So sánh phương pháp

	Mô hình Dự đoán Tái nhập viện tại Bệnh viện	Mô phỏng Luồng Bệnh nhân
Lĩnh vực	Quản lý chăm sóc sức khỏe	Quản lý chăm sóc sức khỏe
Họ	Process / pipeline	Process / pipeline
Năm ra đời	1998	1990
Người khởi xướng	Healthcare data analytics and outcomes research	Operations research and management science
Loại	Logistic regression and machine learning methodology	Discrete event simulation technique
Công trình gốc	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
Tên gọi khác	Readmission Risk Prediction, Hospital Readmission Forecasting	Healthcare DES, Patient Movement Simulation
Liên quan	5	5
Tóm tắt	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.