The effect of public and private health care Expenditures on infant mortality rate in Kenya

Abstract

Public and the private sectors finance Kenyan healthcare system. The public and private sectors contribute34% and 40% of the total health expenditure respectively and the donor contribution is 26%. The total health spending is 6.8% instead of the 15% of the total government expenditure, as per the Abuja agreement to which Kenya is a signatory. The infant mortality rates (IMR) in Kenya is still high, 39 per 1000 live births. While policy and strategy formulation forums pushes for increase in healthcare inputs from the public and private sectors, focus on both the expenditures and outcomes has been ignored. Ascertaining the level of benefits resulting from the various healthcare expenditures is vital. However, researches that summarize the debate on the effects of Public healthcare expenditure (PHE) and Private healthcare expenditure (PRHE) on IMR advocate conflicting views. Little research has since been done for Kenya regarding the effect of PHE and PRHE on IMR. Whether PHE and PRHE reduce IMR in Kenya is still unclear. Other than filling the knowledge gap, an examination of the effect of PHE and PRHE on IMR in Kenya will also be useful in reconciling the different positions. The purpose of the study was to examine the effect of PHE and PRHE on IMR in Kenya. The specific objectives were: To establish the effect of PHE on IMR in Kenya; to ascertain the effect of PRHE on IMR in Kenya; to analyze the joint effect of PHE, PRHE, per capita income (Y), female literacy (FL), immunization coverage (IMU), Urbanization level (URB) on IMR in Kenya. Correlational research design was used. The Health Production model formed the theoretical framework. Time series annual data for a period of 34 years from 1981 to 2014 was used. After confirmation of unit root presence by uses of the, Augmented Dickey Fuller test the Johansen cointergration test was done, the variables were found to be cointergrated. Bivariate and Multivariate Newy -West regressions were carried out to estimate the models. ECM (Error Correction Model) was employed to take care of the adjustments towards equilibrium. The results showed that both the PHE and PRHE had a significant negative relationship with IMR at the 5% level. Increasing PHE by 1% reduced the IMR by 0.12%. 1% increase in PRHE reduced IMR by 0.09%. The joint effects PHE, PRHE, Y, IMU, FL and URB on IMR reveal an R2 of 91.32%.These variables therefore, accounted for more than 91% of the variations in IMR. Y, IMU, FL and URB also have a negative relationship with IMR. The study concludes that PHE and PRHE are significant for the reduction of IMR in Kenya. That jointly PHE, PRHE Y, IMU, FL, URB reduce IMR in Kenya. The study findings provide impetus for the government to design and implement policies that increase PHE. Measures that increase the PRHE such as Private insurance should be enhanced. The education policies that increase female literacy and the increase in accessibility of healthcare facilities are important.