Patterns of Hospital Performance on the Hospital-Wide 30-Day Readmission Metric: Is the Playing Field Level?

Erik Hans Hoyer, William Padula, Daniel Brotman, Natalie Reid, Curtis Leung, Diane Lepley, Amy Deutschendorf

Research output: Contribution to journalArticle

Abstract

Background: Hospital performance on the 30-day hospital-wide readmission (HWR) metric as calculated by the Centers for Medicare and Medicaid Services (CMS) is currently reported as a quality measure. Focusing on patient-level factors may provide an incomplete picture of readmission risk at the hospital level to explain variations in hospital readmission rates. Objective: To evaluate and quantify hospital-level characteristics that track with hospital performance on the current HWR metric. Design: Retrospective cohort study. Setting/Patients: A total of 4785 US hospitals. Metrics: We linked publically available data on individual hospitals published by CMS on patient-level adjusted 30-day HWR rates from July 1, 2011, through June 30, 2014, to the 2014 American Hospital Association annual survey. Primary outcome was performance in the worst CMS-calculated HWR quartile. Primary hospital-level exposure variables were defined as: size (total number of beds), safety net status (top quartile of disproportionate share), academic status [member of the Association of American Medical Colleges (AAMC)], National Cancer Institute Comprehensive Cancer Center (NCI-CCC) status, and hospital services offered (e.g., transplant, hospice, emergency department). Multilevel regression was used to evaluate the association between 30-day HWR and the hospital-level factors. Results: Hospital-level characteristics significantly associated with performing in the worst CMS-calculated HWR quartile included: safety net status [adjusted odds ratio (aOR) 1.99, 95% confidence interval (95% CI) 1.61–2.45, p < 0.001], large size (> 400 beds, aOR 1.42, 95% CI 1.07–1.90, p = 0.016), AAMC alone status (aOR 1.95, 95% CI 1.35–2.83, p < 0.001), and AAMC plus NCI-CCC status (aOR 5.16, 95% CI 2.58–10.31, p < 0.001). Hospitals with more critical care beds (aOR 1.26, 95% CI 1.02–1.56, p = 0.033), those with transplant services (aOR 2.80, 95% CI 1.48–5.31,p = 0.001), and those with emergency room services (aOR 3.37, 95% CI 1.12–10.15, p = 0.031) demonstrated significantly worse HWR performance. Hospice service (aOR 0.64, 95% CI 0.50–0.82, p < 0.001) and having a higher proportion of total discharges being surgical cases (aOR 0.62, 95% CI 0.50–0.76, p < 0.001) were associated with better performance. Limitation: The study approach was not intended to be an alternate readmission metric to compete with the existing CMS metric, which would require a re-examination of patient-level data combined with hospital-level data. Conclusion: A number of hospital-level characteristics (such as academic tertiary care center status) were significantly associated with worse performance on the CMS-calculated HWR metric, which may have important health policy implications. Until the reasons for readmission variability can be addressed, reporting the current HWR metric as an indicator of hospital quality should be reevaluated.

Original languageEnglish (US)
Pages (from-to)57-64
Number of pages8
JournalJournal of General Internal Medicine
Volume33
Issue number1
DOIs
StatePublished - Jan 1 2018

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Patient Readmission
Centers for Medicare and Medicaid Services (U.S.)
Odds Ratio
Confidence Intervals
Hospices
National Cancer Institute (U.S.)
Hospital Emergency Service
American Hospital Association
Transplants
Safety
American Medical Association
Critical Care
Health Policy
Tertiary Care Centers
Neoplasms
Cohort Studies
Retrospective Studies

ASJC Scopus subject areas

  • Internal Medicine

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Patterns of Hospital Performance on the Hospital-Wide 30-Day Readmission Metric : Is the Playing Field Level? / Hoyer, Erik Hans; Padula, William; Brotman, Daniel; Reid, Natalie; Leung, Curtis; Lepley, Diane; Deutschendorf, Amy.

In: Journal of General Internal Medicine, Vol. 33, No. 1, 01.01.2018, p. 57-64.

