विधियों की तुलना करें

	अस्पताल में पुनः भर्ती भविष्यवाणी मॉडल	रोगी प्रवाह सिमुलेशन
क्षेत्र	स्वास्थ्य सेवा प्रबंधन	स्वास्थ्य सेवा प्रबंधन
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	1998	1990
प्रवर्तक	Healthcare data analytics and outcomes research	Operations research and management science
प्रकार	Logistic regression and machine learning methodology	Discrete event simulation technique
मौलिक स्रोत	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
उपनाम	Readmission Risk Prediction, Hospital Readmission Forecasting	Healthcare DES, Patient Movement Simulation
संबंधित	5	5
सारांश	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.