; 6Harvard Medical School, Boston, Massachusetts; 7Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; 8Section of Pediatric Hospital Medicine, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 9Department of Biomedical and Health Informatics, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 10Center for Pediatric Clinical Effectiveness, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; 11Department of Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.

Disclosures

The authors have no financial or other conflicts of interest to disclose.

Previous presentation of the information reported in the manuscript: Presented at the Pediatric Hospital Annual Meeting in Seattle, Washington, on July 26, 2019.

Funding

This study was funded by a Cooperative Agreement from the National Heart, Lung, and Blood Institute of the National Institutes of Health (5U01HL143475) awarded to Dr Bonafide. Dr Brady’s contribution to this manuscript was supported by the Agency for Healthcare Research and Quality under Award Number K08HS23827. Dr Schondelmeyer’s contribution to this manuscript was supported by the Agency for Healthcare Research and Quality under Award Number K08HS026763. Dr Bonafide’s contribution to this manuscript was supported in part by the National Heart, Lung, and Blood Institute under award number K23HL116427. The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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Related Articles

As part of improvement collaboratives that aimed to reduce overuse of continuous pulse oximetry in children hospitalized with bronchiolitis, researchers used the presence of an active order for it as a proxy for the actual use of such monitoring.1,2 With use of this proxy, investigators on a national study documented a high burden of continuous oximetry overuse (86.5% before quality improvement interventions and 45.5% after),1 but the validity of orders in representing actual monitoring practice is unknown. If the presence of an active pulse oximetry order accurately identifies infants on monitors, electronic health record data could inform epidemiologic estimates of monitoring overuse and measure the success of quality improvement and deimplementation interventions. Alternatively, if nurses commonly begin and/or discontinue pulse oximetry without updated orders, a pulse oximetry order would not be an accurate proxy, and additional data capture methods (eg, bedside observation or data capture from bedside monitors) would be needed.

Understanding the validity of orders for detection of actual use is critical because continuous pulse oximetry monitoring is considered an overused practice in pediatric acute viral bronchiolitis,3 and national guidelines recommend against its use in low-risk hospitalized children.4,5 Continuous monitoring may identify trivial, self-resolving oxygen desaturation and its use is not associated with improved outcomes.6-9 When self-resolving desaturations are treated with additional supplemental oxygen, hospital stays may be unnecessarily prolonged.10 In order to reduce unnecessary continuous pulse oximetry use, measurement of the extent of the overused practice is necessary. In this 56-hospital study,11 we aimed to determine the validity of using active continuous pulse oximetry orders instead of bedside observation of actual monitor use.

METHODS

Design

In this multicenter, repeated cross-sectional study, investigators used direct bedside observation to determine continuous pulse oximetry monitor use and then assessed whether an active continuous monitoring order was present in the electronic health record. The study took place during one bronchiolitis season, December 1, 2018, through March 31, 2019.

Setting and Patients

Investigators at 56 freestanding children’s hospitals, children’s hospitals within general hospitals, and community hospitals in the Pediatric Research in Inpatient Settings (PRIS) Network collected data on infants aged 8 weeks to 23 months who were hospitalized with bronchiolitis. As this work was a substudy of the larger Eliminating Monitor Overuse study, only infants not currently receiving supplemental oxygen were included.11 Investigators observed eligible infants outside of the intensive care unit on general hospital medicine units. We excluded infants born premature (documented prematurity of <28 weeks’ gestation or documented “premature” without a gestational age listed), as well as those with a home oxygen requirement, cyanotic congenital heart disease, pulmonary hypertension, tracheostomy, primary neuromuscular disease, immunodeficiency, or cancer.

Data Collection

Investigators used the electronic health record to identify eligible infants. Investigators entered patient rooms to confirm the infant was not on supplemental oxygen (hence confirming eligibility for the study) and determine if continuous pulse oximetry was actively in use by examining the monitor display for a pulse oximetry waveform. Investigators then confirmed if active orders for pulse oximetry were present in the patient’s chart. Per study design, site investigators aimed to observe approximately half of eligible infants during the day (10 am to 5 pm) and the other half during the night (11 pm to 7 am).

Analysis

We excluded patients with conditional orders (eg, monitored only when certain conditions exist, such as when asleep) because of the time-varying and wide range of conditions that could be specified. Furthermore, conditional orders would not be useful as proxies to measure oximetry use because investigators would still need additional data (eg, bedside observation) to determine current monitoring status.

We calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of active orders using the reference standard of direct bedside observation, as well as corresponding 95% CIs that accounted for within-hospital clustering. We calculated these test characteristics overall and as stratified across four age groups: 8 weeks to 5 months, 6 months to 11 months, 12 months to 17 months, and 18 months to 23 months. We also calculated the test characteristics for each hospital. We decided a priori that a PPV and NPV of 80% would represent a reasonable threshold to use active orders as a proxy in multicenter research. For hospital-level analyses we included only hospitals with 60 or more total observations and more than 15 observations with active orders for PPV and more than 15 observations without active orders for NPV. We used Stata (StataCorp LLC, College Station, Texas) version 15.1 for analysis.

For US sites, the Institutional Review Board (IRB) at Children’s Hospital of Philadelphia approved the study as the single reviewing IRB, and the remaining US sites established reliance agreements with the reviewing IRB. Research Ethics Boards at the Canadian sites (University of Calgary and The Hospital for Sick Children) also reviewed and approved the study. All sites granted waivers of consent, assent, parental permission, and HIPAA authorization.

RESULTS

Investigators completed 3,612 observations in 56 hospitals. This included 33 freestanding children’s hospitals, 14 hospitals within large general hospitals, and 9 community hospitals. Of 3,612 completed observations, on 631 occasions (17%) patients had conditional orders (eg, continuous monitoring only when sleeping) and were excluded from further analysis.

Most pulse oximetry–monitored infants did not have an active monitoring order (670 out of 1,309; sensitivity of 49%). Test characteristics, stratified by age group, are presented in the Table. Across all observations, the overall PPV was 77% (95% CI, 72-82), and the overall NPV was 69% (95% CI, 61-77). Variation of all test characteristics across age group was small (eg, the sensitivity ranged from 43% to 51%).

Test Characteristics of the Relationship Between Active Orders and Actual Pulse Oximetry Monitoring, Both Overall and as Stratified by Age

With inclusion of only those hospitals with sufficient observations, hospital-level variation in the PPV and NPV of using active orders was substantial (PPV range of 48% to 96% and NPV range of 30% to 98%). Only two hospitals had both a PPV and NPV for using monitor orders that exceeded the 80% threshold.

DISCUSSION

Active continuous pulse oximetry orders did not accurately represent actual monitoring status in this study. Monitoring orders alone frequently misrepresent true monitoring status and, as such, should be interpreted with caution in research or quality improvement activities. If more valid estimates of monitoring use and overuse are needed, potential measurement options include direct observation, as used in our study, as well as the use of more complex data streams such as the output of monitoring devices or pulse oximetry data in the electronic health record. In only two of the hospitals, using active continuous monitoring orders was a reasonable proxy for detecting actual monitor use. Monitoring orders could potentially be validly used for deimplementation efforts at those centers; other hospitals could consider targeted improvement efforts (eg, morning huddles examining the discordance between monitoring orders and monitoring status) to improve the accuracy of using continuous pulse oximetry orders.

We acknowledge several limitations of this study. Site investigators employed a convenience sampling approach, so it is possible that some investigators observed sicker or less sick infants. Although the PRIS network includes a geographically diverse group of North American hospitals, community hospitals were underrepresented in this study. Our results hence generalize more precisely to freestanding children’s hospitals than to community hospitals. We did not observe infants currently on supplemental oxygen, so we do not know to what degree using orders is valid in that context. We did not collect data on why actual monitoring status differed from monitoring orders and hence cannot quantify to what extent different factors (eg, nurse belief that monitors are a safety net or infants inadvertently left on monitors after a spot check pulse oximetry reading) contributed to this discordance. Finally, our study only examined one electronic health record variable—the presence of an active order. It may be that other variables in the health record (eg, minute-by-minute pulse oximetry values in a vital sign flowsheet) are much better proxies of actual continuous monitor use.

CONCLUSION

Using an active order for continuous pulse oximetry has poor sensitivity, PPV, and NPV for detecting true monitoring status at the bedside. Teams intending to measure the actual use of pulse oximetry should be aware of the limitations of using active orders alone as an accurate measure of pulse oximetry monitoring.

Acknowledgments

We thank the NHLBI scientists who contributed to this project as part of the U01 Cooperative Agreement funding mechanism: Lora Reineck, MD, MS, Karen Bienstock, MS, and Cheryl Boyce, PhD.

We thank the Executive Council of the PRIS Network for their contributions to the early scientific development of this project. We thank the PRIS site investigators for their major contributions to the Eliminating Monitor Overuse (EMO) Study data collection. Each listed collaborator is a group author for the PRIS Network in this manuscript. Their names can be found in the online supplemental information.

As part of improvement collaboratives that aimed to reduce overuse of continuous pulse oximetry in children hospitalized with bronchiolitis, researchers used the presence of an active order for it as a proxy for the actual use of such monitoring.1,2 With use of this proxy, investigators on a national study documented a high burden of continuous oximetry overuse (86.5% before quality improvement interventions and 45.5% after),1 but the validity of orders in representing actual monitoring practice is unknown. If the presence of an active pulse oximetry order accurately identifies infants on monitors, electronic health record data could inform epidemiologic estimates of monitoring overuse and measure the success of quality improvement and deimplementation interventions. Alternatively, if nurses commonly begin and/or discontinue pulse oximetry without updated orders, a pulse oximetry order would not be an accurate proxy, and additional data capture methods (eg, bedside observation or data capture from bedside monitors) would be needed.

Understanding the validity of orders for detection of actual use is critical because continuous pulse oximetry monitoring is considered an overused practice in pediatric acute viral bronchiolitis,3 and national guidelines recommend against its use in low-risk hospitalized children.4,5 Continuous monitoring may identify trivial, self-resolving oxygen desaturation and its use is not associated with improved outcomes.6-9 When self-resolving desaturations are treated with additional supplemental oxygen, hospital stays may be unnecessarily prolonged.10 In order to reduce unnecessary continuous pulse oximetry use, measurement of the extent of the overused practice is necessary. In this 56-hospital study,11 we aimed to determine the validity of using active continuous pulse oximetry orders instead of bedside observation of actual monitor use.

METHODS

Design

In this multicenter, repeated cross-sectional study, investigators used direct bedside observation to determine continuous pulse oximetry monitor use and then assessed whether an active continuous monitoring order was present in the electronic health record. The study took place during one bronchiolitis season, December 1, 2018, through March 31, 2019.

Setting and Patients

Investigators at 56 freestanding children’s hospitals, children’s hospitals within general hospitals, and community hospitals in the Pediatric Research in Inpatient Settings (PRIS) Network collected data on infants aged 8 weeks to 23 months who were hospitalized with bronchiolitis. As this work was a substudy of the larger Eliminating Monitor Overuse study, only infants not currently receiving supplemental oxygen were included.11 Investigators observed eligible infants outside of the intensive care unit on general hospital medicine units. We excluded infants born premature (documented prematurity of <28 weeks’ gestation or documented “premature” without a gestational age listed), as well as those with a home oxygen requirement, cyanotic congenital heart disease, pulmonary hypertension, tracheostomy, primary neuromuscular disease, immunodeficiency, or cancer.

