Year: 2013
Type: article
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.
Source: Health Services Research
Institutions: Stanford Medicine, Stanford University
Language: English
Subfield: Health Information Management
Field: Health Professions
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W2062674046