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- Title
Comparing performance of 30-day readmission risk classifiers among hospitalized primary care patients.
- Authors
Garrison, Gregory M.; Robelia, Paul M.; Pecina, Jennifer L.; Dawson, Nancy L.
- Abstract
Rationale, aims and objectives Hospital readmission within 30 days of discharge occurs in almost 20% of US Medicare patients and may be a marker of poor quality inpatient care, ineffective hospital to home transitions, or disease severity. Within a patient centered medical home, care transition interventions may only be practical from cost and staffing perspectives if targeted at patients with the greatest risk of readmission. Various scoring algorithms attempt to predict patients at risk for 30-day readmission, but head-to-head comparison of performance is lacking. Compare published scoring algorithms which use generally available electronic medical record data on the same set of hospitalized primary care patients. Methods The LACE index, the LACE+ index, the HOSPITAL score, and the readmission risk score were computed on a consecutive cohort of 26,278 hospital admissions. Classifier performance was assessed by plotting receiver operating characteristic curves comparing the computed score with the actual outcome of death or readmission within 30 days. Statistical significance of differences in performance was assessed using bootstrapping techniques. Results Correct readmission classification on this cohort was moderate with the following c-statistics: Readmission risk score 0.666; LACE 0.680; LACE+ 0.662; and HOSPITAL 0.675. There was no statistically significant difference in performance between classifiers. Conclusions Logistic regression based classifiers yield only moderate performance when utilized to predict 30-day readmissions. The task is difficult due to the variety of underlying causes for readmission, nonlinearity, and the arbitrary time period of concern. More sophisticated classification techniques may be necessary to increase performance and allow patient centered medical homes to effectively focus efforts to reduce readmissions.
- Subjects
ALGORITHMS; COMPARATIVE studies; DEATH; HOSPITAL patients; PRIMARY health care; RISK assessment; LOGISTIC regression analysis; RECEIVER operating characteristic curves; PATIENT readmissions; DESCRIPTIVE statistics
- Publication
Journal of Evaluation in Clinical Practice, 2017, Vol 23, Issue 3, p524
- ISSN
1356-1294
- Publication type
Article
- DOI
10.1111/jep.12656