Abstract
In low- and middle-income countries (LMICs), making the best use of scarce resources is essential to achieving universal health coverage. The design of health benefits packages creates the opportunity to select interventions on the basis of explicit objectives. Distributional cost-effectiveness analysis (DCEA) provides a framework to evaluate interventions based on two objectives: increasing population health and reducing health inequality. We conduct aggregate DCEA of potential health benefits package interventions to demonstrate the feasibility of this approach in LMICs, using the case of the Malawian health benefits package. We use publicly available survey and census data common to LMICs and describe what challenges we encountered and how we addressed them. We estimate that diseases targeted by the health benefits package are most prevalent in the poorest population quintile and least prevalent in the richest quintile. The survey data we use indicate socioeconomic patterns in intervention uptake that diminish the population health gain and inequality reduction from the package. We find that a similar set of interventions would be prioritized when impact on health inequality is incorporated alongside impact on overall population health. However, conclusions about the impact of individual interventions on health inequalities are sensitive to assumptions regarding the health opportunity cost, the utilization of interventions, the distribution of diseases across population groups and the level of aversion to inequality. Our results suggest that efforts to improve access to the Essential Health Package could be targeted to specific interventions to improve the health of the poorest fastest but that identifying these interventions is uncertain. This exploratory work has shown the potential for applying the DCEA framework to inform health benefits package design within the LMIC setting and to provide insight into the equity impact of a health benefits package.
Highlights
Recent examples from low and middle-income countries (LMICs) in Africa (Todd et al, 2016) and Latin America (Giedion et al, 2014) demonstrate the use of health benefits packages as a means of focusing scarce resources on interventions that provide the best value for money (Glassman et al, 2016)
We focus on the reduction in inequality in health-adjusted life expectancy (HALE) and the inequality associated with two socioeconomic characteristics: household wealth and urban vs rural residence
There are 44 million cases of illness that qualify for treatment with one of the 51 Essential Health Package (EHP) interventions reported in the health sector strategic plan (Government of the Republic of Malawi, 2017)
Summary
Recent examples from low and middle-income countries (LMICs) in Africa (Todd et al, 2016) and Latin America (Giedion et al, 2014) demonstrate the use of health benefits packages as a means of focusing scarce resources on interventions that provide the best value for money (Glassman et al, 2016). When combined with an estimate of the DALYs that could be averted with alternative uses of health sector funds, this allows interventions to be ranked based on the net DALYs averted. This is useful if the objective is to maximize population health benefits, i.e. DALYs averted, from the available budget. In Malawi, as in many LMICs, the intention is that the health benefits packages address another key consideration, namely equity in health, healthcare access and use.
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