Impact of Architecture of Health Care Financing In Nepal
Recent data suggested that total health expenditure accounted for 5.5% of Nepal’s Gross Domestic Product (GDP), an amount that was close to the average of 5% for other low-income countries but well below the global average of 9.2% (WHO, 2012). Public allocations to fund the health sector were around 10% of total government expenditure. This was higher than the average of 8.1% for other low-income countries and demonstrates government commitment to funding the health sector. In fact, government health expenditure translated into only 2.2% of GDP. While this amount was slightly higher than the low-income country average for that year of 1.9%, it was low for what is essentially the mandatory pre-paid component of a health financing system. The global average, for example, was 5.3%. A good sign, though, is that the 2012 percentage was considerably higher than a decade ago, when the figure was around 1.5% (MOHP, 2011). In 2012, per capita government expenditure on health was around $32 (in terms of purchasing power parity), higher than the low-income country average of $25 but twenty times less than the global average of $652.
Out-of-pocket payments (OOP) were the principal source of financing for health care (at almost half of total financing in 2012). This was around the low-income average but high in global terms (where the average was 21%). It was also well above the 20% limit suggested by the 2010 World Health Report to ensure that financial catastrophe and impoverishment as a result of accessing health care become negligible (World Health Organisation 2010). Private health insurance was negligible in Nepal.
Catastrophic payments due to OOP in different thresholds are increasing over the years. Surprisingly concentration indices for NLSS 2010/11 are found negative, which suggests that mean catastrophic payments are skewed to poor people. Households having higher number of under-five children and elderly are more likely to incur catastrophic payments. Households in Tarai region are more likely to incur catastrophic payments in terms of OOPs and medical expenditure. Impoverishment impacts due to OOP in different thresholds are increasing over the years. Surprisingly poverty gap for NLSS 2010/11 is significantly higher (around 4%). Results from synthetic data analysis suggested that probability of being catastrophic to catastrophic or permanent catastrophic is significantly higher, for example, 13% due to OOP and 7% due to medicine at 10 % threshold. This indicates that nearly 2% of HH remain permanent poor owning to OOP expenditure in health. Synthetic panel provides some additional information how OOP can make impoverishing impact on households.