A needs-based approach to equitable allocation of district primary healthcare expenditure in North West Province, South Africa
Background. Inequity in resource allocation and expenditure exists in the South African (SA) health system at provincial and district level. Needs-based resource allocation has been utilised in developed and developing countries to promote equity.
Objectives. To assess current spending patterns on primary healthcare (PHC)-level care at district level, and ultimately to promote equity in district PHC spending using a needs-based resource allocation approach in North West Province, SA.
Methods. Data on PHC expenditure in 2013/14 were derived from the Vulindlela system. Data on key indicators of need for health services in each district were collated from various sources published online. Alternative needs-based formulae were calculated, and sensitivity analyses were conducted to assess the impact of key assumptions.
Results. The analysis produced four possible needs-based formulae. The districts of Bojanala and Dr Kenneth Kaunda in North West are relatively under-resourced, while Ngaka Moderi Molema and Dr Ruth Segomotsi Mompati are relatively over-resourced. The results suggest that, in moving towards each district’s equity target, a relative redistribution of resources should be undertaken over several years, preferably in the context of an annual increase in the real overall provincial PHC health budget, to avoid any absolute budget cuts for relatively overresourced districts.
Conclusions. Inequity in PHC expenditure exists between the districts of North West. A needs-based resource allocation approach can promote equity across districts. Any formula selected by the Department of Health will need to be refined over time as more up-to-date and accurate data become available. It is recommended that for the initial phase the formula be based on population size, which will need to be updated at regular intervals. The same would apply to other indicators of need selected for the formula. Important areas for refining the formula over time are: (i) estimating the differential cost of providing care in rural v. urban areas, as assumptions were used in this study; and (ii) identifying a more comprehensive burden of disease indicator for which data are available at district level in the province.
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