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Implications of metric choice for common applications of readmission metrics
Sheryl Davies1, Olga Saynina, Ellen Schultz
1Center for Primary Care and Outcomes Research, Stanford School of Medicine, Stanford, CA.
Insights
Different hospital readmission metrics significantly impact performance rankings and pay-for-performance outcomes. Choosing the right metric, such as all-cause readmission (ACR) or CMS 30-day readmission, is crucial for accurate assessment.
Area of Science:
- Health Services Research
- Healthcare Quality Improvement
- Health Informatics
Background:
- Hospital performance evaluation is critical for quality improvement and reimbursement.
- Readmission rates are a key performance indicator, but various metrics exist.
- Understanding the impact of different readmission metrics is essential for accurate hospital assessment.
Purpose of the Study:
- To compare the impact of three readmission metrics on hospital performance: all-cause readmission (ACR), 3M Potential Preventable Readmission (PPR), and Centers for Medicare and Medicaid (CMS) 30-day readmission.
- To analyze the differential effects of these metrics on hospital rankings and longitudinal performance.
- To assess the agreement and correlation between different readmission metrics.
Main Methods:
- Utilized California hospital discharge data from 2000-2009.
- Calculated 30-day readmission rates for heart failure (HF), acute myocardial infarction (AMI), and pneumonia using ACR, PPR, and CMS metrics.
- Analyzed absolute change, correlation, hospital ranking stability across metrics, and longitudinal performance differences.
Main Results:
- CMS and ACR metrics showed higher average hospital rates for HF patients.
- Strong correlations were found between ACR and CMS metrics (r=0.67-0.84).
- Moderate correlations existed between PPR and ACR/CMS metrics (r=0.50-0.67); 47-75% of hospitals remained in extreme deciles across metrics, with modest correlations in longitudinal changes.
Conclusions:
- Different readmission metrics yield varying hospital performance rankings.
- Metric selection significantly influences pay-for-performance outcomes.
- Careful consideration of the chosen readmission metric is vital for accurate hospital evaluation and policy implementation.
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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