Data Collection

Investigators used the electronic health record to identify eligible infants. Investigators entered patient rooms to confirm the infant was not on supplemental oxygen (hence confirming eligibility for the study) and determine if continuous pulse oximetry was actively in use by examining the monitor display for a pulse oximetry waveform. Investigators then confirmed if active orders for pulse oximetry were present in the patient’s chart. Per study design, site investigators aimed to observe approximately half of eligible infants during the day (10 am to 5 pm) and the other half during the night (11 pm to 7 am).

Analysis

We excluded patients with conditional orders (eg, monitored only when certain conditions exist, such as when asleep) because of the time-varying and wide range of conditions that could be specified. Furthermore, conditional orders would not be useful as proxies to measure oximetry use because investigators would still need additional data (eg, bedside observation) to determine current monitoring status.

We calculated the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of active orders using the reference standard of direct bedside observation, as well as corresponding 95% CIs that accounted for within-hospital clustering. We calculated these test characteristics overall and as stratified across four age groups: 8 weeks to 5 months, 6 months to 11 months, 12 months to 17 months, and 18 months to 23 months. We also calculated the test characteristics for each hospital. We decided a priori that a PPV and NPV of 80% would represent a reasonable threshold to use active orders as a proxy in multicenter research. For hospital-level analyses we included only hospitals with 60 or more total observations and more than 15 observations with active orders for PPV and more than 15 observations without active orders for NPV. We used Stata (StataCorp LLC, College Station, Texas) version 15.1 for analysis.

For US sites, the Institutional Review Board (IRB) at Children’s Hospital of Philadelphia approved the study as the single reviewing IRB, and the remaining US sites established reliance agreements with the reviewing IRB. Research Ethics Boards at the Canadian sites (University of Calgary and The Hospital for Sick Children) also reviewed and approved the study. All sites granted waivers of consent, assent, parental permission, and HIPAA authorization.

RESULTS

Investigators completed 3,612 observations in 56 hospitals. This included 33 freestanding children’s hospitals, 14 hospitals within large general hospitals, and 9 community hospitals. Of 3,612 completed observations, on 631 occasions (17%) patients had conditional orders (eg, continuous monitoring only when sleeping) and were excluded from further analysis.

Most pulse oximetry–monitored infants did not have an active monitoring order (670 out of 1,309; sensitivity of 49%). Test characteristics, stratified by age group, are presented in the Table. Across all observations, the overall PPV was 77% (95% CI, 72-82), and the overall NPV was 69% (95% CI, 61-77). Variation of all test characteristics across age group was small (eg, the sensitivity ranged from 43% to 51%).

Test Characteristics of the Relationship Between Active Orders and Actual Pulse Oximetry Monitoring, Both Overall and as Stratified by Age

With inclusion of only those hospitals with sufficient observations, hospital-level variation in the PPV and NPV of using active orders was substantial (PPV range of 48% to 96% and NPV range of 30% to 98%). Only two hospitals had both a PPV and NPV for using monitor orders that exceeded the 80% threshold.

DISCUSSION

Active continuous pulse oximetry orders did not accurately represent actual monitoring status in this study. Monitoring orders alone frequently misrepresent true monitoring status and, as such, should be interpreted with caution in research or quality improvement activities. If more valid estimates of monitoring use and overuse are needed, potential measurement options include direct observation, as used in our study, as well as the use of more complex data streams such as the output of monitoring devices or pulse oximetry data in the electronic health record. In only two of the hospitals, using active continuous monitoring orders was a reasonable proxy for detecting actual monitor use. Monitoring orders could potentially be validly used for deimplementation efforts at those centers; other hospitals could consider targeted improvement efforts (eg, morning huddles examining the discordance between monitoring orders and monitoring status) to improve the accuracy of using continuous pulse oximetry orders.

We acknowledge several limitations of this study. Site investigators employed a convenience sampling approach, so it is possible that some investigators observed sicker or less sick infants. Although the PRIS network includes a geographically diverse group of North American hospitals, community hospitals were underrepresented in this study. Our results hence generalize more precisely to freestanding children’s hospitals than to community hospitals. We did not observe infants currently on supplemental oxygen, so we do not know to what degree using orders is valid in that context. We did not collect data on why actual monitoring status differed from monitoring orders and hence cannot quantify to what extent different factors (eg, nurse belief that monitors are a safety net or infants inadvertently left on monitors after a spot check pulse oximetry reading) contributed to this discordance. Finally, our study only examined one electronic health record variable—the presence of an active order. It may be that other variables in the health record (eg, minute-by-minute pulse oximetry values in a vital sign flowsheet) are much better proxies of actual continuous monitor use.

CONCLUSION

Using an active order for continuous pulse oximetry has poor sensitivity, PPV, and NPV for detecting true monitoring status at the bedside. Teams intending to measure the actual use of pulse oximetry should be aware of the limitations of using active orders alone as an accurate measure of pulse oximetry monitoring.

Acknowledgments

We thank the NHLBI scientists who contributed to this project as part of the U01 Cooperative Agreement funding mechanism: Lora Reineck, MD, MS, Karen Bienstock, MS, and Cheryl Boyce, PhD.

We thank the Executive Council of the PRIS Network for their contributions to the early scientific development of this project. We thank the PRIS site investigators for their major contributions to the Eliminating Monitor Overuse (EMO) Study data collection. Each listed collaborator is a group author for the PRIS Network in this manuscript. Their names can be found in the online supplemental information.

References

1. Ralston SL, Garber MD, Rice-Conboy E, et al. A multicenter collaborative to reduce unnecessary care in inpatient bronchiolitis. Pediatrics. 2016;137(1). https://doi.org/10.1542/peds.2015-0851
2. Mittal S, Marlowe L, Blakeslee S, et al. Successful use of quality improvement methodology to reduce inpatient length of stay in bronchiolitis through judicious use of intermittent pulse oximetry. Hosp Pediatr. 2019;9(2):73-78. https://doi.org/10.1542/hpeds.2018-0023
3. Quinonez RA, Coon ER, Schroeder AR, Moyer VA. When technology creates uncertainty: pulse oximetry and overdiagnosis of hypoxaemia in bronchiolitis. BMJ. 2017;358:j3850. https://doi.org/10.1136/bmj.j3850
4. Quinonez RA, Garber MD, Schroeder AR, et al. Choosing wisely in pediatric hospital medicine: five opportunities for improved healthcare value. J Hosp Med. 2013;8(9):479-485. https://doi.org/10.1002/jhm.2064
5. Ralston SL, Lieberthal AS, Meissner HC, et al. Clinical practice guideline: the diagnosis, management, and prevention of bronchiolitis. Pediatrics. 2014;134(5):e1474-e1502. https://doi.org/10.1542/peds.2014-2742
6. Principi T, Coates AL, Parkin PC, Stephens D, DaSilva Z, Schuh S. Effect of oxygen desaturations on subsequent medical visits in infants discharged from the emergency department with bronchiolitis. JAMA Pediatr. 2016;170(6):602-608. https://doi.org/10.1001/jamapediatrics.2016.0114
7. Cunningham S, Rodriguez A, Adams T, et al. Oxygen saturation targets in infants with bronchiolitis (BIDS): a double-blind, randomised, equivalence trial. Lancet. 2015;386(9998):1041-1048. https://doi.org/10.1016/s0140-6736(15)00163-4
8. McCulloh R, Koster M, Ralston S, et al. Use of intermittent vs continuous pulse oximetry for nonhypoxemic infants and young children hospitalized for bronchiolitis: a randomized clinical trial. JAMA Pediatr. 2015;169(10):898-904. https://doi.org/10.1001/jamapediatrics.2015.1746
9. Schuh S, Freedman S, Coates A, et al. Effect of oximetry on hospitalization in bronchiolitis: a randomized clinical trial. JAMA. 2014;312(7):712-718. https://doi.org/10.1001/jama.2014.8637
10. Schroeder AR, Marmor AK, Pantell RH, Newman TB. Impact of pulse oximetry and oxygen therapy on length of stay in bronchiolitis hospitalizations. Arch Pediatr Adolesc Med. 2004;158(6):527-530. https://doi.org/10.1001/archpedi.158.6.527
11. Rasooly IR, Beidas RS, Wolk CB, et al. Measuring overuse of continuous pulse oximetry in bronchiolitis and developing strategies for large-scale deimplementation: study protocol for a feasibility trial. Pilot Feasibility Stud. 2019;5:68. https://doi.org/10.1186/s40814-019-0453-2

References

1. Ralston SL, Garber MD, Rice-Conboy E, et al. A multicenter collaborative to reduce unnecessary care in inpatient bronchiolitis. Pediatrics. 2016;137(1). https://doi.org/10.1542/peds.2015-0851
2. Mittal S, Marlowe L, Blakeslee S, et al. Successful use of quality improvement methodology to reduce inpatient length of stay in bronchiolitis through judicious use of intermittent pulse oximetry. Hosp Pediatr. 2019;9(2):73-78. https://doi.org/10.1542/hpeds.2018-0023
3. Quinonez RA, Coon ER, Schroeder AR, Moyer VA. When technology creates uncertainty: pulse oximetry and overdiagnosis of hypoxaemia in bronchiolitis. BMJ. 2017;358:j3850. https://doi.org/10.1136/bmj.j3850
4. Quinonez RA, Garber MD, Schroeder AR, et al. Choosing wisely in pediatric hospital medicine: five opportunities for improved healthcare value. J Hosp Med. 2013;8(9):479-485. https://doi.org/10.1002/jhm.2064
5. Ralston SL, Lieberthal AS, Meissner HC, et al. Clinical practice guideline: the diagnosis, management, and prevention of bronchiolitis. Pediatrics. 2014;134(5):e1474-e1502. https://doi.org/10.1542/peds.2014-2742
6. Principi T, Coates AL, Parkin PC, Stephens D, DaSilva Z, Schuh S. Effect of oxygen desaturations on subsequent medical visits in infants discharged from the emergency department with bronchiolitis. JAMA Pediatr. 2016;170(6):602-608. https://doi.org/10.1001/jamapediatrics.2016.0114
7. Cunningham S, Rodriguez A, Adams T, et al. Oxygen saturation targets in infants with bronchiolitis (BIDS): a double-blind, randomised, equivalence trial. Lancet. 2015;386(9998):1041-1048. https://doi.org/10.1016/s0140-6736(15)00163-4
8. McCulloh R, Koster M, Ralston S, et al. Use of intermittent vs continuous pulse oximetry for nonhypoxemic infants and young children hospitalized for bronchiolitis: a randomized clinical trial. JAMA Pediatr. 2015;169(10):898-904. https://doi.org/10.1001/jamapediatrics.2015.1746
9. Schuh S, Freedman S, Coates A, et al. Effect of oximetry on hospitalization in bronchiolitis: a randomized clinical trial. JAMA. 2014;312(7):712-718. https://doi.org/10.1001/jama.2014.8637
10. Schroeder AR, Marmor AK, Pantell RH, Newman TB. Impact of pulse oximetry and oxygen therapy on length of stay in bronchiolitis hospitalizations. Arch Pediatr Adolesc Med. 2004;158(6):527-530. https://doi.org/10.1001/archpedi.158.6.527
11. Rasooly IR, Beidas RS, Wolk CB, et al. Measuring overuse of continuous pulse oximetry in bronchiolitis and developing strategies for large-scale deimplementation: study protocol for a feasibility trial. Pilot Feasibility Stud. 2019;5:68. https://doi.org/10.1186/s40814-019-0453-2

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Imaging Strategies and Outcomes in Children Hospitalized with Cervical Lymphadenitis

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Cervical lymphadenitis is a common superficial neck infection in childhood. While most children with cervical lymphadenitis recover with antibiotic therapy, a subset can develop an abscess that may require surgical drainage. Radiologic imaging, most commonly ultrasound or computed tomography (CT), is often performed to identify such an abscess.1-3 However, no national standards exist to guide clinician decision making around imaging in this population. In the absence of evidence-based guidelines, variability in frequency, timing, and modality of imaging likely exists in children hospitalized with cervical lymphadenitis.

