Predictability and Financial Sufficiency of Health Insurance in Colombia: An Actuarial Analysis With a Bayesian Approach

Abstract

Every year, the Colombian government provides a prospective premium, known as the capitation payment unit (CPU), for each affiliated person (according to sex, region, and age) to each health insurance company, in order to manage the corresponding risk in health. This article studies the prediction capacity for the health expenditure for the more than 20 million affiliates to the contributory regime of health, as well as the CPU’s financial sufficiency, using an actuarial approach. Using the pure risk premium method and generalized linear models, both classic and Bayesian, the CPU is estimated; these results are compared to actual expenditure by an index of forecasting ability. It is concluded that the use of historical information about expenditure on health, as well as the Bayesian inference, among the other methodological innovations developed, provides an advantage for obtaining more accurate prospective values. These technical recommendations seek to support an improvement in the public budget allocation of more than 6 billion dollars per year to the Colombian health system.