Research output: Contribution to journalArticle

Hoyer, Erik Hans ; Padula, William ; Brotman, Daniel ; Reid, Natalie ; Leung, Curtis ; Lepley, Diane ; Deutschendorf, Amy. / Patterns of Hospital Performance on the Hospital-Wide 30-Day Readmission Metric : Is the Playing Field Level?. In: Journal of General Internal Medicine. 2018 ; Vol. 33, No. 1. pp. 57-64.
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title = "Patterns of Hospital Performance on the Hospital-Wide 30-Day Readmission Metric: Is the Playing Field Level?",
abstract = "Background: Hospital performance on the 30-day hospital-wide readmission (HWR) metric as calculated by the Centers for Medicare and Medicaid Services (CMS) is currently reported as a quality measure. Focusing on patient-level factors may provide an incomplete picture of readmission risk at the hospital level to explain variations in hospital readmission rates. Objective: To evaluate and quantify hospital-level characteristics that track with hospital performance on the current HWR metric. Design: Retrospective cohort study. Setting/Patients: A total of 4785 US hospitals. Metrics: We linked publically available data on individual hospitals published by CMS on patient-level adjusted 30-day HWR rates from July 1, 2011, through June 30, 2014, to the 2014 American Hospital Association annual survey. Primary outcome was performance in the worst CMS-calculated HWR quartile. Primary hospital-level exposure variables were defined as: size (total number of beds), safety net status (top quartile of disproportionate share), academic status [member of the Association of American Medical Colleges (AAMC)], National Cancer Institute Comprehensive Cancer Center (NCI-CCC) status, and hospital services offered (e.g., transplant, hospice, emergency department). Multilevel regression was used to evaluate the association between 30-day HWR and the hospital-level factors. Results: Hospital-level characteristics significantly associated with performing in the worst CMS-calculated HWR quartile included: safety net status [adjusted odds ratio (aOR) 1.99, 95{\%} confidence interval (95{\%} CI) 1.61–2.45, p < 0.001], large size (> 400 beds, aOR 1.42, 95{\%} CI 1.07–1.90, p = 0.016), AAMC alone status (aOR 1.95, 95{\%} CI 1.35–2.83, p < 0.001), and AAMC plus NCI-CCC status (aOR 5.16, 95{\%} CI 2.58–10.31, p < 0.001). Hospitals with more critical care beds (aOR 1.26, 95{\%} CI 1.02–1.56, p = 0.033), those with transplant services (aOR 2.80, 95{\%} CI 1.48–5.31,p = 0.001), and those with emergency room services (aOR 3.37, 95{\%} CI 1.12–10.15, p = 0.031) demonstrated significantly worse HWR performance. Hospice service (aOR 0.64, 95{\%} CI 0.50–0.82, p < 0.001) and having a higher proportion of total discharges being surgical cases (aOR 0.62, 95{\%} CI 0.50–0.76, p < 0.001) were associated with better performance. Limitation: The study approach was not intended to be an alternate readmission metric to compete with the existing CMS metric, which would require a re-examination of patient-level data combined with hospital-level data. Conclusion: A number of hospital-level characteristics (such as academic tertiary care center status) were significantly associated with worse performance on the CMS-calculated HWR metric, which may have important health policy implications. Until the reasons for readmission variability can be addressed, reporting the current HWR metric as an indicator of hospital quality should be reevaluated.",
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TY - JOUR

T1 - Patterns of Hospital Performance on the Hospital-Wide 30-Day Readmission Metric

T2 - Is the Playing Field Level?

