C-it DU-it: Community Data Use for Integrated ANC Timeline: 4 years (Oct 2022 – Sep 2026)
Location: 4 counties in western Kenya (Homa Bay, Migori, Kisumu, Kakamega).
Partners:
• LVCT Health - the Lead Agency
• Kenya Medical Research Institute (KEMRI) – Collaborator
• Liverpool School of Tropical Medicine (LSTM) – Collaborator
• GinD - Collaborator


This research project aims to strengthen community health systems in Kenya by increasing antenatal care (ANC) uptake through a health systems strengthening approach. The approach will link digital data platforms and train community Work Improvement Teams (WITs) to use the data they collect to identify problems and develop local solutions. The project entails ‘seeing’ linked data (C-it) and ‘doing’ or acting on the data (DU-it). The study seeks to answer the question, “What is the effect of ‘C-it DU it’ on community health systems strengthening and what is required for effective transfer and scale-up?”

The project will enable smooth integration of data collected at both facility and community levels to track individuals from the community to facilities and back again. The study will pilot in Homa Bay County so as to introduce “C-IT DU-it” and increase the number of pregnant women achieving eight scheduled ANC contacts with a healthcare provider. The project will, from year 3, be scaled-up to the other three Kenyan Counties as an ideal way of transferring lessons.

The project will use mixed methods implementation research design with four components:
a) Realist evaluation will generate, empirically test and refine a transferrable programme theory to understand the causal relationship between context, participant response and outcomes.
b) A 3-arm, cluster-randomised controlled 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.
c) 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.
d) 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 study 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 work improvement teams to use ‘C-it’ data for quality improvement and of CHVs 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. to evaluate what worked or did not work for whom and why
b. to establish the real-world effectiveness of ‘C-it’ and ‘C-it DU it’ on the number of ANC contacts
c. to determine the costs and cost-effectiveness of ‘C-it’ and ‘C-it DU it’ from different perspectives
d. to 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

Target Population: Pregnant women in 4 counties in Western Kenya. These 4 counties (Homa Bay, Migori, Kisumu and Kakamega) have the highest maternal mortality rate in Kenya.

Project Outcomes: This study aims to strengthen community health systems in Kenya through antenatal care (ANC) data linkage and use while learning lessons for other contexts. Through this study the researchers will: 1) determine how counties can use digital data to integrate community-based with facility-based delivery of ANC services; 2) demonstrate how to scale up data use alongside digital data linkage at the community-facility interface and 3) improve the global frameworks for using robust data to track progress towards Universal Health Care (UHC).