The Hospital Compare mortality model and the volume-outcome relationship

Health Serv Res. 2010 Oct;45(5 Pt 1):1148-67. doi: 10.1111/j.1475-6773.2010.01130.x.


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.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Validation Study

MeSH terms

  • Aged
  • Aged, 80 and over
  • Analysis of Variance
  • Bed Occupancy / statistics & numerical data
  • Bias
  • Health Services Research
  • Hospital Bed Capacity / statistics & numerical data
  • Hospital Mortality*
  • Humans
  • Insurance Claim Reporting / statistics & numerical data
  • Internet
  • Linear Models*
  • Logistic Models*
  • Medicare / statistics & numerical data*
  • Myocardial Infarction / mortality
  • Outcome Assessment, Health Care / organization & administration*
  • Patient Admission / statistics & numerical data*
  • Predictive Value of Tests
  • Risk Adjustment
  • United States / epidemiology