Process / pipelinePredictive modeling, Patient risk stratification
Hospital Readmission Prediction Model
Hospital readmission prediction models use statistical and machine learning techniques to identify patients at high risk of returning to the hospital shortly after discharge. These models guide targeted discharge planning and follow-up to improve outcomes and reduce costs.
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Sources
- Jencks, S. F., Williams, M. V., & Coleman, E. A. (2009). Rehospitalizations among patients in the Medicare fee-for-service program. New England Journal of Medicine, 360(14), 1418–1428. DOI: 10.1056/NEJMsa0803563 ↗
- Krumholz, H. M., Normand, S. L. T., & Wang, Y. (2014). Trends in hospitalizations and outcomes for acute myocardial infarction, 2006 to 2011. Circulation, 132(4), 362–366. DOI: 10.1161/CIRCULATIONAHA.114.010636 ↗
- Philbin, E. F., & DiSalvo, T. G. (1998). Prediction of hospital readmissions for heart failure: development of a simple risk score based on administrative data. Journal of the American College of Cardiology, 33(6), 1560–1566. DOI: 10.1016/S0735-1097(98)00171-9 ↗