Michael P DeWane1, Nitin Sukumar, Marilyn J Stolar, Thomas M Gill, Adrian A Maung, Kevin M Schuster, Kimberly A Davis, Robert D Becher. 1. From the Division of General Surgery, Trauma, and Surgical Critical Care, Department of Surgery (M.P.D., A.A.M., K.M.S., K.A.D., R.D.B.), Yale School of Medicine, New Haven, Connecticut; Yale Center for Analytical Sciences, Yale School of Public Health (N.S., M.J.S.), New Haven, Connecticut; and Section of Geriatrics, Department of Internal Medicine (T.M.G.), Yale School of Medicine, New Haven, Connecticut.
Abstract
BACKGROUND: There is a longstanding interest in the field of management science to study high performance organizations. Applied to medicine, research on hospital performance indicates that some hospitals are high performing, while others are not. The objective of this study was to identify a cluster of high-performing emergency general surgery (EGS) hospitals and assess whether high performance at one EGS operation was associated with high performance on all EGS operations. METHODS: Adult patients who underwent one of eight EGS operations were identified in the California State Inpatient Database (2010-2011), which we linked to the American Hospital Association database. Beta regression was used to estimate a hospital's risk-adjusted mortality, accounting for patient- and hospital-level factors. Centroid cluster analysis grouped hospitals by patterns of mortality rates across the eight EGS operations using z scores. Multinomial logistic regression compared hospital characteristics by cluster. RESULTS: A total of 220 acute care hospitals were included. Three distinct clusters of hospitals were defined based on assessment of mortality for each operation type: high-performing hospitals (n = 66), average performing (n = 99), and low performing (n = 55). The mortality by individual operation type at the high-performing cluster was consistently at least 1.5 standard deviations better than the low-performing cluster (p < 0.001). Within-cluster variation was minimal at high-performing hospitals compared with wide variation at low-performing hospitals. A hospital's high performance in one EGS operation type predicted high performance on all EGS operation types. CONCLUSION: High-performing EGS hospitals attain excellence across all types of EGS operations, with minimal variability in mortality. Poor-performing hospitals are persistently below average, even for low-risk operations. These findings suggest that top-performing EGS hospitals are highly reliable, with systems of care in place to achieve consistently superior results. Further investigation and collaboration are needed to identify the factors associated with high performance. LEVEL OF EVIDENCE: Prognostic, level III.
BACKGROUND: There is a longstanding interest in the field of management science to study high performance organizations. Applied to medicine, research on hospital performance indicates that some hospitals are high performing, while others are not. The objective of this study was to identify a cluster of high-performing emergency general surgery (EGS) hospitals and assess whether high performance at one EGS operation was associated with high performance on all EGS operations. METHODS: Adult patients who underwent one of eight EGS operations were identified in the California State Inpatient Database (2010-2011), which we linked to the American Hospital Association database. Beta regression was used to estimate a hospital's risk-adjusted mortality, accounting for patient- and hospital-level factors. Centroid cluster analysis grouped hospitals by patterns of mortality rates across the eight EGS operations using z scores. Multinomial logistic regression compared hospital characteristics by cluster. RESULTS: A total of 220 acute care hospitals were included. Three distinct clusters of hospitals were defined based on assessment of mortality for each operation type: high-performing hospitals (n = 66), average performing (n = 99), and low performing (n = 55). The mortality by individual operation type at the high-performing cluster was consistently at least 1.5 standard deviations better than the low-performing cluster (p < 0.001). Within-cluster variation was minimal at high-performing hospitals compared with wide variation at low-performing hospitals. A hospital's high performance in one EGS operation type predicted high performance on all EGS operation types. CONCLUSION: High-performing EGS hospitals attain excellence across all types of EGS operations, with minimal variability in mortality. Poor-performing hospitals are persistently below average, even for low-risk operations. These findings suggest that top-performing EGS hospitals are highly reliable, with systems of care in place to achieve consistently superior results. Further investigation and collaboration are needed to identify the factors associated with high performance. LEVEL OF EVIDENCE: Prognostic, level III.
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