As demonstrated for several other common pediatric conditions,4,5 variability in imaging practices may contribute to overutilization of resources in children with cervical lymphadenitis. In particular, routinely conducting imaging on presentation may constitute overuse, as children with cervical lymphadenitis who present with less than 72 hours of neck swelling rarely undergo surgical drainage within the first 24 hours of hospitalization.1,6,7 Imaging performed on presentation is often repeated later during hospitalization, particularly if the patient has not improved with antibiotic therapy. The net result may be unnecessary, redundant radiologic studies. Furthermore, serious complications such as bacteremia, extension of infection into the retropharyngeal space, or involvement of the airway or vasculature rarely occur in children with cervical lymphadenitis.6,8 In this context, deferring initial imaging in this population is unlikely to lead to adverse outcomes and may reduce radiation exposure.

The overall objectives of this study are to describe hospital-level variation in imaging practices for pediatric cervical lymphadenitis and to examine the association between early imaging and outcomes in this population.

METHODS

Study Design and Data Source

We conducted a multicenter, cross-sectional study using the Pediatric Health Information Systems (PHIS) database, which contains administrative and billing data from 49 geographically diverse children’s hospitals across the United States (US) affiliated with the Children’s Hospital Association (Lenexa, Kansas). PHIS includes data on patient demographics, discharge diagnoses, and procedures using the International Classification of Diseases, 9th (ICD-9) and 10th Revision (ICD-10) diagnosis codes, as well as daily billed resource utilization for laboratory tests, imaging studies, and medications. Encrypted medical record numbers permit longitudinal identification of children across multiple visits to the same hospital. Use of de-identified PHIS data was deemed to be nonhuman subjects research; our approach to validation of ICD codes using local electronic medical record review was reviewed and approved by the Cincinnati Children’s Hospital Medical Center Institutional Review Board.

Study Population

Our study team developed an algorithm to identify children with cervical lymphadenitis and minimize misclassification using PHIS (Appendix A). All children with lymphadenitis-related ICD-9 and ICD-10 discharge diagnosis codes were eligible for inclusion. Codes were validated at a single center via electronic medical record review; clinician-documented discharge diagnosis of cervical lymphadenitis or the presence of fever and unilateral or asymmetrical neck swelling with overlying skin changes was used as the reference standard. We then excluded children who did not receive antibiotics, children who received radiologic imaging not involving the head or neck (which suggested noncervical lymphadenitis or other illness), and children who had discharge diagnosis codes for other specified conditions that are sometimes associated with enlarged cervical lymph nodes but warrant different evaluation or treatment (eg, Kawasaki disease, retropharyngeal abscess, and dental abscess; Appendix A). Our final algorithm yielded a positive predictive value of 87.5% (95% CI: 79.2%-93.4%) when ICD-9 codes were considered, and 95.1% (95% CI: 88.9%-98.4%) when ICD-10 codes were considered (Appendix A).

This algorithm was subsequently applied to the PHIS database. Children ages two months to 18 years hospitalized at participating PHIS institutions between July 2013 and December 2017 with a diagnosis of cervical lymphadenitis as per the algorithm (Appendix A) were eligible for inclusion. For children with multiple eligible admissions during the study period, we only included the first hospitalization. Children with complex chronic condition diagnosis codes9 were excluded as their clinical complexity could influence decisions around timing and modality of diagnostic imaging. In addition, we excluded children who did not have an emergency department (ED) visit associated with their hospitalization. This step was intended to exclude children who were transferred from another institution, as imaging performed at outside institutions prior to transfer is not available in PHIS. To avoid overinflating hospital-level variation in the setting of a small sample size, we also excluded all children admitted to the five hospitals with fewer than 50 cases of cervical lymphadenitis during the study period. Our final cohort consisted of 44 PHIS hospitals.

Measures of Interest

To examine hospital-level variation in imaging practices, we measured the proportion of children at each hospital who underwent any neck imaging study, CT or ultrasound imaging, early imaging, and multiple imaging studies within a single hospitalization. Neck imaging was defined as the presence of a billing code for ultrasound, CT, or magnetic resonance imaging (MRI) study of the neck (Appendix B). Early imaging was defined as neck imaging conducted on day 0 of hospitalization (ie, calendar day of admission and ending at midnight). Multiple imaging studies were defined as the receipt of more than one imaging study, regardless of timing or modality. We also measured the proportion of children by hospital who received surgical drainage, defined by the presence of procedure codes for incision and drainage of abscess of the neck (Appendix B).

In examining patient-level association between early imaging and clinical outcomes, our primary outcome of interest was the receipt of multiple imaging studies. Secondary outcomes included rates of surgical drainage, length of stay (in hospital days), and rates of lymphadenitis-related hospital readmission within 30 days of index discharge.

Covariates

Baseline demographic characteristics included age, gender, race/ethnicity, and insurance type. We measured ED visits associated with lymphadenitis-related diagnosis codes in the 30 days prior to admission as a proxy measure for illness duration prior to presentation. To approximate illness severity, we included the following covariates: rates of intensive care unit admission on presentation, rates of receipt of intravenous (IV) analgesia (Appendix B) on hospital days prior to surgical drainage, and rates of receipt of broad-spectrum antibiotics on day 0 or 1 of hospitalization. Broad-spectrum antibiotics (Appendix B) were defined by an independent three-person review of available antibiotic codes (SD, SSS, and JT); differences were resolved by group consensus.

 

 

Analysis

Categorical variables were described using frequencies and percentages, while continuous data were described using median and interquartile range. We described hospital-level variation in imaging practices by calculating and comparing the proportion of children at each hospital who underwent any neck imaging study, CT imaging, ultrasound imaging, early imaging, multiple imaging studies, and surgical drainage.

Patient-level demographics and clinical characteristics were compared across groups using chi-square test. To examine the association between early imaging and outcomes, we used generalized linear or logistic mixed effects models to control for patient demographic characteristics and clinical markers of illness duration and severity, with a random effect for hospital to account for clustering. Patient demographics in the model defined a priori included age, race/ethnicity, and insurance type; clinical characteristics included prior ED visit for lymphadenitis, initial intensive care unit (ICU) admission, use of IV analgesia, and use of broad-spectrum antibiotics on day 0 or 1 of hospitalization. To assess the potential for misclassification related to the availability of calendar day but not time of imaging in PHIS, we conducted a secondary analysis to examine the patient-level association between early imaging and outcomes using an alternative definition for early imaging (defined as imaging conducted on day 0 or day 1 of hospitalization).



All statistical analyses were performed by using SAS version 9.4 (SAS Institute, Cary, North Carolina); P < .05 was considered statistically significant.

RESULTS

We identified 19,785 PHIS hospitalizations with lymphadenitis-related discharge diagnosis codes between July 1, 2013 and December 31, 2017. Applying our algorithm and exclusion criteria, we assembled a cohort of 10,014 children hospitalized with cervical lymphadenitis (Figure 1). Two-thirds of the children in our cohort were <4 years old, 42% were non-Hispanic white, and 63% had a government payor (Table 1). Neck imaging (ultrasound, CT, or MRI) was conducted in 8,103 (81%) children. CT imaging was performed in 4,097 (41%) of children, and early imaging was conducted in 6,111 (61%) of children with cervical lymphadenitis.

We noted hospital-level variation in rates of any neck imaging (median: 82.1%, interquartile range [IQR]: 77.7%-85.5%, full range: 68.7%-93.1%), CT imaging (median: 42.3%, IQR: 26.7%-55.2%, full range: 12.0%-81.5%), early imaging (median: 64.4%, IQR: 59.8%-68.4%, full range: 13.8%-76.9%), and multiple imaging studies (median: 23.7%, IQR: 18.6%-28.9%, full range: 1.2%-40.7%; Figure 2). Rates of surgical drainage also varied by hospital (median: 35.1%, IQR: 31.3%-42.0%, full range: 17.1%-54.5%).



At the patient level, children who received early imaging were more likely to be <1 year old (21% vs 16%, P < .001), or Hispanic or Black when compared with children who did not receive early imaging (Table 1). Children who received early imaging were more likely to have had an ED visit for lymphadenitis in the preceding 30 days (8% vs 6%, P = .001). However, they were less likely to have received broad-spectrum antibiotics on admission (6% vs 8%, P < .001; Table 1). Of the 6,111 patients who received early imaging, 2,538 (41.5%) received CT imaging and 3,902 (63.9%) received ultrasound imaging on day 0. Of the 2,272 patients receiving multiple imaging studies, 116 (5.1%) received two or more CT scans.


In multivariable analysis at the patient level, early imaging was associated with higher adjusted odds of receiving multiple imaging studies (adjusted odds ratio [aOR] 3.0, 95% CI: 2.6-3.6). Similarly, early imaging was associated with higher adjusted odds of surgical drainage (aOR: 1.3, 95% CI: 1.1-1.4), increased 30-day readmission for lymphadenitis (aOR: 1.5, 95% CI: 1.2-1.9), and longer length of stay (adjusted rate ratio: 1.2, 95% CI: 1.1-1.2; Table 2). For the subset of patients who did not receive surgical drainage during the index admission, the adjusted odds ratio for the association between early imaging at index admission and 30-day readmission was 1.7 (95% CI: 1.3-2.1). About 63% of readmissions occurred within 7 days of index discharge; 89% occurred within 14 days (Appendix Figure).


In secondary analysis using an alternative definition for early imaging (ie, imaging conducted on day 0 or day 1 of hospitalization), the adjusted odds ratio for multiple imaging studies was 22.6 (95% CI: 15.8-32.4). The adjusted odds and rate ratios for the remaining outcomes were similar to our primary analysis.

 

 

DISCUSSION

In this large multicenter study of children with cervical lymphadenitis, we found variation in imaging practices across 44 US children’s hospitals. Children with cervical lymphadenitis who underwent early imaging were more likely to receive multiple imaging studies during a single hospitalization than those who did not receive early imaging. At the patient level, early imaging was also associated with higher rates of surgical drainage, more frequent 30-day readmission, and longer lengths of stay.

To our knowledge, imaging practices in the population of children hospitalized with cervical lymphadenitis have not been previously characterized in the US; one study from Atlanta, Georgia, describes imaging practices in all children evaluated in the ED.1 Single-center studies of children hospitalized with cervical lymphadenitis have been previously conducted in Canada6 and New Zealand,8 in which 42%-51% of children received imaging. In our study, most (81%) children hospitalized with lymphadenitis received some form of imaging, with 61% of all children receiving early imaging. Furthermore, 41% received CT imaging, as compared with 8%-10% of children in the aforementioned studies from Canada and New Zealand.6,8 This finding is consistent with a pattern of imaging overuse in the US, which has amongst the highest utilization rates globally for advanced imaging such as CT and MRI.10,11 Identifying opportunities to safely reduce routine imaging, particularly CT imaging, in this population could decrease unnecessary radiation exposure without compromising outcomes.

