
Mathematical Techniques of Modelling Salary-Based Health Care Contribution
Author(s) -
Ogungbenle Gbenga Michael
Publication year - 2021
Publication title -
nepal journal of mathematical sciences
Language(s) - English
Resource type - Journals
eISSN - 2738-9928
pISSN - 2738-9812
DOI - 10.3126/njmathsci.v2i2.40129
Subject(s) - salary , actuary , actuarial science , health care , self insurance , business , health policy , government (linguistics) , health care reform , underwriting , economics , public economics , economic growth , linguistics , philosophy , market economy
This paper is intended to support reforms counteracting the adverse health insurance contribution trends through constructing an actuarially equitable salary-based health care system for experienced health insurance underwriters. The focus is on contribution technique employed by experts who consult for health insurance funds especially when performing official duties as health insurance actuary. The objective is to construct actuarial models of computing employee’s, employer’s and government’s contribution for health insurance care program in a way that permits generally equitable cost-efficient health insurance coverage within the framework of obtainable health benefits policy. Nigeria’s low economic growth rate and primitive technology resulted in an increasing rate of health care costs and consequently, quality health care at affordable prices is far from the reach of enrollees because of inequitable distribution of costs. In order to solve this problem, we constructed a health care model with a deterministic salary function structure to compute contribution on behalf of enrollees as a paradigm shift to an actuarial system of modelling contribution with a goal to building a sustainable health insurance delivery that encourages good health outcomes. From our results, the rate derived from our current model is far below the official rating of on employee’s salary which is not footed on actuarial basis and hence cheaper and more equitable to adopt.