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Updated: Jun 12, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
The Hospital Compare mortality model and the volume-outcome relationship
Jeffrey H Silber1, Paul R Rosenbaum, Tanguy J Brachet
1Center for Outcomes Research, 3535 Market Street, Suite 1029, Philadelphia, PA 19104, USA. silberj@wharton.upenn.edu
Objective:
We ask whether Medicare's Hospital Compare random effects model correctly assesses acute myocardial infarction (AMI) hospital mortality rates when there is a volume-outcome relationship.
Data Sources/Study Setting:
Medicare claims on 208,157 AMI patients admitted in 3,629 acute care hospitals throughout the United States.
Study Design:
We compared average-adjusted mortality using logistic regression with average adjusted mortality based on the Hospital Compare random effects model. We then fit random effects models with the same patient variables as in Medicare's Hospital Compare mortality model but also included terms for hospital Medicare AMI volume and another model that additionally included other hospital characteristics.
Principal Findings:
Hospital Compare's average adjusted mortality significantly underestimates average observed death rates in small volume hospitals. Placing hospital volume in the Hospital Compare model significantly improved predictions.
Conclusions:
The Hospital Compare random effects model underestimates the typically poorer performance of low-volume hospitals. Placing hospital volume in the Hospital Compare model, and possibly other important hospital characteristics, appears indicated when using a random effects model to predict outcomes. Care must be taken to insure the proper method of reporting such models, especially if hospital characteristics are included in the random effects model.
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