MODELLING HEALTH MAINTENANCE ORGANIZATIONS PAYMENTS UNDER THE NATIONAL HEALTH INSURANCE SCHEME IN NIGERIA

Abstract

The Nigerian National Health Insurance Scheme (NHIS) is set up to ensure equitable payment of health care bills combining and prudently reducing cost-burden distribution for residents, versus high health care costs. Health maintenance organizations (HMO) are limited liability companies which could be established by private, public or individual entities with the main aim of being players in the scheme. This paper explored logistic regression (LR), linear discriminant analysis (LDA) and random forest (RF) in determining the factors that could determine if an HMO will cover full or part of an individual's healthcare bill. The results do not show a significant difference in the classification accuracies of the three methods. Inferring that the highest number of the Nigerian residents that make use of the NHIS lie between the 31-40yrs age bracket and that largely, ailment classification and the insured’s age are key determining factors of whether an HMO would cover all or part of the bill.