Data Management Practices, Digitization, and Sustainability of Community Health Programmes in Nairobi County, Kenya

Abstract

Monitoring and evaluation data from community health programs are essential for their planning, improvement, success, and sustainability. These data can inform implementers, policymakers, beneficiaries, and funders about the progress or lack of it, prompting them to take appropriate action at any stage of the project life cycle. This study examines the moderating influence of digitization on the relationship between data management practices and sustainability of community health programmes. The study is anchored on Technology Acceptance Model (TAM). A positivist philosophical paradigm and a cross-sectional descriptive survey research design to generate quantitative primary data. A Partial Least Squares – Structural Equation Model (PLS-SEM) priori sample size calculator was used to determine a sample size based on all observable variables, including measurement indicators for the moderating variables. The sample comprised 190 community health promoters in Nairobi County. The response rate was 83%. Data analysis was performed using SmartPLS 4. The study results affirmed that the impact of data management practices on the sustainability of community health programmes decreases with digitalisation. The results resonate with the TAM, which posits that the adoption of innovations, such as data management automation, is influenced by perceived benefits and ease of use for users. This study recommends a hybrid data management approach that combines traditional and automated practices to address the transition and the digital divide. The findings of this study can also be used by policymakers and programme implementers to design programmes with greater specificity about where to invest when introducing or scaling up data digitisation, as well as to address contextual factors that contribute to the sustainability of community health programmes