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Supporting the development of a health benefits package in Malawi
  1. Jessica Ochalek1,
  2. Paul Revill1,
  3. Gerald Manthalu2,
  4. Finn McGuire3,
  5. Dominic Nkhoma4,
  6. Alexandra Rollinger1,
  7. Mark Sculpher1,
  8. Karl Claxton1
  1. 1 Centre for Health Economics, University of York, York, UK
  2. 2 Department of Planning and Policy Development, Ministry of Health, Lilongwe, Malawi
  3. 3 Department of Global Health and Development, London School of Hygiene and Tropical Medicine, London, UK
  4. 4 Ministry of Agriculture, Irrigation and Water Development, Lilongwe, Malawi
  1. Correspondence to Jessica Ochalek, Centre for Health Economics, University of York, York, UK ; jessica.ochalek{at}, jessica.ochalek{at}


Malawi, like many low-income and middle-income countries, has used health benefits packages (HBPs) to allocate scarce resources to key healthcare interventions. With no widely accepted method for their development, HBPs often promise more than can be delivered, given available resources. An analytical framework is developed to guide the design of HBPs that can identify the potential value of including and implementing different interventions. It provides a basis for informing meaningful discussions between governments, donors and other stakeholders around the trade-offs implicit in package design. Metrics of value, founded on an understanding of the health opportunity costs of the choices faced, are used to quantify the scale of the potential net health impact (net disability adjusted life years averted) or the amount of additional healthcare resources that would be required to deliver similar net health impacts with existing interventions (the financial value to the healthcare system). The framework can be applied to answer key questions around, for example: the appropriate scale of the HBP; which interventions represent ‘best buys’ and should be prioritised; where investments in scaling up interventions and health system strengthening should be made; whether the package should be expanded; costs of the conditionalities of donor funding and how objectives beyond improving population health can be considered. This is illustrated using data from Malawi. The framework was successfully applied to inform the HBP in Malawi, as a core component of the country’s Health Sector Strategic Plan II 2017–2022.

  • health systems
  • health policy
  • health economics

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  • Handling editor Seye Abimbola

  • Contributors All authors contributed to the concept and design of this paper. JO led the manuscript drafting with PR, MS and KC. It was edited by all authors with substantial contributions from GM and FM and approved by all authors. This paper draws on a visit by JO to the Malawi Ministry of Health hosted by GM, DN and FM and a workshop on health economics in Lilongwe, Malawi organised by PR and AR, in which all authors participated and which contributed to the conceptual design of this research.

  • Funding This study was funded by ESRC Impact Acceleration Account, York External Engagement Award, Bill and Melinda Gates Foundation (grant number: OPP1165566).

  • Competing interests None declared.

  • Patient consent Not required.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data sharing statement In addition to published empirical estimates of the costs and effects of health interventions from the Tufts Global Health Cost-Effectiveness Registry and World Health Organization CHOosing Interventions that are Cost-Effective (WHO-CHOICE) analyses, this article relied on unpublished data on drug and supply costs, the size of the eligible patient population and the levels to which interventions were actually implemented in Malawi. Data on drug and supply costs were made available from a2014 costing mid-term review of the previous HSSP made available by in-country partners Palladium and the Clinton Health Access Initiative (CHAI) and an assessment of the size of the eligible patient population for each intervention and the levels to which interventions were actually implemented in Malawi in2014 use bottleneck analysis and data from CHAI.

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