Literature DB >> 23742056

Implications of metric choice for common applications of readmission metrics.

Sheryl Davies1, Olga Saynina, Ellen Schultz, Kathryn M McDonald, Laurence C Baker.   

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. © Health Research and Educational Trust.

Entities:  

Keywords:  Administrative data uses; hospitals; quality of care

Mesh:

Year:  2013        PMID: 23742056      PMCID: PMC3876390          DOI: 10.1111/1475-6773.12075

Source DB:  PubMed          Journal:  Health Serv Res        ISSN: 0017-9124            Impact factor:   3.402


  20 in total

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8.  An administrative claims model suitable for profiling hospital performance based on 30-day mortality rates among patients with an acute myocardial infarction.

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6.  Limitations of using same-hospital readmission metrics.

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7.  What is the impact of a clinically related readmission measure on the assessment of hospital performance?

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8.  Risk factors for hospitalizations among patients with cirrhosis: A prospective cohort study.

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  8 in total

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