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| Модел за прогнозиране на повторни хоспитализации× | Lean Healthcare× | |
|---|---|---|
| Област | Управление на здравеопазването | Управление на здравеопазването |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 1998 | 1988 |
| Създател≠ | Healthcare data analytics and outcomes research | Taiichi Ohno, Toyota Production System |
| Тип≠ | Logistic regression and machine learning methodology | Continuous improvement methodology |
| Основополагащ източник≠ | 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 ↗ | Ohno, T. (1988). Toyota Production System: Beyond Large-Scale Production. Productivity Press. link ↗ |
| Други названия | Readmission Risk Prediction, Hospital Readmission Forecasting | Lean Healthcare Management, Healthcare Lean |
| Свързани | 5 | 5 |
| Резюме≠ | 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. | Lean is a management philosophy that emerged from the Toyota Production System, focused on maximizing patient value while minimizing waste. Applied to healthcare, Lean uses systematic methods to identify and eliminate non-value-added activities, reduce wait times, and improve the quality of patient care. |
| ScholarGateНабор от данни ↗ |
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