Predicting Community-Based Healthcare Claims Using International Classification of Primary Care Codes


  • L.A. Ajijola University of Lagos, Nigeria
  • R.K. Ojikutu University of Lagos, Nigeria
  • I.A. Adeleke University of Lagos, Nigeria


Risk Adjustment, Risk Selection, Primary Care, Health Insurance


As in many other developing countries, affordability and accessibility to health care in Nigeria have always been a matter of great concern. The hope of the average Nigerian to have reliable and affordable healthcare delivery system was brightened with the take-off of the National Health Insurance Scheme (NHIS) in 2005. However, Social Health Insurance Schemes like other forms of health insurance have both health and financial risks. This study applied the International Classification of Primary Care codes to develop diagnostic-based risk adjustment model for predicting future claims in a Community Based Social Health Insurance Programme using claims data of 23,735 enrollees. Results show the adequacy of the diagnostic-based risk adjustment model with a predictive performance of 52% and MAPE of 53%. The expectation is that implementation of risk adjustment model will correct prevalence of risk selection cream-skimming at the community level of the healthcare system.