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Budgeting based on need: a model to determine sub-national allocation of resources for health services in Indonesia

DOI: 10.1186/1478-7547-10-11

Keywords: Resource allocation, Costing, Benefits package

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Abstract:

A standardised costing methodology was developed that is sensitive to the main expected drivers of local cost variation including demographic structure, epidemiology and location. Essential package costing is often undertaken at a country level. It is less usual to utilise the methods across different parts of a country in a way that takes account of variation in population needs and location. Costing was based on best clinical practice in Indonesia and province specific data on distribution and costs of facilities. The resulting model was used to estimate essential package costs in a representative district in each province of the country.Substantial differences in the costs of providing basic services ranging from USD 15 in urban Yogyakarta to USD 48 in sparsely populated North Maluku. These costs are driven largely by the structure of the population, particularly numbers of births, infants and children and also key diseases with high cost/prevalence and variation, most notably the level of malnutrition. The approach to resource allocation was implemented using existing data sources and permitted the rapid construction of a needs based formula that is highly specific to the package mandated across the country. Refinement could focus more on resources required to finance demand side costs and expansion of the service package to include priority non-communicable services.Population health service needs are regionally specific in most countries. National health systems are faced with the dilemma of allocating resources to these areas to take account of need. Although historic, incremental systems were the norm in the past, countries increasingly make use of information on local needs to influence these allocations.The main approach to resource allocation has been to identify variables that explain need within a community and use them to develop weights for allocating resources between areas [1]. Early formulae included relatively crude proxies for need such as the (u

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