GCRF:Thanzi la Onse (Health of All): Frameworks and analysis to ensure value for money health care - developing theory, changing practice

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In all countries, difficult decisions are needed on how health care is financed, organised and provided for the benefit of populations. Decisions include how to determine and to secure appropriate levels of funding for health care; which interventions to fund; how to pool and distribute resources between geographical localities; and when to invest resources in strengthening key components of the health care system to improve the quality and coverage of existing interventions versus introducing new effective interventions. All health care systems face the reality that the cost of the available opportunities to enhance benefits always exceeds the available funding. The decisions made affect the kinds of interventions provided, who receives health care, who goes without and, ultimately, the magnitude of benefits to populations. Resources are particularly scarce in low-income countries.For example, total health care spending is US$39 per capita in Malawi, a country that is also highly dependent on aid, representing about 62% of that funding, resulting in local preferences regarding how resources are used having to be balanced against donors' priorities. In sub-Saharan African countries (such as Malawi), the opportunities for improving population benefits are great, but the consequences of getting these decisions wrong are potentially severe in terms of forgone benefits. Thanzi la Onse (TLO) provides an integrated programme of multi-disciplinary research to inform decisions in low-income settings on health care resource allocation. This challenging policy area lies at the intersection of health, economics and politics. The structure of this proposed research reflects that reality. The centrality of 'value for money' in determining domestic and international development activities is now widely accepted, particularly so in low-income countries, but tackling the challenges of policy formulation and resource allocation decisions, given the evidential and institutional constraints faced by health care systems in poor countries, remains an urgent research priority. This work will build research capability to address this need by evaluating alternative policy options in terms of locally-realised health benefits achieved through alternative spending commitments. This requires evaluating the benefits of any commitments and also what is foregone as a result of resource constraints prevailing in health care systems. Understanding the magnitude and distribution of such outcomes is key to ensuring value for money for spending on health.The value of specific interventions needs to be understood within the context of the health care system in which it is delivered. TLO will study the inter-relationships between the impact of different interventions and policies on population benefits and the range of characteristics of the system in terms of how it funds and delivers care, its weakness and constraints. Research to support decision-making also needs to recognise the potential barriers to its acceptance and implementation, requiring close links with policy-makers. Themes of research in epidemiology and health economics will be complemented by a third theme on politics and governance; realising inter-disciplinary complementarities which hitherto have not been fully exploited.The initial focus of TLO will be working with policy-makers and informing resource allocation decisions in Malawi and Uganda. This will include modelling the whole health system in Malawi to fully reflect its limited resources, the needs and characteristics of the population and the value of competing claims upon resources. Activities will receive international attention and inform the priorities of international organizations. Over the longer term, the programme is expected to work closely with policy-makers across the east, southern Africa region and beyond to ensure health care delivery is as fully informed as possible by leading research methods.