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The role of health systems infrastructure in studies of cost-effectiveness analysis and health resource allocation is discussed, and previous health sector cost-effectiveness analyses are cited. Two substantial difficulties concerning the nature of health system costs and the policy choices are presented. First, the issue of health system infrastructure can be addressed by use of computer models such as the Health Resource Allocation Model (HRAM) developed at Harvard, which integrates cost-effectiveness and burden of disease data. It was found that a model which allows for expansion in health infrastructure yields nearly 40% more total DALYs for a hypothetical sub-Saharan African country than a model which neglects infrastructure expansion. Widespread use of cost-effectiveness databases for resource allocations in the health sector will require the cost-effectiveness analyses shift from reporting costs to reporting production functions. Second, three distinct policy questions can be treated using these tools, each necessitating its own inputs and constraints: allocations when given a fixed budget and health infrastructure, or when given resources for marginal expansion, or when given a politically constrained situation of expanding resources. Confusion concerning which question is being addressed must be avoided through development of a consistent and rigorous approach to using cost-effectiveness data for informing resource allocations.A proposed method is presented by which the cost-effectiveness of investing in the physical and human infrastructure of the health system can be evaluated. The role of health systems infrastructure in studies of cost-effectiveness analysis and health resource allocation is discussed, and previous health sector cost-effectiveness analyses are cited. Two substantial difficulties concerning the nature of health system costs and the policy choices are presented. First, the issue of health system infrastructure can be addressed by use of computer models such as the Health Resource Allocation Model (HRAM) developed at Harvard in the General Algebraic Modeling System (GAMS), which integrates cost-effectiveness and burden of disease data. It was found that a model which allows for expansion in health infrastructure yields nearly 40% more total disability-adjusted life years (DALYs) for a hypothetical Sub-Saharan African country with a population of 10 million and GDP per capita of $340, than a model which neglects infrastructure expansion. The most important interventions by expenditure are screening and treatment of acute respiratory infections, malaria, tuberculosis, measles as well as promotion of oral rehydration therapy, breast-feeding, tetanus, and hygiene. Widespread use of cost-effectiveness databases for resource allocations in the health sector will require that cost-effectiveness analyses shift from reporting costs to reporting production functions. Distinct policy questions can be addressed with cost-effectiveness analysis, each necessitating its own inputs and constraints: 1) allocations when given a fixed budget and health infrastructure, or 2) when given resources for marginal expansion, or 3) when given a politically constrained situation of expanding resources. The development of a consistent approach to using cost-effectiveness data for informing resource allocations precludes confusion concerning which question must be addressed. Finally, some implications for future cost-effectiveness studies are highlighted. |
