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Incorporating Demand and Supply Constraints into Economic Evaluations in Low‐Income and Middle‐Income Countries


  • Anna Vassall
  • Lindsay Mangham‐Jefferies
  • Gabriela B. Gomez
  • Catherine Pitt
  • Nicola Foster


Global guidelines for new technologies are based on cost and efficacy data from a limited number of trial locations. Country‐level decision makers need to consider whether cost‐effectiveness analysis used to inform global guidelines are sufficient for their situation or whether to use models that adjust cost‐effectiveness results taking into account setting‐specific epidemiological and cost heterogeneity. However, demand and supply constraints will also impact cost‐effectiveness by influencing the standard of care and the use and implementation of any new technology. These constraints may also vary substantially by setting. We present two case studies of economic evaluations of the introduction of new diagnostics for malaria and tuberculosis control. These case studies are used to analyse how the scope of economic evaluations of each technology expanded to account for and then address demand and supply constraints over time. We use these case studies to inform a conceptual framework that can be used to explore the characteristics of intervention complexity and the influence of demand and supply constraints. Finally, we describe a number of feasible steps that researchers who wish to apply our framework in cost‐effectiveness analyses.

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  • Anna Vassall & Lindsay Mangham‐Jefferies & Gabriela B. Gomez & Catherine Pitt & Nicola Foster, 2016. "Incorporating Demand and Supply Constraints into Economic Evaluations in Low‐Income and Middle‐Income Countries," Health Economics, John Wiley & Sons, Ltd., vol. 25(S1), pages 95-115, February.
  • Handle: RePEc:wly:hlthec:v:25:y:2016:i:s1:p:95-115
    DOI: 10.1002/hec.3306

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    References listed on IDEAS

    1. Yoko Laurence & Ulla Griffiths & Anna Vassall, 2015. "Costs to Health Services and the Patient of Treating Tuberculosis: A Systematic Literature Review," PharmacoEconomics, Springer, vol. 33(9), pages 939-955, September.
    2. Richard Grieve & Richard Nixon & Simon G. Thompson & Charles Normand, 2005. "Using multilevel models for assessing the variability of multinational resource use and cost data," Health Economics, John Wiley & Sons, Ltd., vol. 14(2), pages 185-196, February.
    3. Fern Terris‐Prestholt & Matthew Quaife & Peter Vickerman, 2016. "Parameterising User Uptake in Economic Evaluations: The role of discrete choice experiments," Health Economics, John Wiley & Sons, Ltd., vol. 25(S1), pages 116-123, February.
    4. Nicolas A Menzies & Ted Cohen & Hsien-Ho Lin & Megan Murray & Joshua A Salomon, 2012. "Population Health Impact and Cost-Effectiveness of Tuberculosis Diagnosis with Xpert MTB/RIF: A Dynamic Simulation and Economic Evaluation," PLOS Medicine, Public Library of Science, vol. 9(11), pages 1-17, November.
    5. Anna Vassall & Sanne van Kampen & Hojoon Sohn & Joy S Michael & K R John & Saskia den Boon & J Lucian Davis & Andrew Whitelaw & Mark P Nicol & Maria Tarcela Gler & Anar Khaliqov & Carlos Zamudio & Mar, 2011. "Rapid Diagnosis of Tuberculosis with the Xpert MTB/RIF Assay in High Burden Countries: A Cost-Effectiveness Analysis," PLOS Medicine, Public Library of Science, vol. 8(11), pages 1-14, November.
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    Cited by:

    1. Catherine Pitt & Catherine Goodman & Kara Hanson, 2016. "Economic Evaluation in Global Perspective: A Bibliometric Analysis of the Recent Literature," Health Economics, John Wiley & Sons, Ltd., vol. 25(S1), pages 9-28, February.
    2. Catherine Pitt & Anna Vassall & Yot Teerawattananon & Ulla K. Griffiths & Lorna Guinness & Damian Walker & Nicola Foster & Kara Hanson, 2016. "Foreword: Health Economic Evaluations in Low‐ and Middle‐income Countries: Methodological Issues and Challenges for Priority Setting," Health Economics, John Wiley & Sons, Ltd., vol. 25(S1), pages 1-5, February.

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