An Econometric Analysis Of Health Care Utilization In Kenya

Background: Increasing access to health care has been a policy concern for many governments, Kenya included. The Kenyan government introduced and implemented a number of initiatives in a bid to address the healthcare utilization challenge. These initiatives include 10/20 policy, exemptions for user fees for some specific health services (treatment of children less than five years, maternity services in dispensaries and health centers, Tuberculosis treatment in public health facilities), and increase in the number of health facilities and health workforce. These initiatives notwithstanding, healthcare utilization in Kenya remains a challenge. The Kenya Household Health Expenditure and Utilization Survey of 2007 found that 17 percent of those who needed health care services could not access the services from both government and private health facilities largely due to financial constraints. This paper employed econometric analysis to examine what could be constraining health care utilization in Kenya despite all the efforts employed. Methods: Using the 2007 Kenya Household Health Expenditures and Utilization Survey (KHHEUS) data (n = 8414), this paper investigates the factors that affect health care utilization in Kenya by estimating a count data negative binomial model. The model was also applied to public and private health facilities to better understand the specificities of poverty in these two facility types. Common estimation problems of endogeneity, heterogeneity, multicollinearity and heteroskedasticity are addressed. Findings: The econometric analysis reveals that out-of-pocket expenditures, waiting time, distance, household size, income, chronic illness area of residence and working status of the household head are significant factors affecting health care utilization in Kenya. While income and distance are significant factors affecting public health care utilization they are not significant in explaining healthcare utilization in private facilities. In addition, working status of the household head, insurance cover and education are significant in explaining private and not public health care utilization. A striking finding is the positive relationship between distance and health care utilization implying that people will travel long distances to obtain treatment. This is perhaps associated with expectations of higher quality of care at far away higher level facilities, especially in rural areas. Conclusion: The paper confirms the existing evidenc