Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Model de predicție a readmisiilor spitalicești× | Sănătate Lean× | |
|---|---|---|
| Domeniu | Management sanitar | Management sanitar |
| Familie | Process / pipeline | Process / pipeline |
| Anul apariției≠ | 1998 | 1988 |
| Autorul original≠ | Healthcare data analytics and outcomes research | Taiichi Ohno, Toyota Production System |
| Tip≠ | Logistic regression and machine learning methodology | Continuous improvement methodology |
| Sursa seminală≠ | 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 ↗ |
| Denumiri alternative | Readmission Risk Prediction, Hospital Readmission Forecasting | Lean Healthcare Management, Healthcare Lean |
| Înrudite | 5 | 5 |
| Rezumat≠ | 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. |
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