Silvia Moler-Zapata1, Noémi Kreif2, Jessica Ochalek2, Andrew J Mirelman2, Mardiati Nadjib3, Marc Suhrcke2,4. 1. Department of Health Services Research and Policy, Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, WC1H 9SH, UK. silvia.moler@lshtm.ac.uk. 2. Centre for Health Economics, University of York, Heslington, York, YO10 5DD, UK. 3. Department of Health Policy and Administration, Faculty of Public Health, University of Indonesia, Depok, Indonesia. 4. Luxembourg Institute of Socio-economic Research, 4366, Esch-sur-Alzette, Luxembourg.
Abstract
BACKGROUND: The marginal productivity of a country's healthcare system refers to the health gains produced per unit change in the level of spending. In budget-constrained settings, this metric reflects the opportunity cost, in terms of health gains forgone, of committing additional or existing resources to alternative uses within the healthcare system. It can therefore assist in evidence-based decisions on whether different interventions represent good value for money. OBJECTIVE: The aim of this paper was to estimate the marginal productivity of the Indonesian healthcare system using subnational data, and to use this to inform health opportunity costs in the country. METHODS: We define a dynamic health production function to model the stream of effects of current and prior public health spending decisions on population under-five mortality. To estimate the model, we use data from the 33 Indonesian provinces for the 2004-2012 period. The estimated elasticity is then translated into gains in terms of cost per DALY (disability-adjusted life-year) averted. We use dynamic panel data methods to address potential endogeneity issues in the model. RESULTS: Our base-case estimates suggest that a 1% expansion in the level of health spending reduces under-five mortality by 0.38% (95% CI 0.00-0.76), which translates into a cost of averting one DALY of $235 (2019 US$). CONCLUSION: With Indonesia aiming for universal health coverage, our results support these efforts by highlighting the associated benefits resulting from increases in public health expenditure and have the potential to inform the decision-making process about a suitable locally relevant cost-effectiveness threshold.
BACKGROUND: The marginal productivity of a country's healthcare system refers to the health gains produced per unit change in the level of spending. In budget-constrained settings, this metric reflects the opportunity cost, in terms of health gains forgone, of committing additional or existing resources to alternative uses within the healthcare system. It can therefore assist in evidence-based decisions on whether different interventions represent good value for money. OBJECTIVE: The aim of this paper was to estimate the marginal productivity of the Indonesian healthcare system using subnational data, and to use this to inform health opportunity costs in the country. METHODS: We define a dynamic health production function to model the stream of effects of current and prior public health spending decisions on population under-five mortality. To estimate the model, we use data from the 33 Indonesian provinces for the 2004-2012 period. The estimated elasticity is then translated into gains in terms of cost per DALY (disability-adjusted life-year) averted. We use dynamic panel data methods to address potential endogeneity issues in the model. RESULTS: Our base-case estimates suggest that a 1% expansion in the level of health spending reduces under-five mortality by 0.38% (95% CI 0.00-0.76), which translates into a cost of averting one DALY of $235 (2019 US$). CONCLUSION: With Indonesia aiming for universal health coverage, our results support these efforts by highlighting the associated benefits resulting from increases in public health expenditure and have the potential to inform the decision-making process about a suitable locally relevant cost-effectiveness threshold.
Authors: Laura C Edney; James Lomas; Jonathan Karnon; Laura Vallejo-Torres; Niek Stadhouders; Jonathan Siverskog; Mike Paulden; Ijeoma P Edoka; Jessica Ochalek Journal: Pharmacoeconomics Date: 2021-09-29 Impact factor: 4.981