Arjun K Venkatesh1, Ying Dai, Joseph S Ross, Jeremiah D Schuur, Roberta Capp, Harlan M Krumholz. 1. *Robert Wood Johnson Clinical Scholars Program †Department of Emergency Medicine, Yale University School of Medicine ‡Center for Outcomes Research and Evaluation, Yale-New Haven Hospital §Department of Internal Medicine, Section of General Internal Medicine, Yale University School of Medicine ∥Department of Health Policy and Management, Yale School of Public Health, New Haven, CT ¶Department of Emergency Medicine, Brigham and Women's Hospital, Boston, MA #Department of Emergency Medicine, University of Colorado School of Medicine, Denver, CO **Department of Internal Medicine, Section of Cardiovascular Medicine, Yale University School of Medicine, New Haven, CT.
Abstract
BACKGROUND: Variation in hospitalization rates have been described for decades, yet little is known about variation in emergency department (ED) admission rates across clinical conditions. We sought to describe variation in ED risk-standardized admission rates (RSAR) and the consistency between condition-specific ED admission rates within hospitals. METHODS: Cross-sectional analysis of the 2009 National Emergency Department Sample, an all-payer administrative, claims dataset. We identify the 15 most frequently admitted conditions using Clinical Classification Software. To identify conditions with the highest ED RSAR variation, we compared both the ratio of the 75th percentile to the 25th percentile hospital and coefficient of variation between conditions. We calculate Spearman correlation coefficients to assess within-hospital correlation of condition-specific ED RSARs. RESULTS: Of 21,885,845 adult ED visits, 4,470,105 (20%) resulted in admission. Among the 15 most frequently admitted conditions, the 5 with the highest magnitude of variation were: mood disorders (ratio of 75th:25th percentile, 6.97; coefficient of variation, 0.81), nonspecific chest pain (2.68; 0.66), skin and soft tissue infections (1.82; 0.51), urinary tract infections (1.58; 0.43), and chronic obstructive pulmonary disease (1.57; 0.33). For these 5 conditions, the within-hospital RSAR correlations between each pair of conditions were >0.4, except for mood disorders, which was poorly correlated with all other conditions (r<0.3). CONCLUSIONS: There is significant condition-specific variation in ED admission rates across US hospitals. This variation appears to be consistent between conditions with high variation within hospitals.
BACKGROUND: Variation in hospitalization rates have been described for decades, yet little is known about variation in emergency department (ED) admission rates across clinical conditions. We sought to describe variation in ED risk-standardized admission rates (RSAR) and the consistency between condition-specific ED admission rates within hospitals. METHODS: Cross-sectional analysis of the 2009 National Emergency Department Sample, an all-payer administrative, claims dataset. We identify the 15 most frequently admitted conditions using Clinical Classification Software. To identify conditions with the highest ED RSAR variation, we compared both the ratio of the 75th percentile to the 25th percentile hospital and coefficient of variation between conditions. We calculate Spearman correlation coefficients to assess within-hospital correlation of condition-specific ED RSARs. RESULTS: Of 21,885,845 adult ED visits, 4,470,105 (20%) resulted in admission. Among the 15 most frequently admitted conditions, the 5 with the highest magnitude of variation were: mood disorders (ratio of 75th:25th percentile, 6.97; coefficient of variation, 0.81), nonspecific chest pain (2.68; 0.66), skin and soft tissue infections (1.82; 0.51), urinary tract infections (1.58; 0.43), and chronic obstructive pulmonary disease (1.57; 0.33). For these 5 conditions, the within-hospital RSAR correlations between each pair of conditions were >0.4, except for mood disorders, which was poorly correlated with all other conditions (r<0.3). CONCLUSIONS: There is significant condition-specific variation in ED admission rates across US hospitals. This variation appears to be consistent between conditions with high variation within hospitals.
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