How to do (or not to do) . . . translation of national health accounts data to evidence for policy making in a low resourced setting

摘要

For more than a decade, the Organization for Economic Co-operation and Development (OECD), the World Health Organization (WHO) and the World Bank have promoted the international standardization of National Health Accounts (NHA) for reporting global statistics on public, private and donor health expenditure and improve the quality of evidence-based decision-making at country level. A 2010-2012 World Bank review of NHA activity in 50 countries found structural and technical constraints (rather than cost) were key impediments to institutionalizing NHA in many low-and middle-income countries (LMICs). Pilot projects focused resources on data production, neglecting longer-term capacity building for analysing the data, developing ownership among local stakeholders and establishing routine production, utilization and dissemination of NHA data. Hence, genuine institutionalization of NHA in most LMICs has been slow to materialize. International manuals focus on the production of NHA data and do not include practical, incremental and low-cost strategies to guide countries in translating the data into evidence for policy-making. The main aim of this article is to recommend strategies for bridging this divide between production and utilization of NHA data in low-resource settings. The article begins by discussing the origins and purpose of NHA, including factors currently undermining their uptake. The focus then turns to the development and application of strategies to assist LMICs in 'unlocking' the hidden value of their NHA. The article draws on the example of Fiji, a country currently attempting to integrate their NHA data into policy formulation, despiteminimal resources, training and familiarity with economic analysis of health systems. Simple, low cost recommendations such as embedding health finance indicators in planning documents, a user-friendly NHA guide for evaluating local health priorities, and sharing NHA data for collaborative research have helped translate NHA from raw data to evidence for policymaking.