AU - Hoyer, Erik Hans

AU - Padula, William

AU - Brotman, Daniel

AU - Reid, Natalie

AU - Leung, Curtis

AU - Lepley, Diane

AU - Deutschendorf, Amy

PY - 2018/1/1

Y1 - 2018/1/1

N2 - Background: Hospital performance on the 30-day hospital-wide readmission (HWR) metric as calculated by the Centers for Medicare and Medicaid Services (CMS) is currently reported as a quality measure. Focusing on patient-level factors may provide an incomplete picture of readmission risk at the hospital level to explain variations in hospital readmission rates. Objective: To evaluate and quantify hospital-level characteristics that track with hospital performance on the current HWR metric. Design: Retrospective cohort study. Setting/Patients: A total of 4785 US hospitals. Metrics: We linked publically available data on individual hospitals published by CMS on patient-level adjusted 30-day HWR rates from July 1, 2011, through June 30, 2014, to the 2014 American Hospital Association annual survey. Primary outcome was performance in the worst CMS-calculated HWR quartile. Primary hospital-level exposure variables were defined as: size (total number of beds), safety net status (top quartile of disproportionate share), academic status [member of the Association of American Medical Colleges (AAMC)], National Cancer Institute Comprehensive Cancer Center (NCI-CCC) status, and hospital services offered (e.g., transplant, hospice, emergency department). Multilevel regression was used to evaluate the association between 30-day HWR and the hospital-level factors. Results: Hospital-level characteristics significantly associated with performing in the worst CMS-calculated HWR quartile included: safety net status [adjusted odds ratio (aOR) 1.99, 95% confidence interval (95% CI) 1.61–2.45, p < 0.001], large size (> 400 beds, aOR 1.42, 95% CI 1.07–1.90, p = 0.016), AAMC alone status (aOR 1.95, 95% CI 1.35–2.83, p < 0.001), and AAMC plus NCI-CCC status (aOR 5.16, 95% CI 2.58–10.31, p < 0.001). Hospitals with more critical care beds (aOR 1.26, 95% CI 1.02–1.56, p = 0.033), those with transplant services (aOR 2.80, 95% CI 1.48–5.31,p = 0.001), and those with emergency room services (aOR 3.37, 95% CI 1.12–10.15, p = 0.031) demonstrated significantly worse HWR performance. Hospice service (aOR 0.64, 95% CI 0.50–0.82, p < 0.001) and having a higher proportion of total discharges being surgical cases (aOR 0.62, 95% CI 0.50–0.76, p < 0.001) were associated with better performance. Limitation: The study approach was not intended to be an alternate readmission metric to compete with the existing CMS metric, which would require a re-examination of patient-level data combined with hospital-level data. Conclusion: A number of hospital-level characteristics (such as academic tertiary care center status) were significantly associated with worse performance on the CMS-calculated HWR metric, which may have important health policy implications. Until the reasons for readmission variability can be addressed, reporting the current HWR metric as an indicator of hospital quality should be reevaluated.

AB - Background: Hospital performance on the 30-day hospital-wide readmission (HWR) metric as calculated by the Centers for Medicare and Medicaid Services (CMS) is currently reported as a quality measure. Focusing on patient-level factors may provide an incomplete picture of readmission risk at the hospital level to explain variations in hospital readmission rates. Objective: To evaluate and quantify hospital-level characteristics that track with hospital performance on the current HWR metric. Design: Retrospective cohort study. Setting/Patients: A total of 4785 US hospitals. Metrics: We linked publically available data on individual hospitals published by CMS on patient-level adjusted 30-day HWR rates from July 1, 2011, through June 30, 2014, to the 2014 American Hospital Association annual survey. Primary outcome was performance in the worst CMS-calculated HWR quartile. Primary hospital-level exposure variables were defined as: size (total number of beds), safety net status (top quartile of disproportionate share), academic status [member of the Association of American Medical Colleges (AAMC)], National Cancer Institute Comprehensive Cancer Center (NCI-CCC) status, and hospital services offered (e.g., transplant, hospice, emergency department). Multilevel regression was used to evaluate the association between 30-day HWR and the hospital-level factors. Results: Hospital-level characteristics significantly associated with performing in the worst CMS-calculated HWR quartile included: safety net status [adjusted odds ratio (aOR) 1.99, 95% confidence interval (95% CI) 1.61–2.45, p < 0.001], large size (> 400 beds, aOR 1.42, 95% CI 1.07–1.90, p = 0.016), AAMC alone status (aOR 1.95, 95% CI 1.35–2.83, p < 0.001), and AAMC plus NCI-CCC status (aOR 5.16, 95% CI 2.58–10.31, p < 0.001). Hospitals with more critical care beds (aOR 1.26, 95% CI 1.02–1.56, p = 0.033), those with transplant services (aOR 2.80, 95% CI 1.48–5.31,p = 0.001), and those with emergency room services (aOR 3.37, 95% CI 1.12–10.15, p = 0.031) demonstrated significantly worse HWR performance. Hospice service (aOR 0.64, 95% CI 0.50–0.82, p < 0.001) and having a higher proportion of total discharges being surgical cases (aOR 0.62, 95% CI 0.50–0.76, p < 0.001) were associated with better performance. Limitation: The study approach was not intended to be an alternate readmission metric to compete with the existing CMS metric, which would require a re-examination of patient-level data combined with hospital-level data. Conclusion: A number of hospital-level characteristics (such as academic tertiary care center status) were significantly associated with worse performance on the CMS-calculated HWR metric, which may have important health policy implications. Until the reasons for readmission variability can be addressed, reporting the current HWR metric as an indicator of hospital quality should be reevaluated.

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