Linganisha mbinu

	Ufanisi wa Hospitali wa DEA	Modeli wa Ut napilika wa Kulazwa Hospitalini
Nyanja	Usimamizi wa Huduma za Afya	Usimamizi wa Huduma za Afya
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	1978	1998
Mwanzilishi	Abraham Charnes, William Cooper, Edward Rhodes	Healthcare data analytics and outcomes research
Aina	Non-parametric frontier estimation technique	Logistic regression and machine learning methodology
Chanzo asilia	Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429–444.	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.
Majina mbadala	Hospital DEA, Healthcare DEA	Readmission Risk Prediction, Hospital Readmission Forecasting
Zinazohusiana	5	5
Muhtasari	Data Envelopment Analysis (DEA) is a linear programming technique for measuring the relative efficiency of multiple hospitals using multiple inputs and outputs. Introduced by Charnes, Cooper, and Rhodes in 1978, DEA has become the standard method for benchmarking hospital performance in healthcare systems worldwide.	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.