We also noted variability in imaging practices across PHIS hospitals. Some of this variability may be partially explained by differences in the patient population or illness severity across hospitals. However, given the absence of evidence-based best practices for children with cervical lymphadenitis, clinicians may rely on anecdotal experience or local practice culture to guide their decision making,12 leading to variability in frequency, timing, and modality of imaging.

At the patient level, we found that children who received early imaging were more likely to receive multiple imaging studies. This finding supports our hypothesis that clinicians often order a second imaging study when the initial imaging study does not clearly demonstrate an abscess, and the child subsequently fails to demonstrate clear improvement after 24-48 hours of antibiotics.

Furthermore, early imaging was associated with overall increased utilization in our cohort, including increased likelihood of surgical drainage, 30-day readmission for lymphadenitis, as well as longer lengths of stay. Confounding may be one explanation for this finding. For instance, clinicians may pursue early imaging in children who present with longer duration of symptoms or more severe illness on presentation, as these factors may be associated with abscess formation.1,6,7 These clinical covariates are not available in PHIS. Thus, we used prior ED visits for lymphadenitis to approximate illness duration, and initial admission to ICU, receipt of IV analgesia, and receipt of broad-spectrum antibiotics to approximate illness severity in an attempt to mitigate confounding. However, our proxy measures may not appropriately estimate illness duration and severity. For instance, children who had urgent care or outpatient visits for lymphadenitis would not be captured using the proxy of prior ED visit for lymphadenitis. Similarly, use of broad-spectrum antibiotics and IV analgesia may be influenced by provider or institutional preference rather than illness severity. Thus, residual confounding may exist despite adjusting for these measures.

On the other hand, it is also possible that a proportion of children with a small fluid collection on imaging may have improved with antibiotics alone. There is a growing body of evidence in children with other head and neck infections (eg, retropharyngeal abscess and orbital cellulitis with periosteal abscess)13-15 that suggests that children with small abscesses often improve with antibiotic therapy alone. In children with cervical lymphadenitis who have small or developing abscesses identified via routine imaging on presentation, clinicians may be driven to pursue a surgical intervention with uncertain benefit. Deferring routine imaging in this population may provide an opportunity to improve the value of care in children with lymphadenitis without adversely affecting outcomes.

Upon closer examination of readmissions, children who received early imaging during index hospitalization were more likely to have a 30-day readmission when only evaluating the subset of patients who did not receive surgical drainage during the index admission. This suggests that readmissions are less likely attributable to surgical complications and more likely a reflection of the natural history of lymphadenitis in which a subset of patients eventually develop an abscess. Further supporting this, 61% of children who had a 30-day readmission for lymphadenitis underwent surgical drainage during readmission. Given that lymphadenitis is a slow-brewing infection in which serious complications are rare, patients who demonstrate gradual clinical improvement do not need to remain hospitalized and serially imaged to identify a possible abscess. Outpatient expectant management and readmission as needed for drainage may be an acceptable approach.

This study has several limitations given our use of an administrative database. Children with lymphadenitis may have been misclassified as these patients were identified using discharge diagnosis codes. To mitigate this potential misclassification, we conducted a structured validation process and found that the included codes had high positive predictive values (Appendix A). This validation process was conducted at a single hospital, and coding may vary across hospitals. To approximate sensitivity, we also sampled children without our included codes but with neck imaging and antibiotic use, and found that rates of cervical lymphadenitis were very low among children without our included diagnosis codes.

Furthermore, we were unable to measure the exact time of imaging study in PHIS; we used imaging conducted on hospital day 0 as a proxy measure for imaging conducted within the first 24 hours of presentation. With this definition, some children who had early imaging were likely misclassified as not having received early imaging. For example, a patient who arrived in the ED at 9 pm on day 0 of admission and had a neck ultrasound performed at 1 am would be classified as having had an imaging study on day 1 of hospitalization even though the imaging study was conducted within 4 hours of presentation. Using an alternative definition of early imaging as imaging conducted on hospital day 0 and day 1, we found a much higher adjusted OR for multiple imaging studies, with similar associations for secondary outcomes. As such, our definition of early imaging as day 0 likely biases the results toward the null; the true increase in likelihood of multiple imaging for those who receive early imaging is probably greater than our conservative estimation.

Additionally, there may be a subset of children who underwent imaging prior to presentation at the PHIS hospital ED for further workup and admission. Imaging conducted outside a PHIS hospital was not captured in this database. Similarly, children who had a readmission at a different hospital than their index admission would not be captured using PHIS. Finally, PHIS captures data from children’s hospitals; practices at these hospitals may not be generalizable to practices in the community hospital setting.

 

 

CONCLUSION

In conclusion, we found that imaging practices in children hospitalized with cervical lymphadenitis were widely variable across hospitals. Children receiving early imaging had more resource utilization and intervention when compared with children who did not receive early imaging. Our findings may represent a cascade effect, in which routinely conducted early imaging prompts clinicians to pursue more testing and interventions in this population. Future studies should obtain more detailed patient level covariates to further characterize clinical factors that may impact decisions around imaging and clinical outcomes for children with cervical lymphadenitis.

Acknowledgments

The authors would like to acknowledge the following investigators for their contributions to data interpretation and review of the final manuscript: Angela Choe MD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Margaret Rush MD, Children’s National Medical Center, Washington, DC; Ryosuke Takei MD, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; Wallis Molchen DO, Texas Children’s Hospital, Houston, Texas; Stephanie Royer Moss MD, Cleveland Clinic, Cleveland, Ohio; Rebecca Dang, MD, Lucile Packard Children’s Hospital Stanford, Palo Alto, California; Joy Solano MD, Children’s Mercy Hospital Kansas, Overland Park, Kansas; Nathaniel P. Goodrich MD, Children’s Hospital & Medical Center, Omaha, Nebraska; Ngozi Eboh MD, Texas Tech University Health Sciences Center, Dallas, Texas; Ashley Jenkins MD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Rebecca Steuart MD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Sonya Tang Girdwood MD, PhD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Alissa McInerney MD, Maria Fareri Children’s Hospital at Westchester Medical Center, Valhalla, New York; Sumeet Banker MD, MPH, New York Presbyterian Morgan Stanley Children’s Hospital, New York, New York; Corrie McDaniel DO, Seattle Children’s Hospital, Seattle, Washington; Christiane Lenzen MD, Rady Children’s Hospital, San Diego, California; Aleisha Nabower MD, Children’s Hospital & Medical Center, Omaha, Nebraska; Waheeda Samady MD, Ann & Robert H. Lurie Children’s Hospital, Chicago, Illinois; Jennifer Chen MD, Rady Children’s Hospital, San Diego, California; Marquita Genies MD, MPH, John’s Hopkins Children’s Center, Baltimore, Maryland; Justin Lockwood MD, Children’s Hospital Colorado, Aurora, Colorado; David Synhorst MD, Children’s Mercy Hospital Kansas, Overland Park, Kansas.

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References

1. Sauer MW, Sharma S, Hirsh DA et al. Acute neck infections in children: who is likely to undergo surgical drainage? Am J Emerg Med. 2013;31(6):906-909. https://doi.org/10.1016/j.ajem.2013.02.043.
2. Sethia R, Mahida JB, Subbarayan RA, et al. Evaluation of an imaging protocol using ultrasound as the primary diagnostic modality in pediatric patients with superficial soft tissue infections of the face and neck. Int J Pediatr Otorhinolaryngol. 2017;96:89-93. https://doi.org/10.1016/j.ijporl.2017.02.027.
3. Neff L, Newland JG, Sykes KJ, Selvarangan R, Wei JL. Microbiology and antimicrobial treatment of pediatric cervical lymphadenitis requiring surgical intervention. Int J Pediatr Otorhinolaryngol. 2013;77(5):817-820. https://doi.org/10.1016/j.ijporl.2013.02.018.
4. Brogan TV, Hall M, Williams DJ, et al. Variability in processes of care and outcomes among children hospitalized with community-acquired pneumonia. Pediatr Infect Dis J. 2012;31(10):1036-1041. https://doi.org/10.1097/INF.0b013e31825f2b10.
5. Conway PH, Keren R. Factors associated with variability in outcomes for children hospitalized with urinary tract infection. J Pediatr. 2009;154(6):789-796. https://doi.org/10.1016/j.jpeds.2009.01.010.
6. Luu TM, Chevalier I, Gauthier M et al. Acute adenitis in children: clinical course and factors predictive of surgical drainage. J Paediatr Child Health. 2005;41(5-6):273-277. https://doi.org/10.1111/j.1440-1754.2005.00610.x.
7. Golriz F, Bisset GS, 3rd, D’Amico B, et al. A clinical decision rule for the use of ultrasound in children presenting with acute inflammatory neck masses. Pediatr Rad. 2017;47(4):422-428. https://doi.org/10.1007/s00247-016-3774-9.
8. Courtney MJ, Miteff A, Mahadevan M. Management of pediatric lateral neck infections: does the adage “… never let the sun go down on undrained pus …” hold true? Int J Pediatr Otorhinolaryngol. 2007;71(1):95-100. https://doi.org/10.1016/j.ijporl.2006.09.009.
9. Feudtner C, Feinstein JA, Zhong W, Hall M, Dai D. Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199. https://doi.org/10.1186/1471-2431-14-199.
10. Papanicolas I, Woskie LR, Jha AK. Health care spending in the United States and other high-income countries. JAMA. 2018;319(10):1024-1039. https://doi.org/10.1001/jama.2018.1150.
11. Oren O, Kebebew E, Ioannidis JPA. Curbing unnecessary and wasted diagnostic imaging. JAMA. 2019;321(3):245-246. https://doi.org/10.1001/jama.2018.20295.
12. Palmer RH, Miller MR. Methodologic challenges in developing and implementing measures of quality for child health care. Ambul Pediatr Off J Ambul Pediatr Assoc. 2001;1(1):39-52. https://doi.org/10.1367/1539-4409(2001)001<0039:MCIDAI>2.0.CO;2.
13. Daya H, Lo S, Papsin BC, et al. Retropharyngeal and parapharyngeal infections in children: the Toronto experience. Int J Pediatr Otorhinolaryngol. 2005;69(1):81-86. https://doi.org/10.1016/j.ijporl.2004.08.010.
14. Wong SJ, Levi J. Management of pediatric orbital cellulitis: A systematic review. Int J Pediatr Otorhinolaryngol. 2018;110:123-129. https://doi.org/10.1016/j.ijporl.2018.05.006.
15. Wong DK, Brown C, Mills N, Spielmann P, Neeff M. To drain or not to drain-management of pediatric deep neck abscesses: a case-control study. Int J Pediatr Otorhinolaryngol. 2012;76(12):1810-1813. https://doi.org/10.1016/j.ijporl.2012.09.006.

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The authors have no conflicts of interest relevant to this article to disclose.

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Supported by an institutional Clinical and Translational Science Award at the University Of Cincinnati College Of Medicine (National Institutes of Health National Center for Advancing Translational Sciences; 1UL1TR001425).

