Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Modeli wa Ut napilika wa Kulazwa Hospitalini× | Uiguzi wa Mtiririko wa Wagonjwa× | |
|---|---|---|
| Nyanja | Usimamizi wa Huduma za Afya | Usimamizi wa Huduma za Afya |
| Familia | Process / pipeline | Process / pipeline |
| Mwaka wa asili≠ | 1998 | 1990 |
| Mwanzilishi≠ | Healthcare data analytics and outcomes research | Operations research and management science |
| Aina≠ | Logistic regression and machine learning methodology | Discrete event simulation technique |
| Chanzo asilia≠ | 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 ↗ | Pidd, M. (1992). Computer Simulation in Management Science (3rd ed.). John Wiley & Sons. ISBN: 9780471939314 |
| Majina mbadala | Readmission Risk Prediction, Hospital Readmission Forecasting | Healthcare DES, Patient Movement Simulation |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | 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. | Discrete Event Simulation (DES) is a computational technique that models the movement of patients through healthcare facilities by simulating individual patient journeys and interactions with resources (staff, beds, equipment). DES allows realistic representation of complex, stochastic healthcare processes and supports 'what-if' analysis without disrupting live operations. |
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