A retrospective review of the Honduras AIN-C program guided by a community health worker performance logic model
Daniela C Rodríguez1, Lauren A Peterson2
1Department of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N. Wolfe Street, Rm. E-8612, Baltimore, MD, 21205, USA. drodri17@jhu.edu.
Background:
Factors that influence performance of community health workers (CHWs) delivering health services are not well understood. A recent logic model proposed categories of support from both health sector and communities that influence CHW performance and program outcomes. This logic model has been used to review a growth monitoring program delivered by CHWs in Honduras, known as Atención Integral a la Niñez en la Comunidad (AIN-C).
Methods:
A retrospective review of AIN-C was conducted through a document desk review and supplemented with in-depth interviews. Documents were systematically coded using the categories from the logic model, and gaps were addressed through interviews. Authors reviewed coded data for each category to analyze program details and outcomes as well as identify potential issues and gaps in the logic model.
Results:
Categories from the logic model were inconsistently represented, with more information available for health sector than community. Context and input activities were not well documented. Information on health sector systems-level activities was available for governance but limited for other categories, while not much was found for community systems-level activities. Most available information focused on program-level activities with substantial data on technical support. Output, outcome, and impact data were drawn from various resources and suggest mixed results of AIN-C on indicators of interest.
Conclusions:
Assessing CHW performance through a desk review left gaps that could not be addressed about the relationship of activities and performance. There were critical characteristics of program design that made it contextually appropriate; however, it was difficult to identify clear links between AIN-C and malnutrition indicators. Regarding the logic model, several categories were too broad (e.g., technical support, context) and some aspects of AIN-C did not fit neatly in logic model categories (e.g., political commitment, equity, flexibility in implementation). The CHW performance logic model has potential as a tool for program planning and evaluation but would benefit from additional supporting tools and materials to facilitate and operationalize its use.
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