Using Top-down and Bottom-up Costing Approaches in LMICs: The Case for Using Both to Assess the Incremental Costs of New Technologies at Scale.


Cunnama, L; Sinanovic, E; Ramma, L; Foster, N; Berrie, L; Stevens, W; Molapo, S; Marokane, P; McCarthy, K; Churchyard, G; Vassall, A; (2016) Using Top-down and Bottom-up Costing Approaches in LMICs: The Case for Using Both to Assess the Incremental Costs of New Technologies at Scale. Health economics, 25 Suppl 1. pp. 53-66. ISSN 1057-9230 DOI: https://doi.org/10.1002/hec.3295

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Abstract

PURPOSE: Estimating the incremental costs of scaling-up novel technologies in low-income and middle-income countries is a methodologically challenging and substantial empirical undertaking, in the absence of routine cost data collection. We demonstrate a best practice pragmatic approach to estimate the incremental costs of new technologies in low-income and middle-income countries, using the example of costing the scale-up of Xpert Mycobacterium tuberculosis (MTB)/resistance to riframpicin (RIF) in South Africa.<br/> MATERIALS AND METHODS: We estimate costs, by applying two distinct approaches of bottom-up and top-down costing, together with an assessment of processes and capacity.<br/> RESULTS: The unit costs measured using the different methods of bottom-up and top-down costing, respectively, are $US16.9 and $US33.5 for Xpert MTB/RIF, and $US6.3 and $US8.5 for microscopy. The incremental cost of Xpert MTB/RIF is estimated to be between $US14.7 and $US17.7. While the average cost of Xpert MTB/RIF was higher than previous studies using standard methods, the incremental cost of Xpert MTB/RIF was found to be lower.<br/> CONCLUSION: Costs estimates are highly dependent on the method used, so an approach, which clearly identifies resource-use data collected from a bottom-up or top-down perspective, together with capacity measurement, is recommended as a pragmatic approach to capture true incremental cost where routine cost data are scarce.<br/>

Item Type: Article
Faculty and Department: Faculty of Public Health and Policy > Dept of Global Health and Development
Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology
Research Centre: Social and Mathematical Epidemiology (SaME)
SaME Modelling & Economics
Related URLs:
PubMed ID: 26763594
Web of Science ID: 368859100006
URI: http://researchonline.lshtm.ac.uk/id/eprint/2528162

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