Efficiency, equity and feasibility of strategies to identify the poor: An application to premium exemptions under National Health Insurance in Ghana
Introduction
Currently many sub-Saharan African countries are exploring ways to replace user fees at point of service use with more equitable alternatives. Indirect payment systems such as social and community health insurance are of increasing interest [1]. Whether with user fees or insurance financing, exemptions are needed for the poorest to improve equity. Apart from the challenges of how to mobilize and pool adequate resources to finance such systems, there are challenges with effectively identifying and targeting the most vulnerable groups for exemptions. In low income countries, these challenges are related in part to large non formal sectors and corresponding difficulties in assessing income and living standards to minimize errors of inclusion and exclusion; constrained health budgets to cover the costs of identification, as well as the financing of such mandates given the large numbers of poor and low tax base [2]. Feasibility concerns and trade-offs between equity and efficiency continue to be an important point of debate.
Ghana passed a National Health Insurance (NHI) act in 2003, as part of financing reforms to address financial access constraints especially for the poor and improve equity in access to affordable and good quality care. By the end of 2007 a total of 145 District Wide Mutual Health Insurance Schemes were established, and more than 11 million people had enrolled representing 55% of the population [3].
Despite such strides recent empirical evidence suggests enrolment among the informal sector (including the poor) is relatively low [4], [5], [6]. The NHI act makes a provision for premium exemptions for the core poor (indigents) [5], but only a small proportion actually benefits. This is in part due to implementation problems related to difficulties in identifying the poor in the absence of clear guidelines/criteria and lack of detailed costing analysis to implement and fund the mandate [14]. In addition, there is a group of people in the “very poor” category who fall between the indigent category and those able to pay the minimum premium. They represent 18% of the population [7]. This group requires special protection arrangements to benefits from the NHIS [8], [9]. Consequently, to adopt a pro-poor strategy to the implementation of the NHIS, strenuous efforts to identify and enrol the poor are required as repeatedly stressed in MOH health sector reviews [10], [11], and other documents [12], [13], [14].
Against this background, this paper aims to identify potential strategies to identify the poor, and to judge their efficiency, equity and feasibility. The paper first reviews local and international experiences on identification of the poor. Since identification of the poor is an issue of concern beyond the health sector, the review includes experiences in health and non-health sectors. Next, the paper estimates costs of each strategy, and presents the trade-offs between feasibility (defined as practical ability to identify the poor in a given context), efficiency (defined by cost per exempted poor individual, and equity (defined by error of exclusion) of the different strategies. Finally, results are translated into a set of clear policy recommendations. This work has relevance not only for the health sector in Ghana but for other low and middle income countries that are struggling with issues around equitable health care financial protection whether through premium exemption as part of health insurance systems, user fee exemptions or conditional cash transfers.
Section snippets
Materials and methods
We conducted a literature search in Medline using the following Keywords: alone and in combination: ‘poor’; ‘identification’; ‘poverty measurement’; ‘health insurance’; ‘welfare analysis’; ‘Africa’; ‘Latin America’; ‘Asia’; ‘Pacific’ or ‘developing countries’. Snowballing techniques; contacting of individual authors; and grey literature searches were used to identify other relevant articles. We excluded articles reporting on strategies with limited feasibility in the health sector. In total 62
Background
A substantial body of literature exists on strategies to identify and target the poor [23], [24], [25], [26], [27], [28], [29], [30], [31], [32], [33], [34], [35], [36], [37], [38], [39], [40], [41], [42], [43], [44]. An important distinction is made between welfare and non-welfare approaches, and between absolute and relative poverty lines. Also, several authors define conditions for successful strategies.
The welfare approach is the most commonly used way to measure poverty, and is based on
Costs of different strategies to identify the poor in Ghana
Fig. 1 shows the resulting cost estimates for a number of districts in the two regions studied, with details for two of its districts in Table 1.
In all districts in the Greater Accra Region, the costs of PMT and PWR are relatively low compared to GT (Fig. 1). The main reason is the relative low incidence of poverty in the districts. Whereas PMT and PWR only provide premium exemptions to those households who are identified as poor, GT exempts every household in the district, and thus incurs high
Discussion
This paper shows that proxy means testing (PMT), participatory welfare ranking (PWR), and geographic targeting (GT) achieve efficiency and equity objectives to different degrees. On the one hand, PWR appears the least costly and therefore most efficient strategy, but is also the least equitable. On the other hand, GT covers all (poor) individuals in a given area, and is therefore the most equitable but also the most costly. Our analysis reveals that the incremental costs of exempting one extra
Acknowledgements
The preparation of this document received financial support from the Ministry of Health and from the Netherlands Organization for Scientific Research (NWO) through the research grant for the project SHINE-Ghana “Reaching the poor in Ghana's National Health Insurance Scheme”. The authors would also like to thank Dr. Eddie Addai, Director of the Policy Planning Monitoring and Evaluation Division of the Ministry of Health, Ghana for his support. Special thanks also go to Agnes Kotoh, Daniel
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