https://www.ohdsi.org/wp-content/uploads/2023/11/Nov7-Tong.pdf 

Background

Hospital profiling asks whether patient outcomes differ across hospitals after accounting for differences in the patients they treat. This use case studied COVID-19 mortality among hospitalized adults from 12 OHDSI sites in the United States, Spain, and the Netherlands. Because sites differed in sample size, age distribution, and comorbidity burden, crude mortality rates alone could give a misleading picture of hospital performance.

Method

We applied a distributed hospital profiling framework that estimates risk-standardized mortality rates without sharing patient-level data. The framework combines dGEM, a communication-efficient distributed generalized linear mixed-effects model, with counterfactual standardization, which compares hospitals as if they had treated the same reference patient population. This enables privacy-preserving, risk-adjusted benchmarking across heterogeneous health systems.

Main finding

After case-mix adjustment, the 12 hospitals showed a stable tier-wise performance pattern across the two pandemic waves. Top, middle, and lower-performing groups remained visible even when individual ranks shifted. At the same time, 8 of 12 sites improved their risk-standardized mortality rates from Wave A to Wave B, suggesting broad improvement in COVID-19 inpatient outcomes over time.