Validation of a claims-based algorithm to characterize episodes of care.

OBJECTIVES:Although hospitals face increasing pressure from payers to improve the efficiency of healthcare delivery beyond the index hospitalization, they often lack information on postdischarge events. The Michigan Value Collaborative (MVC) developed a claims-based algorithm to provide hospitals with data on events that occur to patients beyond the hospitalization. Herein, we discuss the validation of MVC's claims-based algorithm. STUDY DESIGN:Retrospective analysis of a claims-based algorithm's ability to identify specific medical events, such as index hospitalizations, 30-day readmissions, emergency department visits, skilled nursing facility admissions, home health visits, and rehabilitation services. The claims-based events were validated using a primary review at 63 hospitals. METHODS:We selected 1830 Blue Cross Blue Shield of Michigan episodes from MVC data and asked 63 Michigan hospitals to query their medical records for the presence or absence of specific events. We then calculated agreement statistics and improved our algorithm using feedback from hospitals. RESULTS:All 63 hospitals participated in the validation process and successfully identified 99% of episodes in their medical records. The initial agreement between our algorithm and medical records was moderate for 4 postdischarge events (kappa ranging from 0.62-0.78) and poor for rehabilitation services (0.16). Much of the disagreements occurred because hospitals could not identify postdischarge events occurring outside of their hospital systems. Other disagreements occurred because of hospital coding practices. Through this analysis, the claims-based algorithm was improved to better reflect real-world coding practice. CONCLUSIONS:Our findings suggest that the MVC claims-based algorithm identifies and classifies claims with high fidelity and outperforms medical records in the identification of postdischarge events. These findings provide important insight to policy makers, payers, and hospital administrators about the value of claims-based data for the implementation of episode-based programs.