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Circ Cardiovasc Qual Outcomes ; 1(1): 29-37, 2008 Sep.
Article in English | MEDLINE | ID: mdl-20031785

ABSTRACT

BACKGROUND: Readmission soon after hospital discharge is an expensive and often preventable event for patients with heart failure. We present a model approved by the National Quality Forum for the purpose of public reporting of hospital-level readmission rates by the Centers for Medicare & Medicaid Services. METHODS AND RESULTS: We developed a hierarchical logistic regression model to calculate hospital risk-standardized 30-day all-cause readmission rates for patients hospitalized with heart failure. The model was derived with the use of Medicare claims data for a 2004 cohort and validated with the use of claims and medical record data. The unadjusted readmission rate was 23.6%. The final model included 37 variables, had discrimination ranging from 15% observed 30-day readmission rate in the lowest predictive decile to 37% in the upper decile, and had a c statistic of 0.60. The 25th and 75th percentiles of the risk-standardized readmission rates across 4669 hospitals were 23.1% and 24.0%, with 5th and 95th percentiles of 22.2% and 25.1%, respectively. The odds of all-cause readmission for a hospital 1 standard deviation above average was 1.30 times that of a hospital 1 standard deviation below average. State-level adjusted readmission rates developed with the use of the claims model are similar to rates produced for the same cohort with the use of a medical record model (correlation, 0.97; median difference, 0.06 percentage points). CONCLUSIONS: This claims-based model of hospital risk-standardized readmission rates for heart failure patients produces estimates that may serve as surrogates for those derived from a medical record model.


Subject(s)
Insurance Claim Review/statistics & numerical data , Medical Records/statistics & numerical data , Models, Statistical , Patient Readmission/statistics & numerical data , Female , Heart Failure/economics , Humans , Male , Medicare , Outcome Assessment, Health Care , Patient Readmission/economics , Software Validation , United States
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