Developing A Risk-Adjusted Capitation Regime for Nigeria Health Insurance Scheme (NHIS)


  • Ismaila Adeleke University of Lagos, Nigeria


Risk Adjustment, Capitation, Healthcare, Generalized Linear Model, Risk - Adjusted Model


The National Health Insurance Scheme (NHIS) is set up to operate as Public Private Partnership and directed at providing accessible, affordable and qualitative healthcare for all Nigerians. The Nigerian health insurance industry is faced with the challenge of developing a sustainable fees structure owing to serious data deficits pervading the Nigerian healthcare system and unreliable critical health statistics. Using the capitation payment mechanism the health care provider assumes that for a given insured population, the provider will cover all health care services for a fixed payment per member per month. However, in this arrangement, payments assumed equal risk level for all subscribers and this may encourage risk selection. This article proposes the development of risk-adjusted capitation framework for the Nigeria National Health Insurance Scheme using generalised linear models. Findings show that the usual normal-based risk adjustment models could lead to further risk selection for highly skewed and heavy tailed data. The use of generalized gamma-based regression model for risk adjustment and determining fair capitation rates is suggested. The study relied on healthcare cost of various diagnoses based on international classification of diseases and information on enrollment to facilities with regards to enrollees characteristics. This framework would allow the healthcare management system to consolidate on the profile of its present and historical data contained in the production system and provides pathways for clinical and administrative information, actuarial valuation and in-depth statistical analysis. This is in tandem with the healthcare delivery agenda of the Millennium Development Goals (MDGs) and sustainable development. Policy implications and recommendation are discussed.