Abstract
BACKGROUND: Out-of-pocket (OOP) payment on healthcare is dominant mode of financing in developing countries. In Pakistan it is 67% of total expenditure on healthcare. Analysis of determinants of OOP health expenditure is a key aspect of equity in healthcare financing. It helps to formulate an effective health policy. Evidence on OOP in Pakistan is sparse. This paper attempts to fill this research gap. METHODS: We estimated determinants of OOP payments on healthcare in Pakistan. We used data sets of Pakistan Household Integrated Economic Survey (HIES) and Pakistan Standard of Living Measurement (PSLM) Survey for the year 2004-05. We developed a multiple regression model for the determinants of OOP payments using methods of Ordinary Least Square (OLS). We mainly used social, economic, demographic and health variables in our analysis. RESULTS: Median household OOP healthcare in the year 2004-05 was Pakistani Rupees (PKR) 2500 (US$ 41.99) in 2004-05. Household non-food expenditure was the single highest significant predictor of household OOP health expenditure. Household features like literate head and spouse, at least one obstetric delivery in last three years, unsafe water, unhygienic toilet and household belonging to Khyber Pukhtonkhwa (KPK) province were significant positive predictors of OOP payments. Households with male head, bricks used in housing construction, household with at least one child and no elderly, and head of household in a white collar profession were negative predictors of OOP payments. CONCLUSION: Our analysis confirms earlier findings that economic status and number of old aged members are significant positive predictors of OOP payments. This association can direct government to enhance allocations to healthcare and to include program focusing on non-communicable diseases. Our findings suggest further research to explore beneficiaries of government healthcare programs and determinants of high OOP payments by household residing in KPK province than other province. The interaction between white collar profession and their economic status in predicting OOP payments is also an area for further research.