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Empirically derived composite measures of surgical performance
Douglas O Staiger1, Justin B Dimick, Onur Baser
1Department of Economics and the Dartmouth Institute for Health Policy and Clinical Practice, Dartmouth College, Hanover, New Hampshire, USA.
Medical Care
|January 27, 2009
Summary
A new composite measure for surgical performance effectively explains and forecasts hospital mortality rates, outperforming individual quality indicators. This approach can enhance public reporting and quality improvement initiatives.
Area of Science:
- Cardiovascular Surgery
- Health Services Research
- Surgical Quality Measurement
Background:
- Individual surgical quality measures have limitations in assessing overall performance.
- Empirically-based methods for composite surgical quality measures are not well-established.
Purpose of the Study:
- To develop and validate a composite measure of surgical performance.
- To assess the measure's ability to explain and forecast hospital mortality rates.
Main Methods:
- Utilized national Medicare claims data for aortic valve replacement (AVR) patients (2000-2001).
- Identified hospital-level predictors of mortality, including volume and complication rates.
- Employed Bayesian-derived modeling to predict hospital-specific mortality rates and validated against subsequent outcomes.
Main Results:
- The composite measure explained 78% of variation in AVR mortality rates (2000-2001).
- Key predictors included hospital volume and mortality for AVR and other high-risk cardiac procedures.
- The measure forecasted 70% of future hospital-level mortality variation (2002-2003), significantly outperforming individual measures.
- Hospitals in the bottom quintile had double the mortality rates of top-quintile hospitals in the subsequent period.
Conclusions:
- Empirically derived composite measures are superior to individual indicators for explaining and forecasting surgical mortality.
- These composite measures can inform public reporting, value-based purchasing, and quality benchmarking.