Faculty Publication by Xin Wang

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Faculty Member:

Xin Wang

Title of Publication:

"Estimating A Composite Measure of Hospital Quality From the Hospital Compare Database: Differences When Using a Bayesian Hierarchical Latent Variable Model Versus Denominator-Based Weights"

Publication Type:

Forthcoming Paper

Year of Publication:

2008

Co-Authors:

M. Shwartz, Z.J. Ren, E. Pekoz, A. Cohen, J. Restuccia

Publication Details:

Medical Care, 2008

Abstract:

Using data for 15 quality indicators from 3,275 hospitals in the Hospital Compare database, we calculated hospital ranks using several versions of denominator-based weights (DBWs) and two Bayesian hierarchical latent variable models (BLVMs). Estimates in one BLVM were driven by differences in variances of the QIs (BLVM1) and estimates in the other by differences in the signal-to-noise ratios of the QIs (BLVM2). There was a high correlation in ranks among all of the DBW approaches and between those approaches and BLVM1. However, a high correlation does not necessarily mean that the same hospitals were ranked in the top or bottom quality deciles. In general, large hospitals were ranked in higher quality deciles by all of the approaches, though the effect was most apparent using BLVM2. Both conceptually and practically, hospital-specific DBWs are a reasonable approach for calculating a composite measure. However, this approach fails to take into account differences in the reliability of estimates from hospitals of different sizes, a big advantage of the Bayesian models.

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