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Disclosures

The authors have no conflicts of interest relevant to this article to disclose.

Funding

Supported by an institutional Clinical and Translational Science Award at the University Of Cincinnati College Of Medicine (National Institutes of Health National Center for Advancing Translational Sciences; 1UL1TR001425).

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1Division of Hospital Medicine, Department of Pediatrics, Seattle Children’s Hospital, University of Washington School of Medicine, Seattle, Washington; 2Divisions of Hospital Medicine and of 3Infectious Diseases, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, University of Cincinnati College of Medicine, Cincinnati, Ohio; 4Children’s Hospital Association, Lenexa, Kansas.

Disclosures

The authors have no conflicts of interest relevant to this article to disclose.

Funding

Supported by an institutional Clinical and Translational Science Award at the University Of Cincinnati College Of Medicine (National Institutes of Health National Center for Advancing Translational Sciences; 1UL1TR001425).

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Related Articles

Cervical lymphadenitis is a common superficial neck infection in childhood. While most children with cervical lymphadenitis recover with antibiotic therapy, a subset can develop an abscess that may require surgical drainage. Radiologic imaging, most commonly ultrasound or computed tomography (CT), is often performed to identify such an abscess.1-3 However, no national standards exist to guide clinician decision making around imaging in this population. In the absence of evidence-based guidelines, variability in frequency, timing, and modality of imaging likely exists in children hospitalized with cervical lymphadenitis.

As demonstrated for several other common pediatric conditions,4,5 variability in imaging practices may contribute to overutilization of resources in children with cervical lymphadenitis. In particular, routinely conducting imaging on presentation may constitute overuse, as children with cervical lymphadenitis who present with less than 72 hours of neck swelling rarely undergo surgical drainage within the first 24 hours of hospitalization.1,6,7 Imaging performed on presentation is often repeated later during hospitalization, particularly if the patient has not improved with antibiotic therapy. The net result may be unnecessary, redundant radiologic studies. Furthermore, serious complications such as bacteremia, extension of infection into the retropharyngeal space, or involvement of the airway or vasculature rarely occur in children with cervical lymphadenitis.6,8 In this context, deferring initial imaging in this population is unlikely to lead to adverse outcomes and may reduce radiation exposure.

The overall objectives of this study are to describe hospital-level variation in imaging practices for pediatric cervical lymphadenitis and to examine the association between early imaging and outcomes in this population.

METHODS

Study Design and Data Source

We conducted a multicenter, cross-sectional study using the Pediatric Health Information Systems (PHIS) database, which contains administrative and billing data from 49 geographically diverse children’s hospitals across the United States (US) affiliated with the Children’s Hospital Association (Lenexa, Kansas). PHIS includes data on patient demographics, discharge diagnoses, and procedures using the International Classification of Diseases, 9th (ICD-9) and 10th Revision (ICD-10) diagnosis codes, as well as daily billed resource utilization for laboratory tests, imaging studies, and medications. Encrypted medical record numbers permit longitudinal identification of children across multiple visits to the same hospital. Use of de-identified PHIS data was deemed to be nonhuman subjects research; our approach to validation of ICD codes using local electronic medical record review was reviewed and approved by the Cincinnati Children’s Hospital Medical Center Institutional Review Board.

Study Population

Our study team developed an algorithm to identify children with cervical lymphadenitis and minimize misclassification using PHIS (Appendix A). All children with lymphadenitis-related ICD-9 and ICD-10 discharge diagnosis codes were eligible for inclusion. Codes were validated at a single center via electronic medical record review; clinician-documented discharge diagnosis of cervical lymphadenitis or the presence of fever and unilateral or asymmetrical neck swelling with overlying skin changes was used as the reference standard. We then excluded children who did not receive antibiotics, children who received radiologic imaging not involving the head or neck (which suggested noncervical lymphadenitis or other illness), and children who had discharge diagnosis codes for other specified conditions that are sometimes associated with enlarged cervical lymph nodes but warrant different evaluation or treatment (eg, Kawasaki disease, retropharyngeal abscess, and dental abscess; Appendix A). Our final algorithm yielded a positive predictive value of 87.5% (95% CI: 79.2%-93.4%) when ICD-9 codes were considered, and 95.1% (95% CI: 88.9%-98.4%) when ICD-10 codes were considered (Appendix A).

This algorithm was subsequently applied to the PHIS database. Children ages two months to 18 years hospitalized at participating PHIS institutions between July 2013 and December 2017 with a diagnosis of cervical lymphadenitis as per the algorithm (Appendix A) were eligible for inclusion. For children with multiple eligible admissions during the study period, we only included the first hospitalization. Children with complex chronic condition diagnosis codes9 were excluded as their clinical complexity could influence decisions around timing and modality of diagnostic imaging. In addition, we excluded children who did not have an emergency department (ED) visit associated with their hospitalization. This step was intended to exclude children who were transferred from another institution, as imaging performed at outside institutions prior to transfer is not available in PHIS. To avoid overinflating hospital-level variation in the setting of a small sample size, we also excluded all children admitted to the five hospitals with fewer than 50 cases of cervical lymphadenitis during the study period. Our final cohort consisted of 44 PHIS hospitals.

Measures of Interest

To examine hospital-level variation in imaging practices, we measured the proportion of children at each hospital who underwent any neck imaging study, CT or ultrasound imaging, early imaging, and multiple imaging studies within a single hospitalization. Neck imaging was defined as the presence of a billing code for ultrasound, CT, or magnetic resonance imaging (MRI) study of the neck (Appendix B). Early imaging was defined as neck imaging conducted on day 0 of hospitalization (ie, calendar day of admission and ending at midnight). Multiple imaging studies were defined as the receipt of more than one imaging study, regardless of timing or modality. We also measured the proportion of children by hospital who received surgical drainage, defined by the presence of procedure codes for incision and drainage of abscess of the neck (Appendix B).

In examining patient-level association between early imaging and clinical outcomes, our primary outcome of interest was the receipt of multiple imaging studies. Secondary outcomes included rates of surgical drainage, length of stay (in hospital days), and rates of lymphadenitis-related hospital readmission within 30 days of index discharge.

Covariates

Baseline demographic characteristics included age, gender, race/ethnicity, and insurance type. We measured ED visits associated with lymphadenitis-related diagnosis codes in the 30 days prior to admission as a proxy measure for illness duration prior to presentation. To approximate illness severity, we included the following covariates: rates of intensive care unit admission on presentation, rates of receipt of intravenous (IV) analgesia (Appendix B) on hospital days prior to surgical drainage, and rates of receipt of broad-spectrum antibiotics on day 0 or 1 of hospitalization. Broad-spectrum antibiotics (Appendix B) were defined by an independent three-person review of available antibiotic codes (SD, SSS, and JT); differences were resolved by group consensus.

 

 

Analysis

Categorical variables were described using frequencies and percentages, while continuous data were described using median and interquartile range. We described hospital-level variation in imaging practices by calculating and comparing the proportion of children at each hospital who underwent any neck imaging study, CT imaging, ultrasound imaging, early imaging, multiple imaging studies, and surgical drainage.

Patient-level demographics and clinical characteristics were compared across groups using chi-square test. To examine the association between early imaging and outcomes, we used generalized linear or logistic mixed effects models to control for patient demographic characteristics and clinical markers of illness duration and severity, with a random effect for hospital to account for clustering. Patient demographics in the model defined a priori included age, race/ethnicity, and insurance type; clinical characteristics included prior ED visit for lymphadenitis, initial intensive care unit (ICU) admission, use of IV analgesia, and use of broad-spectrum antibiotics on day 0 or 1 of hospitalization. To assess the potential for misclassification related to the availability of calendar day but not time of imaging in PHIS, we conducted a secondary analysis to examine the patient-level association between early imaging and outcomes using an alternative definition for early imaging (defined as imaging conducted on day 0 or day 1 of hospitalization).



All statistical analyses were performed by using SAS version 9.4 (SAS Institute, Cary, North Carolina); P < .05 was considered statistically significant.

RESULTS

We identified 19,785 PHIS hospitalizations with lymphadenitis-related discharge diagnosis codes between July 1, 2013 and December 31, 2017. Applying our algorithm and exclusion criteria, we assembled a cohort of 10,014 children hospitalized with cervical lymphadenitis (Figure 1). Two-thirds of the children in our cohort were <4 years old, 42% were non-Hispanic white, and 63% had a government payor (Table 1). Neck imaging (ultrasound, CT, or MRI) was conducted in 8,103 (81%) children. CT imaging was performed in 4,097 (41%) of children, and early imaging was conducted in 6,111 (61%) of children with cervical lymphadenitis.

We noted hospital-level variation in rates of any neck imaging (median: 82.1%, interquartile range [IQR]: 77.7%-85.5%, full range: 68.7%-93.1%), CT imaging (median: 42.3%, IQR: 26.7%-55.2%, full range: 12.0%-81.5%), early imaging (median: 64.4%, IQR: 59.8%-68.4%, full range: 13.8%-76.9%), and multiple imaging studies (median: 23.7%, IQR: 18.6%-28.9%, full range: 1.2%-40.7%; Figure 2). Rates of surgical drainage also varied by hospital (median: 35.1%, IQR: 31.3%-42.0%, full range: 17.1%-54.5%).



At the patient level, children who received early imaging were more likely to be <1 year old (21% vs 16%, P < .001), or Hispanic or Black when compared with children who did not receive early imaging (Table 1). Children who received early imaging were more likely to have had an ED visit for lymphadenitis in the preceding 30 days (8% vs 6%, P = .001). However, they were less likely to have received broad-spectrum antibiotics on admission (6% vs 8%, P < .001; Table 1). Of the 6,111 patients who received early imaging, 2,538 (41.5%) received CT imaging and 3,902 (63.9%) received ultrasound imaging on day 0. Of the 2,272 patients receiving multiple imaging studies, 116 (5.1%) received two or more CT scans.


In multivariable analysis at the patient level, early imaging was associated with higher adjusted odds of receiving multiple imaging studies (adjusted odds ratio [aOR] 3.0, 95% CI: 2.6-3.6). Similarly, early imaging was associated with higher adjusted odds of surgical drainage (aOR: 1.3, 95% CI: 1.1-1.4), increased 30-day readmission for lymphadenitis (aOR: 1.5, 95% CI: 1.2-1.9), and longer length of stay (adjusted rate ratio: 1.2, 95% CI: 1.1-1.2; Table 2). For the subset of patients who did not receive surgical drainage during the index admission, the adjusted odds ratio for the association between early imaging at index admission and 30-day readmission was 1.7 (95% CI: 1.3-2.1). About 63% of readmissions occurred within 7 days of index discharge; 89% occurred within 14 days (Appendix Figure).


In secondary analysis using an alternative definition for early imaging (ie, imaging conducted on day 0 or day 1 of hospitalization), the adjusted odds ratio for multiple imaging studies was 22.6 (95% CI: 15.8-32.4). The adjusted odds and rate ratios for the remaining outcomes were similar to our primary analysis.

 

 

DISCUSSION

In this large multicenter study of children with cervical lymphadenitis, we found variation in imaging practices across 44 US children’s hospitals. Children with cervical lymphadenitis who underwent early imaging were more likely to receive multiple imaging studies during a single hospitalization than those who did not receive early imaging. At the patient level, early imaging was also associated with higher rates of surgical drainage, more frequent 30-day readmission, and longer lengths of stay.

