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Model predikcie rehospitalizácií v nemocnici×Simulácia toku pacientov×
OdborManažment zdravotníctvaManažment zdravotníctva
RodinaProcess / pipelineProcess / pipeline
Rok vzniku19981990
TvorcaHealthcare data analytics and outcomes researchOperations research and management science
TypLogistic regression and machine learning methodologyDiscrete event simulation technique
Pôvodný 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
Ďalšie názvyReadmission Risk Prediction, Hospital Readmission ForecastingHealthcare DES, Patient Movement Simulation
Príbuzné55
ZhrnutieHospital 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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ScholarGatePorovnať metódy: Hospital Readmission Prediction Model · Patient Flow Simulation. Získané 2026-06-20 z https://scholargate.app/sk/compare