Financial protection in health revisited: Is catastrophic health spending underestimated for service- or disease-specific analysis?

Economists originally developed methods to assess financial catastrophe using total or aggregate out-of-pocket health spending. Aggregate out-of-pocket health spending is financially catastrophic when it exceeds a fixed proportion (i.e., threshold) of a household's total income or expenditure in a given period. However, these methods are now applied to assess financial catastrophe in disease- or service-specific rather than aggregate out-of-pocket health spending without using disease- or service-specific thresholds. This paper argues that not using disease- or service-specific thresholds for such assessments is misleading and underestimates the burden of financial catastrophe, especially among households from poorer backgrounds. It then proposed disease- or service-specific catastrophic payment thresholds, applied them to Nigeria and found that financial catastrophe was underestimated for the five service groups considered. The paper stresses the importance of using disease- or service-specific thresholds and avoiding unadjusted thresholds, which may leave poorer households behind as financially protected.

Scaling up Maternal and Child Healthcare Delivery among Mission Hospitals in Southeast Nigeria: An Empirical Application of Data Envelopment Analysis for Setting Benchmarks and Targets.

The health system in many parts of Nigeria has been dysfunctional in several domains including financing, human resources, infrastructure, health management information system and hospital services. In an attempt to scale up Maternal and Child Health (MCH) services and ensure efficiency, Ebonyi State Government in Southeast Nigeria provided funding to mission hospitals across the State as a grant. This study used nonparametric method to assess the effect of this public financing on the efficiency of the mission hospitals. Operational cost and number of hospital beds were used as the input variables, while antenatal registrations, number of immunization doses and hospital deliveries were the output variables. The hospitals were disaggregated into 15 hospital-years. The mean overall technical efficiency of the mission hospitals was 84.05 22.45%. The mean pure technical efficiency was 95.56±6.9% and the scale efficiency was 88.05±22.20%. About 46.67% of all the hospital-years were technically and scale efficient. Although, 55.33% were generally inefficient, only 33.33% of hospital-years exhibited pure technical inefficiency. Low immunization coverage was the major cause of inefficiency. The study showed increased maternal health service output as result of public funding or intervention; however, the mission hospitals could have saved 16% of input resources if they had performed efficiently. It also shows that data envelopment analysis can be used in setting targets/benchmarks for relatively inefficient health facilities, and in monitoring impact of interventions on efficiency of hospitals over-time.

An Alternative Approach to Decomposing the Redistributive Effect of Health Financing Between and Within Groups Using the Gini Index: The Case of Out-of-Pocket Payments in Nigeria.

Equity in health financing remains significant in the universal health coverage discourse. The way a health system is financed, apart from determining whether people have access to needed health services, also has implications for income inequality in a country. Traditionally, the impact of health financing on income inequality or the redistributive effect of health financing is assessed by looking at whether income inequality reduces because of health financing. This is also decomposed into a vertical component (the extent of progressivity), a horizontal component (the extent to which households with similar incomes are treated equally when financing health services) and a reranking component (whether households change their relative socio-economic ranking after financing health services). Such an approach to decomposition is mainly essential to assess the equal treatment of equals and unequal treatment of unequals in the entire population. This paper argues that in decomposing the redistributive effect of health financing, the impact of health financing on changes in income inequality between and within population groups should be investigated as they are relevant for policy dialogues in many countries. It develops a framework for such analysis and applies this to data from Nigeria. Decomposing the Gini index of income inequality using the Shapley value approach, the results show that changes in inequality associated with out-of-pocket payments for health services within the geopolitical zones in Nigeria dominate the changes in income inequality between the geopolitical zones. Although not all the results in the application in this paper are statistically significant, this framework is still useful for policies in countries that aim to use health financing to reduce, among other things, income disparities between and within defined population groups.

Explaining socio-economic inequalities in immunization coverage in Nigeria.

Globally, in 2013 over 6 million children younger than 5 years died from either an infectious cause or during the neonatal period. A large proportion of these deaths occurred in developing countries, especially in sub-Saharan Africa. Immunization is one way to reduce childhood morbidity and deaths. In Nigeria, however, although immunization is provided without a charge at public facilities, coverage remains low and deaths from vaccine preventable diseases are high. This article seeks to assess inequalities in full and partial immunization coverage in Nigeria. It also assesses inequality in the 'intensity' of immunization coverage and it explains the factors that account for disparities in child immunization coverage in the country. Using nationally representative data, this article shows that disparities exist in the coverage of immunization to the advantage of the rich. Also, factors such as mother's literacy, region and location of the child, and socio-economic status explain the disparities in immunization coverage in Nigeria. Apart from addressing these issues, the article notes the importance of addressing other social determinants of health to reduce the disparities in immunization coverage in the country. These should be in line with the social values of communities so as to ensure acceptability and compliance. We argue that any policy that addresses these issues will likely reduce disparities in immunization coverage and put Nigeria on the road to sustainable development.

Scaling up maternal and child healthcare delivery among mission hospitals in Southeast Nigeria: an empirical application of data envelopment analysis for setting benchmarks and targets

The health system in many parts of Nigeria has been dysfunctional in several domains including financing, human resources, infrastructure, health management information system and hospital services. In an attempt to scale up Maternal and Child Health (MCH) services and ensure efficiency, Ebonyi State Government in Southeast Nigeria provided funding to mission hospitalsacross the State as a grant. This study used nonparametric method to assess the effect of this public financing on the efficiency of the mission hospitals. Operational cost and number of hospital beds were used as the input variables, while antenatal registrations, number of immunization doses and hospital deliveries were the output variables. The hospitals were disaggregated into 15 hospital-years. The mean overall technical efficiency of the mission hospitals was 84.05 22.45%. The mean pure technical efficiency was 95.56±6.9% and the scale efficiency was 88.05±22.20%. About 46.67% of all the hospital-years were technically and scale efficient. Although, 55.33% were generally inefficient, only 33.33% of hospital-years exhibited pure technical inefficiency. Low immunization coverage was the major cause of inefficiency. The study showed increased maternal health service output as result of public funding or intervention; however, the mission hospitals could have saved 16% of input resources if they had performed efficiently. It also shows that data envelopment analysis can be used in setting targets/benchmarks for relatively inefficient health facilities, and in monitoring impact of interventions on efficiency of hospitals over-time