To our knowledge, imaging practices in the population of children hospitalized with cervical lymphadenitis have not been previously characterized in the US; one study from Atlanta, Georgia, describes imaging practices in all children evaluated in the ED.1 Single-center studies of children hospitalized with cervical lymphadenitis have been previously conducted in Canada6 and New Zealand,8 in which 42%-51% of children received imaging. In our study, most (81%) children hospitalized with lymphadenitis received some form of imaging, with 61% of all children receiving early imaging. Furthermore, 41% received CT imaging, as compared with 8%-10% of children in the aforementioned studies from Canada and New Zealand.6,8 This finding is consistent with a pattern of imaging overuse in the US, which has amongst the highest utilization rates globally for advanced imaging such as CT and MRI.10,11 Identifying opportunities to safely reduce routine imaging, particularly CT imaging, in this population could decrease unnecessary radiation exposure without compromising outcomes.

We also noted variability in imaging practices across PHIS hospitals. Some of this variability may be partially explained by differences in the patient population or illness severity across hospitals. However, given the absence of evidence-based best practices for children with cervical lymphadenitis, clinicians may rely on anecdotal experience or local practice culture to guide their decision making,12 leading to variability in frequency, timing, and modality of imaging.

At the patient level, we found that children who received early imaging were more likely to receive multiple imaging studies. This finding supports our hypothesis that clinicians often order a second imaging study when the initial imaging study does not clearly demonstrate an abscess, and the child subsequently fails to demonstrate clear improvement after 24-48 hours of antibiotics.

Furthermore, early imaging was associated with overall increased utilization in our cohort, including increased likelihood of surgical drainage, 30-day readmission for lymphadenitis, as well as longer lengths of stay. Confounding may be one explanation for this finding. For instance, clinicians may pursue early imaging in children who present with longer duration of symptoms or more severe illness on presentation, as these factors may be associated with abscess formation.1,6,7 These clinical covariates are not available in PHIS. Thus, we used prior ED visits for lymphadenitis to approximate illness duration, and initial admission to ICU, receipt of IV analgesia, and receipt of broad-spectrum antibiotics to approximate illness severity in an attempt to mitigate confounding. However, our proxy measures may not appropriately estimate illness duration and severity. For instance, children who had urgent care or outpatient visits for lymphadenitis would not be captured using the proxy of prior ED visit for lymphadenitis. Similarly, use of broad-spectrum antibiotics and IV analgesia may be influenced by provider or institutional preference rather than illness severity. Thus, residual confounding may exist despite adjusting for these measures.

On the other hand, it is also possible that a proportion of children with a small fluid collection on imaging may have improved with antibiotics alone. There is a growing body of evidence in children with other head and neck infections (eg, retropharyngeal abscess and orbital cellulitis with periosteal abscess)13-15 that suggests that children with small abscesses often improve with antibiotic therapy alone. In children with cervical lymphadenitis who have small or developing abscesses identified via routine imaging on presentation, clinicians may be driven to pursue a surgical intervention with uncertain benefit. Deferring routine imaging in this population may provide an opportunity to improve the value of care in children with lymphadenitis without adversely affecting outcomes.

Upon closer examination of readmissions, children who received early imaging during index hospitalization were more likely to have a 30-day readmission when only evaluating the subset of patients who did not receive surgical drainage during the index admission. This suggests that readmissions are less likely attributable to surgical complications and more likely a reflection of the natural history of lymphadenitis in which a subset of patients eventually develop an abscess. Further supporting this, 61% of children who had a 30-day readmission for lymphadenitis underwent surgical drainage during readmission. Given that lymphadenitis is a slow-brewing infection in which serious complications are rare, patients who demonstrate gradual clinical improvement do not need to remain hospitalized and serially imaged to identify a possible abscess. Outpatient expectant management and readmission as needed for drainage may be an acceptable approach.

This study has several limitations given our use of an administrative database. Children with lymphadenitis may have been misclassified as these patients were identified using discharge diagnosis codes. To mitigate this potential misclassification, we conducted a structured validation process and found that the included codes had high positive predictive values (Appendix A). This validation process was conducted at a single hospital, and coding may vary across hospitals. To approximate sensitivity, we also sampled children without our included codes but with neck imaging and antibiotic use, and found that rates of cervical lymphadenitis were very low among children without our included diagnosis codes.

Furthermore, we were unable to measure the exact time of imaging study in PHIS; we used imaging conducted on hospital day 0 as a proxy measure for imaging conducted within the first 24 hours of presentation. With this definition, some children who had early imaging were likely misclassified as not having received early imaging. For example, a patient who arrived in the ED at 9 pm on day 0 of admission and had a neck ultrasound performed at 1 am would be classified as having had an imaging study on day 1 of hospitalization even though the imaging study was conducted within 4 hours of presentation. Using an alternative definition of early imaging as imaging conducted on hospital day 0 and day 1, we found a much higher adjusted OR for multiple imaging studies, with similar associations for secondary outcomes. As such, our definition of early imaging as day 0 likely biases the results toward the null; the true increase in likelihood of multiple imaging for those who receive early imaging is probably greater than our conservative estimation.

Additionally, there may be a subset of children who underwent imaging prior to presentation at the PHIS hospital ED for further workup and admission. Imaging conducted outside a PHIS hospital was not captured in this database. Similarly, children who had a readmission at a different hospital than their index admission would not be captured using PHIS. Finally, PHIS captures data from children’s hospitals; practices at these hospitals may not be generalizable to practices in the community hospital setting.

 

 

CONCLUSION

In conclusion, we found that imaging practices in children hospitalized with cervical lymphadenitis were widely variable across hospitals. Children receiving early imaging had more resource utilization and intervention when compared with children who did not receive early imaging. Our findings may represent a cascade effect, in which routinely conducted early imaging prompts clinicians to pursue more testing and interventions in this population. Future studies should obtain more detailed patient level covariates to further characterize clinical factors that may impact decisions around imaging and clinical outcomes for children with cervical lymphadenitis.

Acknowledgments

The authors would like to acknowledge the following investigators for their contributions to data interpretation and review of the final manuscript: Angela Choe MD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Margaret Rush MD, Children’s National Medical Center, Washington, DC; Ryosuke Takei MD, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; Wallis Molchen DO, Texas Children’s Hospital, Houston, Texas; Stephanie Royer Moss MD, Cleveland Clinic, Cleveland, Ohio; Rebecca Dang, MD, Lucile Packard Children’s Hospital Stanford, Palo Alto, California; Joy Solano MD, Children’s Mercy Hospital Kansas, Overland Park, Kansas; Nathaniel P. Goodrich MD, Children’s Hospital & Medical Center, Omaha, Nebraska; Ngozi Eboh MD, Texas Tech University Health Sciences Center, Dallas, Texas; Ashley Jenkins MD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Rebecca Steuart MD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Sonya Tang Girdwood MD, PhD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Alissa McInerney MD, Maria Fareri Children’s Hospital at Westchester Medical Center, Valhalla, New York; Sumeet Banker MD, MPH, New York Presbyterian Morgan Stanley Children’s Hospital, New York, New York; Corrie McDaniel DO, Seattle Children’s Hospital, Seattle, Washington; Christiane Lenzen MD, Rady Children’s Hospital, San Diego, California; Aleisha Nabower MD, Children’s Hospital & Medical Center, Omaha, Nebraska; Waheeda Samady MD, Ann & Robert H. Lurie Children’s Hospital, Chicago, Illinois; Jennifer Chen MD, Rady Children’s Hospital, San Diego, California; Marquita Genies MD, MPH, John’s Hopkins Children’s Center, Baltimore, Maryland; Justin Lockwood MD, Children’s Hospital Colorado, Aurora, Colorado; David Synhorst MD, Children’s Mercy Hospital Kansas, Overland Park, Kansas.

Cervical lymphadenitis is a common superficial neck infection in childhood. While most children with cervical lymphadenitis recover with antibiotic therapy, a subset can develop an abscess that may require surgical drainage. Radiologic imaging, most commonly ultrasound or computed tomography (CT), is often performed to identify such an abscess.1-3 However, no national standards exist to guide clinician decision making around imaging in this population. In the absence of evidence-based guidelines, variability in frequency, timing, and modality of imaging likely exists in children hospitalized with cervical lymphadenitis.

As demonstrated for several other common pediatric conditions,4,5 variability in imaging practices may contribute to overutilization of resources in children with cervical lymphadenitis. In particular, routinely conducting imaging on presentation may constitute overuse, as children with cervical lymphadenitis who present with less than 72 hours of neck swelling rarely undergo surgical drainage within the first 24 hours of hospitalization.1,6,7 Imaging performed on presentation is often repeated later during hospitalization, particularly if the patient has not improved with antibiotic therapy. The net result may be unnecessary, redundant radiologic studies. Furthermore, serious complications such as bacteremia, extension of infection into the retropharyngeal space, or involvement of the airway or vasculature rarely occur in children with cervical lymphadenitis.6,8 In this context, deferring initial imaging in this population is unlikely to lead to adverse outcomes and may reduce radiation exposure.

The overall objectives of this study are to describe hospital-level variation in imaging practices for pediatric cervical lymphadenitis and to examine the association between early imaging and outcomes in this population.

METHODS

Study Design and Data Source

We conducted a multicenter, cross-sectional study using the Pediatric Health Information Systems (PHIS) database, which contains administrative and billing data from 49 geographically diverse children’s hospitals across the United States (US) affiliated with the Children’s Hospital Association (Lenexa, Kansas). PHIS includes data on patient demographics, discharge diagnoses, and procedures using the International Classification of Diseases, 9th (ICD-9) and 10th Revision (ICD-10) diagnosis codes, as well as daily billed resource utilization for laboratory tests, imaging studies, and medications. Encrypted medical record numbers permit longitudinal identification of children across multiple visits to the same hospital. Use of de-identified PHIS data was deemed to be nonhuman subjects research; our approach to validation of ICD codes using local electronic medical record review was reviewed and approved by the Cincinnati Children’s Hospital Medical Center Institutional Review Board.

Study Population

Our study team developed an algorithm to identify children with cervical lymphadenitis and minimize misclassification using PHIS (Appendix A). All children with lymphadenitis-related ICD-9 and ICD-10 discharge diagnosis codes were eligible for inclusion. Codes were validated at a single center via electronic medical record review; clinician-documented discharge diagnosis of cervical lymphadenitis or the presence of fever and unilateral or asymmetrical neck swelling with overlying skin changes was used as the reference standard. We then excluded children who did not receive antibiotics, children who received radiologic imaging not involving the head or neck (which suggested noncervical lymphadenitis or other illness), and children who had discharge diagnosis codes for other specified conditions that are sometimes associated with enlarged cervical lymph nodes but warrant different evaluation or treatment (eg, Kawasaki disease, retropharyngeal abscess, and dental abscess; Appendix A). Our final algorithm yielded a positive predictive value of 87.5% (95% CI: 79.2%-93.4%) when ICD-9 codes were considered, and 95.1% (95% CI: 88.9%-98.4%) when ICD-10 codes were considered (Appendix A).

