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What Are the Characteristics That Explain Hospital Quality? A Longitudinal Pridit Approach
Author(s) -
Lieberthal Robert D.,
Comer Dominique M.
Publication year - 2013
Publication title -
risk management and insurance review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.386
H-Index - 16
eISSN - 1540-6296
pISSN - 1098-1616
DOI - 10.1111/rmir.12017
Subject(s) - quality (philosophy) , context (archaeology) , health care , actuarial science , set (abstract data type) , medicine , health care quality , computer science , business , economics , paleontology , philosophy , epistemology , biology , programming language , economic growth
Abstract Health outcomes vary substantially between high‐ and low‐quality institutions, meaning the difference between life and death in some cases. The prior literature has identified a number of variables that can be used to determine hospital quality, but methodologies for combining variables into an overall measure of hospital quality are not well developed. This analysis builds on the prior investigation of hospital quality by evaluating a method originally developed for the detection of health‐care fraud, Pridit, in the context of determining hospital quality. We developed a theoretical model to justify the application of Pridit to the hospital quality setting and then applied the Pridit method to a national, multiyear data set on U.S. hospital quality variables and outcomes. The results demonstrate how the Pridit method can be used predictively, in order to predict future health outcomes based on currently available quality measures. These results inform the use of Pridit, and other unsupervised learning methods, in fraud detection and other settings where valid and reliable outcomes variables are difficult to obtain. The empirical results obtained in this study may also be of use to health insurers and policymakers who aim to improve quality in the hospital setting.