Prediction of insurance membership retention rates using machine learning: a case study of Tanzania’s improved community health insurance fund (iCHF)

Abstract Introduction Developing countries like Tanzania rely heavily on out-of-pocket (OOP) payments to finance health. Unfortunately, these OOP payments often expose patients to catastrophic health expenditures (CHE), which hinders progress toward universal health coverage (UHC). Tanzania introduc...

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Główni autorzy:	Castory Munishi, George Ruhago, Amani Mori, Jofrey S. Amos, Othman Haji, Alphoncina Kagaigai, James T. Kengia, Oddvar Martin
Format:	Artigo
Język:	Inglês
Wydane:	Springer Nature 2026-03-01
Seria:	Discover Health Systems
Hasła przedmiotowe:	Machine-learning Health insurance Tanzania Community health fund Catastrophic health expenditure
Dostęp online:	https://doi.org/10.1007/s44250-026-00358-3
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