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Model predikce rehospitalizací×Simulace toku pacientů×
OborManagement zdravotní péčeManagement zdravotní péče
RodinaProcess / pipelineProcess / pipeline
Rok vzniku19981990
TvůrceHealthcare data analytics and outcomes researchOperations research and management science
TypLogistic regression and machine learning methodologyDiscrete event simulation technique
Původní zdrojJencks, 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
Další názvyReadmission Risk Prediction, Hospital Readmission ForecastingHealthcare DES, Patient Movement Simulation
Příbuzné55
ShrnutíHospital 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.
ScholarGateDatová sada
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  1. v1
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  3. PUBLISHED

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ScholarGatePorovnat metody: Hospital Readmission Prediction Model · Patient Flow Simulation. Získáno 2026-06-20 z https://scholargate.app/cs/compare