手法を比較

	再入院予測モデル	患者フローシミュレーション
分野	医療経営学	医療経営学
系統	Process / pipeline	Process / pipeline
提唱年	1998	1990
提唱者	Healthcare data analytics and outcomes research	Operations research and management science
種類	Logistic regression and machine learning methodology	Discrete event simulation technique
原典	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.	Pidd, M. (1992). Computer Simulation in Management Science (3rd ed.). John Wiley & Sons. ISBN: 9780471939314
別名	Readmission Risk Prediction, Hospital Readmission Forecasting	Healthcare DES, Patient Movement Simulation
関連	5	5
概要	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.