Socioeconomic Determinants of National Hospital Insurance Fund Health Contributions and Absorption: A Time Series Investigation Among the Counties in Kenya

Eugene Wanzetse Musungu

doi:10.11648/j.hep.20210601.11

Abstract

The aim of this investigation was to analyze socioeconomic determinants of National Hospital Insurance Fund Health contributions and absorption. The investigation was conducted in two study areas; the 47 counties and NHIF. First, the investigation targeted the 47 County Governments in Kenya. The study collected secondary data on the socioeconomic variables including; level of education, level of income and GDP from the respective 47 counties in Kenya collected from the Kenya Economic Review (2014-2020). The second investigation area was NHIF where collecting the annual audited financial statements from the NHIF between 2013/2014 – 2019/2020 financial years obtained from Kenya Auditor General, a total of 7 years resulting into 329 observations. The investigation employed a mixed research design, descriptive research design and casual-correlation research design. Findings on the relationship between educational level and income the socioeconomic determinants and NHIF contributions, the study established significant relationship between county education level (r=0.2813, p=0.010), counties income (r=6.3706, p=0.048) and NHIF contributions. Therefore the hypothesis HO1 that individual socioeconomic factors among the 47 counties in Kenya do not significantly influence NHIF contribution was rejected. On the other hand, findings on the relationship between socioeconomic determinants and NHIF absorptions, at individual socioeconomic determinants level significant relationship between education level, the study established significant relationship between county education level (r=0.02863, p=0.007), counties income (r=6.3906, p=0.040) and NHIF absorptions. Therefore the hypothesis HO2 that individual socioeconomic factors among the 47 counties in Kenya do not significantly influence NHIF absorption was rejected. Further findings on relationship between combined socioeconomic determinants and NHIF contributions established that all the determinants including counties GDP had significant relationship with NHIF contributions (Counties education level r=0. 02708, p=0.015, counties income level r=0. 0220, p=0.005, counties GDP r=-1.17749, p=0.015). The hypothesis HO3 that the combined socioeconomic factors among the 47 counties in Kenya do not significantly influence NHIF contribution was rejected. Concerning the relationship between the combined socioeconomic determinants and NHIF absorption, the study also established that all the determinants including counties GDP had significant relationship with NHIF absorptions (Counties education level r=0.02766, p=0.010, counties income level r=0.0224, p=0.003, counties GDP r-1.207783, p=0.010). The hypothesis HO4 that the combined socioeconomic factors among the 47 counties in Kenya do not significantly influence NHIF absorption was rejected.

Highlights

Low and medium-income countries (LMICs) are increasingly adopting universal health coverage (UHC) as their health policy priority [1]
Where Xit is the predictor variable that is the revenue as economic determinants and Yit is the dependent variable, the National Hospital Insurance Fund (NHIF) contribution assumes the homogeneity of estimates across entities in the random effect model and that the independent variable that the probability of NHIF contribution varies over time but has a random effect across entities, β1 is the coefficients of the regressor variables and a0 was the error term
Where Xit is the predictor variable that is the degree of education as social determinants and Yit is the dependent variable, NHIF contribution assumes homogeneity of estimates across entities in the random effect model and that the independent variable assumes that the likelihood of NHIF contribution varies over time but has a random effect across entities, β1 is the coefficients of the regressor variables and a0 is the coefficient of the predictor variable and μit is error term

Summary

Introduction

Low and medium-income countries (LMICs) are increasingly adopting universal health coverage (UHC) as their health policy priority [1]. In order to achieve UHC, countries need to increase the scope of services they provide their citizens, extend population coverage through a prepayment mechanism, and reduce the proportion of direct costs that citizens pay for Eugene Wanzetse Musungu: Socioeconomic Determinants of National Hospital Insurance Fund Health Contributions and Absorption: A Time Series Investigation Among the Counties in Kenya accessing health care services. In 1998, an Act of Parliament, which was later amended in 2012, established NHIF as a state corporation (Republic of Kenya, 2012) It raises funds mainly through member contributions, which are statutory deductions from persons employed in the formal sector (based on income levels) and voluntary (flat rate) for persons employed in the informal/self-employed sector. The NHIF committed itself in its strategic plan for 2014-2018 to increasing coverage in the informal sector and among indigent communities through government funding [4]

Methods

Results

Conclusion