To assess the reliability of risk‐standardized readmission rates (s) for medical conditions and surgical procedures used in the Hospital Readmission Reduction Program ().
State Inpatient Databases for six states from 2011 to 2013 were used to identify patient cohorts for the six conditions used in the , which was augmented with hospital characteristic and penalty data.
Hierarchical logistic regression models estimated hospital‐level s for each condition, the reliability of each , and the extent to which socioeconomic and hospital factors further explain variation. We used publicly available data to estimate payments for excess readmissions in hospitals with reliable and unreliable s.
Only s for surgical procedures exceeded the reliability benchmark for most hospitals, whereas s for medical conditions were typically below the benchmark. Additional adjustment for socioeconomic and hospital factors modestly explained variation in s. Approximately 25 percent of payments for excess readmissions were tied to unreliable s.
Many of the s employed by the are unreliable, and one quarter of payments for excess readmissions are associated with unreliable s. Unreliable measures blur the connection between hospital performance and incentives, and threaten the success of the .