Composite measures for hospital quality using quality-adjusted life years

Area of Science:

• Health Services Research
• Biostatistics
• Health Economics

Background:

• Developing clinically meaningful summary measures of healthcare quality is crucial for effective quality improvement.
• Current quality measures often lack weighting based on clinical importance, potentially misdirecting improvement efforts.
• Coronary artery bypass graft (CABG) surgery serves as a case study to develop and test a novel quality measurement framework.

Purpose of the Study:

• To develop and illustrate a new composite measure of healthcare quality for CABG surgery, weighted by clinical importance.
• To compare the performance of this novel QALY-based measure against conventional mortality measures in identifying quality outliers.
• To demonstrate the utility of a fully Bayesian hierarchical modeling approach in health outcomes research.

Main Methods:

• Utilized a hierarchical exponential survival model within a fully Bayesian framework to estimate 1-year survival outcomes post-CABG.
• Incorporated patient-specific complication probabilities and literature-derived utility values to calculate expected utility.
• Estimated quality-adjusted life years (QALYs) per hospital as the utility-weighted average of 1-year survival, calculating incremental QALYs relative to state averages.

Main Results:

• Applied the framework to 14 hospitals performing CABG surgery in Massachusetts in 2003.
• Demonstrated that a composite measure based on incremental QALYs can alter the classification of quality outliers compared to traditional mortality metrics.
• Highlighted the potential for QALY-based measures to provide a more nuanced understanding of hospital quality.

Conclusions:

• A composite quality measure incorporating clinical importance through QALYs offers a more informative assessment of healthcare performance for CABG surgery.
• This QALY-based approach provides a valuable tool for focusing quality improvement initiatives on areas with the greatest potential impact on patient health outcomes.
• The methodology offers a robust framework for developing clinically meaningful summary measures applicable to other healthcare interventions and settings.