Decision analytic models in the economic evaluation of community health worker programmes globally: a systematic review
File(s)
Published version
Author(s)
Chen, Siying
Banstola, Amrit
Junghans Minton, Cornelia
Harris, Matthew
Anokye, Nana
Type
Journal Article
Abstract
Introduction: Economic evidence on Community Health Worker (CHW) programmes is crucial for scaling these initiatives. Although Decision-Analytic Models (DAMs) are essential for projecting long-term value, it is unclear how rigorously they have been applied to CHW evaluations, potentially compromising the reliability and comparability of cost-effectiveness estimates used for policy decisions.
Methods: A systematic review was conducted to identify full economic evaluations of CHW-led or CHW-integrated interventions that employed a DAM. Following PRISMA guidelines, six databases (Medline, Embase, Global Health, CINAHL, Web of Science and Scopus) were searched from inception to June 2025. Eligible studies were full economic evaluations assessing CHW-led or CHW-integrated interventions using DAMs. Study selection and data extraction were conducted independently by two reviewers. Methodological quality was appraised using the Philips checklist, and data were extracted on model type, data sources, and validation practices. Findings were synthesised narratively across model structures, income groups, and quality domains.
Results: Thirty-seven studies met the inclusion criteria. Decision trees were used in 32% of studies and Markov models in 30%, with the remainder applying microsimulation, dynamic transmission or hybrid approaches. Most evaluations were undertaken in low- and middle-income countries (LMICs), with few from low-income or high-income settings. Data constraints in low-income settings limited model complexity, whereas models in high-income settings tended to adopt more sophisticated structures but narrower intervention scopes. The mean quality score was 67%, with substantial gaps in model validation and limited exploration of structural uncertainty. Overall, 84% of studies concluded that CHW-led interventions were cost-effective, with ICERs generally favourable across settings.
Conclusion: Although CHW interventions are generally cost-effective, the strength of this evidence is constrained by methodological limitations in existing models. Future modelling should prioritise rigorous validation, localisation of input data, and explicit valuation of CHW and societal contributions to enhance the credibility of economic evidence for policy use.
Funding: This study was supported by the NIHR Applied Research Collaboration Northwest London.
PROSPERO registration number: CRD420251066586.
Methods: A systematic review was conducted to identify full economic evaluations of CHW-led or CHW-integrated interventions that employed a DAM. Following PRISMA guidelines, six databases (Medline, Embase, Global Health, CINAHL, Web of Science and Scopus) were searched from inception to June 2025. Eligible studies were full economic evaluations assessing CHW-led or CHW-integrated interventions using DAMs. Study selection and data extraction were conducted independently by two reviewers. Methodological quality was appraised using the Philips checklist, and data were extracted on model type, data sources, and validation practices. Findings were synthesised narratively across model structures, income groups, and quality domains.
Results: Thirty-seven studies met the inclusion criteria. Decision trees were used in 32% of studies and Markov models in 30%, with the remainder applying microsimulation, dynamic transmission or hybrid approaches. Most evaluations were undertaken in low- and middle-income countries (LMICs), with few from low-income or high-income settings. Data constraints in low-income settings limited model complexity, whereas models in high-income settings tended to adopt more sophisticated structures but narrower intervention scopes. The mean quality score was 67%, with substantial gaps in model validation and limited exploration of structural uncertainty. Overall, 84% of studies concluded that CHW-led interventions were cost-effective, with ICERs generally favourable across settings.
Conclusion: Although CHW interventions are generally cost-effective, the strength of this evidence is constrained by methodological limitations in existing models. Future modelling should prioritise rigorous validation, localisation of input data, and explicit valuation of CHW and societal contributions to enhance the credibility of economic evidence for policy use.
Funding: This study was supported by the NIHR Applied Research Collaboration Northwest London.
PROSPERO registration number: CRD420251066586.
Date Issued
2026-06-01
Date Acceptance
2026-06-05
Citation
BMJ Global Health, 2026, 11 (6)
ISSN
2059-7908
Publisher
BMJ Publishing Group
Journal / Book Title
BMJ Global Health
Volume
11
Issue
6
Copyright Statement
© 2026 The Author(s). This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license
License URL
Identifier
10.1136/bmjgh-2025-023076
Publication Status
Published
Article Number
e023076
Date Publish Online
2026-06-22