Implications of metric choice for common applications of readmission metrics

Abstract

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.

Keywords: Administrative data uses; hospitals; quality of care.

© Health Research and Educational Trust.

Figures

Figure 1

Impact of Metric Choice on Longitudinal Performance. (Scatterplots show the hospital-year readmission rates for two metrics [identified in the column headings] for each of the three clinical groups [identified in the row headings]. Pearson correlation coefficients. Data are based on 2000–2009 California Office of Statewide Health Planning and Development Patient Discharge Data)