This algorithm was subsequently applied to the PHIS database. Children ages two months to 18 years hospitalized at participating PHIS institutions between July 2013 and December 2017 with a diagnosis of cervical lymphadenitis as per the algorithm (Appendix A) were eligible for inclusion. For children with multiple eligible admissions during the study period, we only included the first hospitalization. Children with complex chronic condition diagnosis codes9 were excluded as their clinical complexity could influence decisions around timing and modality of diagnostic imaging. In addition, we excluded children who did not have an emergency department (ED) visit associated with their hospitalization. This step was intended to exclude children who were transferred from another institution, as imaging performed at outside institutions prior to transfer is not available in PHIS. To avoid overinflating hospital-level variation in the setting of a small sample size, we also excluded all children admitted to the five hospitals with fewer than 50 cases of cervical lymphadenitis during the study period. Our final cohort consisted of 44 PHIS hospitals.

Measures of Interest

To examine hospital-level variation in imaging practices, we measured the proportion of children at each hospital who underwent any neck imaging study, CT or ultrasound imaging, early imaging, and multiple imaging studies within a single hospitalization. Neck imaging was defined as the presence of a billing code for ultrasound, CT, or magnetic resonance imaging (MRI) study of the neck (Appendix B). Early imaging was defined as neck imaging conducted on day 0 of hospitalization (ie, calendar day of admission and ending at midnight). Multiple imaging studies were defined as the receipt of more than one imaging study, regardless of timing or modality. We also measured the proportion of children by hospital who received surgical drainage, defined by the presence of procedure codes for incision and drainage of abscess of the neck (Appendix B).

In examining patient-level association between early imaging and clinical outcomes, our primary outcome of interest was the receipt of multiple imaging studies. Secondary outcomes included rates of surgical drainage, length of stay (in hospital days), and rates of lymphadenitis-related hospital readmission within 30 days of index discharge.

Covariates

Baseline demographic characteristics included age, gender, race/ethnicity, and insurance type. We measured ED visits associated with lymphadenitis-related diagnosis codes in the 30 days prior to admission as a proxy measure for illness duration prior to presentation. To approximate illness severity, we included the following covariates: rates of intensive care unit admission on presentation, rates of receipt of intravenous (IV) analgesia (Appendix B) on hospital days prior to surgical drainage, and rates of receipt of broad-spectrum antibiotics on day 0 or 1 of hospitalization. Broad-spectrum antibiotics (Appendix B) were defined by an independent three-person review of available antibiotic codes (SD, SSS, and JT); differences were resolved by group consensus.

 

 

Analysis

Categorical variables were described using frequencies and percentages, while continuous data were described using median and interquartile range. We described hospital-level variation in imaging practices by calculating and comparing the proportion of children at each hospital who underwent any neck imaging study, CT imaging, ultrasound imaging, early imaging, multiple imaging studies, and surgical drainage.

Patient-level demographics and clinical characteristics were compared across groups using chi-square test. To examine the association between early imaging and outcomes, we used generalized linear or logistic mixed effects models to control for patient demographic characteristics and clinical markers of illness duration and severity, with a random effect for hospital to account for clustering. Patient demographics in the model defined a priori included age, race/ethnicity, and insurance type; clinical characteristics included prior ED visit for lymphadenitis, initial intensive care unit (ICU) admission, use of IV analgesia, and use of broad-spectrum antibiotics on day 0 or 1 of hospitalization. To assess the potential for misclassification related to the availability of calendar day but not time of imaging in PHIS, we conducted a secondary analysis to examine the patient-level association between early imaging and outcomes using an alternative definition for early imaging (defined as imaging conducted on day 0 or day 1 of hospitalization).



All statistical analyses were performed by using SAS version 9.4 (SAS Institute, Cary, North Carolina); P < .05 was considered statistically significant.

RESULTS

We identified 19,785 PHIS hospitalizations with lymphadenitis-related discharge diagnosis codes between July 1, 2013 and December 31, 2017. Applying our algorithm and exclusion criteria, we assembled a cohort of 10,014 children hospitalized with cervical lymphadenitis (Figure 1). Two-thirds of the children in our cohort were <4 years old, 42% were non-Hispanic white, and 63% had a government payor (Table 1). Neck imaging (ultrasound, CT, or MRI) was conducted in 8,103 (81%) children. CT imaging was performed in 4,097 (41%) of children, and early imaging was conducted in 6,111 (61%) of children with cervical lymphadenitis.

We noted hospital-level variation in rates of any neck imaging (median: 82.1%, interquartile range [IQR]: 77.7%-85.5%, full range: 68.7%-93.1%), CT imaging (median: 42.3%, IQR: 26.7%-55.2%, full range: 12.0%-81.5%), early imaging (median: 64.4%, IQR: 59.8%-68.4%, full range: 13.8%-76.9%), and multiple imaging studies (median: 23.7%, IQR: 18.6%-28.9%, full range: 1.2%-40.7%; Figure 2). Rates of surgical drainage also varied by hospital (median: 35.1%, IQR: 31.3%-42.0%, full range: 17.1%-54.5%).



At the patient level, children who received early imaging were more likely to be <1 year old (21% vs 16%, P < .001), or Hispanic or Black when compared with children who did not receive early imaging (Table 1). Children who received early imaging were more likely to have had an ED visit for lymphadenitis in the preceding 30 days (8% vs 6%, P = .001). However, they were less likely to have received broad-spectrum antibiotics on admission (6% vs 8%, P < .001; Table 1). Of the 6,111 patients who received early imaging, 2,538 (41.5%) received CT imaging and 3,902 (63.9%) received ultrasound imaging on day 0. Of the 2,272 patients receiving multiple imaging studies, 116 (5.1%) received two or more CT scans.


In multivariable analysis at the patient level, early imaging was associated with higher adjusted odds of receiving multiple imaging studies (adjusted odds ratio [aOR] 3.0, 95% CI: 2.6-3.6). Similarly, early imaging was associated with higher adjusted odds of surgical drainage (aOR: 1.3, 95% CI: 1.1-1.4), increased 30-day readmission for lymphadenitis (aOR: 1.5, 95% CI: 1.2-1.9), and longer length of stay (adjusted rate ratio: 1.2, 95% CI: 1.1-1.2; Table 2). For the subset of patients who did not receive surgical drainage during the index admission, the adjusted odds ratio for the association between early imaging at index admission and 30-day readmission was 1.7 (95% CI: 1.3-2.1). About 63% of readmissions occurred within 7 days of index discharge; 89% occurred within 14 days (Appendix Figure).


In secondary analysis using an alternative definition for early imaging (ie, imaging conducted on day 0 or day 1 of hospitalization), the adjusted odds ratio for multiple imaging studies was 22.6 (95% CI: 15.8-32.4). The adjusted odds and rate ratios for the remaining outcomes were similar to our primary analysis.

 

 

DISCUSSION

In this large multicenter study of children with cervical lymphadenitis, we found variation in imaging practices across 44 US children’s hospitals. Children with cervical lymphadenitis who underwent early imaging were more likely to receive multiple imaging studies during a single hospitalization than those who did not receive early imaging. At the patient level, early imaging was also associated with higher rates of surgical drainage, more frequent 30-day readmission, and longer lengths of stay.

To our knowledge, imaging practices in the population of children hospitalized with cervical lymphadenitis have not been previously characterized in the US; one study from Atlanta, Georgia, describes imaging practices in all children evaluated in the ED.1 Single-center studies of children hospitalized with cervical lymphadenitis have been previously conducted in Canada6 and New Zealand,8 in which 42%-51% of children received imaging. In our study, most (81%) children hospitalized with lymphadenitis received some form of imaging, with 61% of all children receiving early imaging. Furthermore, 41% received CT imaging, as compared with 8%-10% of children in the aforementioned studies from Canada and New Zealand.6,8 This finding is consistent with a pattern of imaging overuse in the US, which has amongst the highest utilization rates globally for advanced imaging such as CT and MRI.10,11 Identifying opportunities to safely reduce routine imaging, particularly CT imaging, in this population could decrease unnecessary radiation exposure without compromising outcomes.

We also noted variability in imaging practices across PHIS hospitals. Some of this variability may be partially explained by differences in the patient population or illness severity across hospitals. However, given the absence of evidence-based best practices for children with cervical lymphadenitis, clinicians may rely on anecdotal experience or local practice culture to guide their decision making,12 leading to variability in frequency, timing, and modality of imaging.

At the patient level, we found that children who received early imaging were more likely to receive multiple imaging studies. This finding supports our hypothesis that clinicians often order a second imaging study when the initial imaging study does not clearly demonstrate an abscess, and the child subsequently fails to demonstrate clear improvement after 24-48 hours of antibiotics.

Furthermore, early imaging was associated with overall increased utilization in our cohort, including increased likelihood of surgical drainage, 30-day readmission for lymphadenitis, as well as longer lengths of stay. Confounding may be one explanation for this finding. For instance, clinicians may pursue early imaging in children who present with longer duration of symptoms or more severe illness on presentation, as these factors may be associated with abscess formation.1,6,7 These clinical covariates are not available in PHIS. Thus, we used prior ED visits for lymphadenitis to approximate illness duration, and initial admission to ICU, receipt of IV analgesia, and receipt of broad-spectrum antibiotics to approximate illness severity in an attempt to mitigate confounding. However, our proxy measures may not appropriately estimate illness duration and severity. For instance, children who had urgent care or outpatient visits for lymphadenitis would not be captured using the proxy of prior ED visit for lymphadenitis. Similarly, use of broad-spectrum antibiotics and IV analgesia may be influenced by provider or institutional preference rather than illness severity. Thus, residual confounding may exist despite adjusting for these measures.

On the other hand, it is also possible that a proportion of children with a small fluid collection on imaging may have improved with antibiotics alone. There is a growing body of evidence in children with other head and neck infections (eg, retropharyngeal abscess and orbital cellulitis with periosteal abscess)13-15 that suggests that children with small abscesses often improve with antibiotic therapy alone. In children with cervical lymphadenitis who have small or developing abscesses identified via routine imaging on presentation, clinicians may be driven to pursue a surgical intervention with uncertain benefit. Deferring routine imaging in this population may provide an opportunity to improve the value of care in children with lymphadenitis without adversely affecting outcomes.

Upon closer examination of readmissions, children who received early imaging during index hospitalization were more likely to have a 30-day readmission when only evaluating the subset of patients who did not receive surgical drainage during the index admission. This suggests that readmissions are less likely attributable to surgical complications and more likely a reflection of the natural history of lymphadenitis in which a subset of patients eventually develop an abscess. Further supporting this, 61% of children who had a 30-day readmission for lymphadenitis underwent surgical drainage during readmission. Given that lymphadenitis is a slow-brewing infection in which serious complications are rare, patients who demonstrate gradual clinical improvement do not need to remain hospitalized and serially imaged to identify a possible abscess. Outpatient expectant management and readmission as needed for drainage may be an acceptable approach.

This study has several limitations given our use of an administrative database. Children with lymphadenitis may have been misclassified as these patients were identified using discharge diagnosis codes. To mitigate this potential misclassification, we conducted a structured validation process and found that the included codes had high positive predictive values (Appendix A). This validation process was conducted at a single hospital, and coding may vary across hospitals. To approximate sensitivity, we also sampled children without our included codes but with neck imaging and antibiotic use, and found that rates of cervical lymphadenitis were very low among children without our included diagnosis codes.

