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VOLUME 48 | NUMBER 6 | DECEMBER 2013


Implications of Metric Choice for Common Applications of Readmission Metrics

Keywords: Administrative data uses;hospitals;quality of care

Objective: To quantify the differential impact on hospital performance of three readmission metrics: all-cause readmission (ACR), 3M Potential Preventable Readmission (PPR), and Centers for Medicare and Medicaid 30-day readmission (CMS).

Data Sources: 2000–2009 California Office of Statewide Health Planning and Development Patient Discharge Data Nonpublic file.

Study Design: We calculated 30-day readmission rates using three metrics, for three disease groups: heart failure (HF), acute myocardial infarction (AMI), and pneumonia. Using each metric, we calculated the absolute change and correlation between performance; the percent of hospitals remaining in extreme deciles and level of agreement; and differences in longitudinal performance.

Principal Findings: Average hospital rates for HF patients and the CMS metric were generally higher than for other conditions and metrics. Correlations between the ACR and CMS metrics were highest (r = 0.67–0.84). Rates calculated using the PPR and either ACR or CMS metrics were moderately correlated (r = 0.50–0.67). Between 47 and 75 percent of hospitals in an extreme decile according to one metric remained when using a different metric. Correlations among metrics were modest when measuring hospital longitudinal change.

Conclusions: Different approaches to computing readmissions can produce different hospital rankings and impact pay-for-performance. Careful consideration should be placed on readmission metric choice for these applications.

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