An analysis of publicly reported pediatric heart surgery data and patient mortality implications
Year: 2018
Type: article
Abstract: Background: An association exists between higher hospital volumes and better patient outcomes for high-risk pediatric and congenital heart surgery. This relationship suggests that patient deaths could potentially be avoided if the highest complexity operations performed in low- and medium-volume hospitals were shifted to high-volume hospitals. Using publicly available data, this study investigates the number of deaths of pediatric and congenital heart surgery patients in the USA that theoretically could be avoided if highest complexity patients had surgery at high-volume hospitals. Methods: Data were extracted from The Society of Thoracic Surgeons website for 61 hospitals that voluntarily publicly reported their outcomes. Each hospital was categorized based on their mean annual volume of pediatric and congenital heart surgeries. For each volume and patient risk category combination, we calculated an observed-to-expected mortality ratio. Using high-volume hospitals as the reference, we calculated the theoretical difference in number of deaths in medium- and low-volume hospitals if they had the same mortality performance as high-volume hospitals. Results: Over the 4-year reporting period, 104 deaths (overall 26% reduction in observed deaths) theoretically might have been prevented if higher-risk operations done at low- and medium-volume hospitals were performed with outcomes comparable to those of high-volume hospitals. Conclusions: This analysis identified a large relative risk reduction in mortality of high-risk pediatric and congenital heart surgery patients that theoretically could be achieved if higher-risk operations performed at low- and medium-volume hospitals could shift to high-volume hospitals. A number of potential solutions exist to reduce these potentially preventable deaths, including regionalization.
Authors: J. Matthew Austin, Jordan M. Derk, Peter J. Pronovost
Institutions: Johns Hopkins University, Johns Hopkins Medicine
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W2904348635