Predicting health insurance uptake in Kenya using Random Forest: An analysis of socio-economic and demographic factors.

ABSTRACT: Universal Health Coverage (UHC) is a global objective aimed at providing equitable access to essential and cost-effective healthcare services, irrespective of individuals' financial circumstances. Despite efforts to promote UHC through health insurance programs, the uptake in Kenya remains low. This study aimed to explore the factors influencing health insurance uptake and offer insights for effective policy development and outreach programs. The study utilized machine learning techniques on data from the 2021 FinAccess Survey. Among the models examined, the Random Forest model demonstrated the highest performance with notable metrics, including a high Kappa score of 0.9273, Recall score of 0.9640, F1 score of 0.9636, and Accuracy of 0.9636. The study identified several crucial predictors

SUBMITTER: Yego NKK 

PROVIDER: S-EPMC10688734 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature