4.6 Article Proceedings Paper

The relationship between hospital surgical case volumes and mortality rates in pediatric cardiac surgery: A national sample, 1988-2005

Journal

ANNALS OF THORACIC SURGERY
Volume 86, Issue 3, Pages 889-896

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.athoracsur.2008.04.077

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Background. Overall surgical volumes and raw mortality rates are frequently used to compare pediatric cardiac surgical programs, but unadjusted comparisons are potentially unreliable. We sought to quantify the relationship between hospital volume and pediatric cardiac surgical mortality. Methods. Pediatric cardiac operations assigned to Risk Adjustment for Congenital Heart Surgery, version 1 (RACHS-1) categories were retrospectively identified by International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) coding from the Nationwide Inpatient Sample, 1988 -2005. Hospitals were grouped by yearly pediatric cardiac surgical volume (very small, <= 20; small, 21 to 100; medium, 101 to 200; large, > 200). Mortality rates were adjusted for surgical volume, case mix (RACHS-1 categories), patient age, and year of operation by logistic regression. Results. We identified 55,164 operations from 307 hospitals; 188 (61%) performed 20 or fewer cases per year. The unadjusted mortality rate at very small hospitals was no different than at large hospitals (odds ratio, 1.0, 95% confidence interval [CI] 0.7 to 1.4). After adjustment for RACHS-1 category and age, large hospitals performed significantly better than all other volume groups. As a discriminator of mortality, volume performed significantly worse than a model with RACHS-1 category and age (receiver operating characteristic [ROC] curve area, 0.60 vs 0.81). Conclusions. As a discriminator of mortality, volume alone was only marginally better than a coin flip (ROC curve area of 0.50). However, large-volume hospitals performed more complex operations and achieved superior results; therefore, the use of overall, unadjusted mortality rates to evaluate institution quality is misleading. Hospital comparisons and pay-for-performance initiatives must be based on robust risk-adjusted comparisons.

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