In western Kenya, four counties are testing whether linking community and clinic digital health records can get more pregnant women to attend the eight antenatal care visits the WHO now recommends. Kenya’s 47 devolved counties have rapidly digitised health data, but the systems do not talk to each other. A woman might be registered by a community health volunteer but fall off the facility’s radar. This project—called C-it DU-it (see it, do it)—will link those data platforms so a single pregnancy can be tracked across both settings. It will also train community Work Improvement Teams to use the linked data to spot problems—missed appointments, gaps in care—and devise local fixes. If it works, the approach could give county health managers a real-time tool to schedule appointments and follow up with women who drop out. The trial will measure whether the linked data alone, or the data plus community action teams, actually increases the number of contacts per pregnancy. Because county officials are co-investigators, the results could feed directly into Kenyan health policy and, eventually, into similar systems in other low-resource settings.
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Facility and community health data is being rapidly digitised using multiple parallel systems across the 47 devolved counties in Kenya, but data do not link. Setting up community-based antenatal care (ANC) to complement facility-based ANC and data systems that link these platforms is essential to support Kenya in adopting WHO’s ambitious target of 8 ANC contacts. We propose to increase ANC uptake through a health systems strengthening approach that links digital data platforms and trains community Work Improvement Teams (WITs) to use these data to identify problems and come up with local solutions. Our short name C-it DU-it (pronounced “see-it; do-it”) is an acronym intended to convey ‘seeing’ linked data (C-it) and ‘doing’ or acting on the data (DU-it). Our objectives are: 1. To increase ANC uptake and quality in Western Kenya by a. linking community and facility digital ANC data systems, creating a system able to track an individual woman throughout pregnancy and schedule appointments (‘C-it’) b. strengthening the capacity of community WITs to use ‘C-it’ data for quality improvement and of community health volunteers to deliver community-based ANC contacts (‘DU-it’). 2. To co-develop research strategies with county policymakers that address evidence gaps to scale-up community health systems strengthening through ‘C-it DU-it’: a. evaluate what worked or did not work for whom and why b. establish the real-world effectiveness of ‘C-it’ and ‘C-it DU it’ on the number of ANC contacts c. determine the costs and cost-effectiveness of our approach from different perspectives d. assess the transferability of our approach to other counties, countries, and contexts 3. To strengthen the capacity of communities, county managers, Kenyan researchers, and institutions to set the community health research agenda and deliver major implementation research. The overarching research question we will seek to answer is “what is the effect of ‘C-it DU it’ on community health systems strengthening and what is required for effective transfer and scale-up?” We will use mixed methods implementation research to evaluate this in 4 counties in Western Kenya (Homa Bay, Migori, Kisumu, Kakamega). Realist evaluation will generate, empirically test and refine a transferrable programme theory to understand the causal relationship between context, participant response and outcomes. A 3-arm, cluster-randomised controlled superiority trial in Homa Bay County will determine the efficacy of ‘C-it’ and ‘C-it DU-it’ to increase ANC contacts when compared to the standard of care. Health economic evaluation and equity analysis will compare health expenditure of women accessing and engaging with ANC care and determine costs and cost-effectiveness of C-it Du-it from a health systems perspective. Qualitative interviews will assess transferability and iterative scale-up of C-it DU-it across the three remaining counties using toolkits developed in Homa Bay. The 4-year timeline is Year 1 inception; years 2-3 intervention, realist evaluation, trial and economic evaluation; year 2-4 scale-up will overlap and be iteratively informed by the results of the evaluations. We seek to answer questions that are of significant import globally, to the Kenyan government, to county level and for communities to have trust in the health system. Policy impact is likely as county officials are co-investigators, and policy and community engagement are central to the design.
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