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Assessing value-for-money in maternal and newborn health.

Aduragbemi Oluwabusayo Banke-ThomasBarbara MadajShubha KumarCharles Anawo AmehNynke R van den Broek
Published in: BMJ global health (2017)
Responding to increasing demands to demonstrate value-for-money (VfM) for maternal and newborn health interventions, and in the absence of VfM analysis in peer-reviewed literature, this paper reviews VfM components and methods, critiques their applicability, strengths and weakness and proposes how VfM assessments can be improved. VfM comprises four components: economy, efficiency, effectiveness and cost-effectiveness. Both 'economy' and 'efficiency' can be assessed with detailed cost analysis utilising costs obtained from programme accounting data or generic cost databases. Before-and-after studies, case-control studies or randomised controlled trials can be used to assess 'effectiveness'. To assess 'cost-effectiveness', cost-effectiveness analysis (CEA), cost-utility analysis (CUA), cost-benefit analysis (CBA) or social return on investment (SROI) analysis are applicable. Generally, costs can be obtained from programme accounting data or existing generic cost databases. As such 'economy' and 'efficiency' are relatively easy to assess. However, 'effectiveness' and 'cost-effectiveness' which require establishment of the counterfactual are more difficult to ascertain. Either a combination of CEA or CUA with tools for assessing other VfM components, or the independent use of CBA or SROI are alternative approaches proposed to strengthen VfM assessments. Cross-cutting themes such as equity, sustainability, scalability and cultural acceptability should also be assessed, as they provide critical contextual information for interpreting VfM assessments. To select an assessment approach, consideration should be given to the purpose, data availability, stakeholders requiring the findings and perspectives of programme beneficiaries. Implementers and researchers should work together to improve the quality of assessments. Standardisation around definitions, methodology and effectiveness measures to be assessed would help.
Keyphrases
  • systematic review
  • randomized controlled trial
  • healthcare
  • public health
  • big data
  • case control
  • body mass index
  • electronic health record
  • climate change
  • social media
  • deep learning
  • weight loss
  • weight gain
  • birth weight