Cargando…
Applying the Community Health Worker Coverage and Capacity Tool for Time-Use Modeling for Program Planning in Rwanda and Zanzibar
Community health worker (CHW) programs are a critical component of health systems, notably in lower- and middle-income countries. However, when policy recommendations exceed what is feasible to implement, CHWs are overstretched by the volume of activities, implementation strength is diluted, and pro...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Global Health: Science and Practice
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7971371/ https://www.ncbi.nlm.nih.gov/pubmed/33727321 http://dx.doi.org/10.9745/GHSP-D-20-00324 |
Sumario: | Community health worker (CHW) programs are a critical component of health systems, notably in lower- and middle-income countries. However, when policy recommendations exceed what is feasible to implement, CHWs are overstretched by the volume of activities, implementation strength is diluted, and programs fail to produce promised outcomes. To counteract this, we developed a time-use modeling tool—the CHW Coverage and Capacity (C3) Tool—and used it with government partners in Rwanda and Zanzibar to address common policy questions related to CHW needs, coverage, and time optimization. In Rwanda, the C3 Tool was used to analyze 2 well-established cadres of CHWs and 1 new one. The well-established CHW cadres were within a “manageable” workload range whereas the new cadre was projected to achieve less than half of assigned activities. This is informing ongoing changes to the CHWs' scopes of work. In Zanzibar, the C3 Tool was used to update the national community health strategy to include community health volunteers (CHVs) for the first time and determine how many CHVs were needed. The tool projected that 2,200 CHVs could achieve approximately 90% coverage of all defined services. Based on these figures, Zanzibar updated its national community health strategy, which officially launched in February 2020. We discuss lessons from these 2 experiences. Translating analysis into decision making depends not only on the programmatic will and motivation of governments but also on finding opportune timing for when policy and program processes allow for optimization of CHW investments. Further research is needed but our experience supports the value of a modeling tool to ground program plans within estimated constraints on CHW time. |
---|