Furthermore, we were unable to measure the exact time of imaging study in PHIS; we used imaging conducted on hospital day 0 as a proxy measure for imaging conducted within the first 24 hours of presentation. With this definition, some children who had early imaging were likely misclassified as not having received early imaging. For example, a patient who arrived in the ED at 9 pm on day 0 of admission and had a neck ultrasound performed at 1 am would be classified as having had an imaging study on day 1 of hospitalization even though the imaging study was conducted within 4 hours of presentation. Using an alternative definition of early imaging as imaging conducted on hospital day 0 and day 1, we found a much higher adjusted OR for multiple imaging studies, with similar associations for secondary outcomes. As such, our definition of early imaging as day 0 likely biases the results toward the null; the true increase in likelihood of multiple imaging for those who receive early imaging is probably greater than our conservative estimation.

Additionally, there may be a subset of children who underwent imaging prior to presentation at the PHIS hospital ED for further workup and admission. Imaging conducted outside a PHIS hospital was not captured in this database. Similarly, children who had a readmission at a different hospital than their index admission would not be captured using PHIS. Finally, PHIS captures data from children’s hospitals; practices at these hospitals may not be generalizable to practices in the community hospital setting.

 

 

CONCLUSION

In conclusion, we found that imaging practices in children hospitalized with cervical lymphadenitis were widely variable across hospitals. Children receiving early imaging had more resource utilization and intervention when compared with children who did not receive early imaging. Our findings may represent a cascade effect, in which routinely conducted early imaging prompts clinicians to pursue more testing and interventions in this population. Future studies should obtain more detailed patient level covariates to further characterize clinical factors that may impact decisions around imaging and clinical outcomes for children with cervical lymphadenitis.

Acknowledgments

The authors would like to acknowledge the following investigators for their contributions to data interpretation and review of the final manuscript: Angela Choe MD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Margaret Rush MD, Children’s National Medical Center, Washington, DC; Ryosuke Takei MD, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania; Wallis Molchen DO, Texas Children’s Hospital, Houston, Texas; Stephanie Royer Moss MD, Cleveland Clinic, Cleveland, Ohio; Rebecca Dang, MD, Lucile Packard Children’s Hospital Stanford, Palo Alto, California; Joy Solano MD, Children’s Mercy Hospital Kansas, Overland Park, Kansas; Nathaniel P. Goodrich MD, Children’s Hospital & Medical Center, Omaha, Nebraska; Ngozi Eboh MD, Texas Tech University Health Sciences Center, Dallas, Texas; Ashley Jenkins MD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Rebecca Steuart MD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Sonya Tang Girdwood MD, PhD, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio; Alissa McInerney MD, Maria Fareri Children’s Hospital at Westchester Medical Center, Valhalla, New York; Sumeet Banker MD, MPH, New York Presbyterian Morgan Stanley Children’s Hospital, New York, New York; Corrie McDaniel DO, Seattle Children’s Hospital, Seattle, Washington; Christiane Lenzen MD, Rady Children’s Hospital, San Diego, California; Aleisha Nabower MD, Children’s Hospital & Medical Center, Omaha, Nebraska; Waheeda Samady MD, Ann & Robert H. Lurie Children’s Hospital, Chicago, Illinois; Jennifer Chen MD, Rady Children’s Hospital, San Diego, California; Marquita Genies MD, MPH, John’s Hopkins Children’s Center, Baltimore, Maryland; Justin Lockwood MD, Children’s Hospital Colorado, Aurora, Colorado; David Synhorst MD, Children’s Mercy Hospital Kansas, Overland Park, Kansas.

References

1. Sauer MW, Sharma S, Hirsh DA et al. Acute neck infections in children: who is likely to undergo surgical drainage? Am J Emerg Med. 2013;31(6):906-909. https://doi.org/10.1016/j.ajem.2013.02.043.
2. Sethia R, Mahida JB, Subbarayan RA, et al. Evaluation of an imaging protocol using ultrasound as the primary diagnostic modality in pediatric patients with superficial soft tissue infections of the face and neck. Int J Pediatr Otorhinolaryngol. 2017;96:89-93. https://doi.org/10.1016/j.ijporl.2017.02.027.
3. Neff L, Newland JG, Sykes KJ, Selvarangan R, Wei JL. Microbiology and antimicrobial treatment of pediatric cervical lymphadenitis requiring surgical intervention. Int J Pediatr Otorhinolaryngol. 2013;77(5):817-820. https://doi.org/10.1016/j.ijporl.2013.02.018.
4. Brogan TV, Hall M, Williams DJ, et al. Variability in processes of care and outcomes among children hospitalized with community-acquired pneumonia. Pediatr Infect Dis J. 2012;31(10):1036-1041. https://doi.org/10.1097/INF.0b013e31825f2b10.
5. Conway PH, Keren R. Factors associated with variability in outcomes for children hospitalized with urinary tract infection. J Pediatr. 2009;154(6):789-796. https://doi.org/10.1016/j.jpeds.2009.01.010.
6. Luu TM, Chevalier I, Gauthier M et al. Acute adenitis in children: clinical course and factors predictive of surgical drainage. J Paediatr Child Health. 2005;41(5-6):273-277. https://doi.org/10.1111/j.1440-1754.2005.00610.x.
7. Golriz F, Bisset GS, 3rd, D’Amico B, et al. A clinical decision rule for the use of ultrasound in children presenting with acute inflammatory neck masses. Pediatr Rad. 2017;47(4):422-428. https://doi.org/10.1007/s00247-016-3774-9.
8. Courtney MJ, Miteff A, Mahadevan M. Management of pediatric lateral neck infections: does the adage “… never let the sun go down on undrained pus …” hold true? Int J Pediatr Otorhinolaryngol. 2007;71(1):95-100. https://doi.org/10.1016/j.ijporl.2006.09.009.
9. Feudtner C, Feinstein JA, Zhong W, Hall M, Dai D. Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199. https://doi.org/10.1186/1471-2431-14-199.
10. Papanicolas I, Woskie LR, Jha AK. Health care spending in the United States and other high-income countries. JAMA. 2018;319(10):1024-1039. https://doi.org/10.1001/jama.2018.1150.
11. Oren O, Kebebew E, Ioannidis JPA. Curbing unnecessary and wasted diagnostic imaging. JAMA. 2019;321(3):245-246. https://doi.org/10.1001/jama.2018.20295.
12. Palmer RH, Miller MR. Methodologic challenges in developing and implementing measures of quality for child health care. Ambul Pediatr Off J Ambul Pediatr Assoc. 2001;1(1):39-52. https://doi.org/10.1367/1539-4409(2001)001<0039:MCIDAI>2.0.CO;2.
13. Daya H, Lo S, Papsin BC, et al. Retropharyngeal and parapharyngeal infections in children: the Toronto experience. Int J Pediatr Otorhinolaryngol. 2005;69(1):81-86. https://doi.org/10.1016/j.ijporl.2004.08.010.
14. Wong SJ, Levi J. Management of pediatric orbital cellulitis: A systematic review. Int J Pediatr Otorhinolaryngol. 2018;110:123-129. https://doi.org/10.1016/j.ijporl.2018.05.006.
15. Wong DK, Brown C, Mills N, Spielmann P, Neeff M. To drain or not to drain-management of pediatric deep neck abscesses: a case-control study. Int J Pediatr Otorhinolaryngol. 2012;76(12):1810-1813. https://doi.org/10.1016/j.ijporl.2012.09.006.

References

1. Sauer MW, Sharma S, Hirsh DA et al. Acute neck infections in children: who is likely to undergo surgical drainage? Am J Emerg Med. 2013;31(6):906-909. https://doi.org/10.1016/j.ajem.2013.02.043.
2. Sethia R, Mahida JB, Subbarayan RA, et al. Evaluation of an imaging protocol using ultrasound as the primary diagnostic modality in pediatric patients with superficial soft tissue infections of the face and neck. Int J Pediatr Otorhinolaryngol. 2017;96:89-93. https://doi.org/10.1016/j.ijporl.2017.02.027.
3. Neff L, Newland JG, Sykes KJ, Selvarangan R, Wei JL. Microbiology and antimicrobial treatment of pediatric cervical lymphadenitis requiring surgical intervention. Int J Pediatr Otorhinolaryngol. 2013;77(5):817-820. https://doi.org/10.1016/j.ijporl.2013.02.018.
4. Brogan TV, Hall M, Williams DJ, et al. Variability in processes of care and outcomes among children hospitalized with community-acquired pneumonia. Pediatr Infect Dis J. 2012;31(10):1036-1041. https://doi.org/10.1097/INF.0b013e31825f2b10.
5. Conway PH, Keren R. Factors associated with variability in outcomes for children hospitalized with urinary tract infection. J Pediatr. 2009;154(6):789-796. https://doi.org/10.1016/j.jpeds.2009.01.010.
6. Luu TM, Chevalier I, Gauthier M et al. Acute adenitis in children: clinical course and factors predictive of surgical drainage. J Paediatr Child Health. 2005;41(5-6):273-277. https://doi.org/10.1111/j.1440-1754.2005.00610.x.
7. Golriz F, Bisset GS, 3rd, D’Amico B, et al. A clinical decision rule for the use of ultrasound in children presenting with acute inflammatory neck masses. Pediatr Rad. 2017;47(4):422-428. https://doi.org/10.1007/s00247-016-3774-9.
8. Courtney MJ, Miteff A, Mahadevan M. Management of pediatric lateral neck infections: does the adage “… never let the sun go down on undrained pus …” hold true? Int J Pediatr Otorhinolaryngol. 2007;71(1):95-100. https://doi.org/10.1016/j.ijporl.2006.09.009.
9. Feudtner C, Feinstein JA, Zhong W, Hall M, Dai D. Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation. BMC Pediatr. 2014;14:199. https://doi.org/10.1186/1471-2431-14-199.
10. Papanicolas I, Woskie LR, Jha AK. Health care spending in the United States and other high-income countries. JAMA. 2018;319(10):1024-1039. https://doi.org/10.1001/jama.2018.1150.
11. Oren O, Kebebew E, Ioannidis JPA. Curbing unnecessary and wasted diagnostic imaging. JAMA. 2019;321(3):245-246. https://doi.org/10.1001/jama.2018.20295.
12. Palmer RH, Miller MR. Methodologic challenges in developing and implementing measures of quality for child health care. Ambul Pediatr Off J Ambul Pediatr Assoc. 2001;1(1):39-52. https://doi.org/10.1367/1539-4409(2001)001<0039:MCIDAI>2.0.CO;2.
13. Daya H, Lo S, Papsin BC, et al. Retropharyngeal and parapharyngeal infections in children: the Toronto experience. Int J Pediatr Otorhinolaryngol. 2005;69(1):81-86. https://doi.org/10.1016/j.ijporl.2004.08.010.
14. Wong SJ, Levi J. Management of pediatric orbital cellulitis: A systematic review. Int J Pediatr Otorhinolaryngol. 2018;110:123-129. https://doi.org/10.1016/j.ijporl.2018.05.006.
15. Wong DK, Brown C, Mills N, Spielmann P, Neeff M. To drain or not to drain-management of pediatric deep neck abscesses: a case-control study. Int J Pediatr Otorhinolaryngol. 2012;76(12):1810-1813. https://doi.org/10.1016/j.ijporl.2012.09.006.

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Journal of Hospital Medicine 15(4)
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Journal of Hospital Medicine 15(4)
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197-203. Published Online First November 20, 2019
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197-203. Published Online First November 20, 2019
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