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Our approach

At the heart of our approach is the belief that data linkage is essential for effective health service delivery. By integrating community and facility digital antenatal care (ANC) data systems, we can create a comprehensive framework that allows for continuous tracking of individual women throughout their pregnancies. This not only helps schedule appointments but also improves the overall quality and uptake of ANC services.

our-approach

Our approach

At the heart of our approach is the belief that data linkage is essential for effective health service delivery. By integrating community and facility digital antenatal care (ANC) data systems, we can create a comprehensive framework that allows for continuous tracking of individual women throughout their pregnancies. This not only helps schedule appointments but also improves the overall quality and uptake of ANC services.

our-approach

Photo credit: Anouk Delafortrie for the European Union, via Flickr.

The C-it DU-it study targets the interface between the community and the facility. Data linkage for data use is at its heart with ANC picked as an example of what is possible. 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).

We aim to:

  • Increase ANC Uptake and Quality: By integrating community and facility ANC data systems, we can track individual women throughout their pregnancy and improve service delivery.
  • Research Co-development: We collaborate with policymakers to address evidence gaps and support the scaling up of community health systems.
  • Capacity Building: We empower communities and county managers to set the health research agenda and implement key initiatives.

Our research will be conducted in Homa Bay before scale up to Kisumu, Migori and Kakamega.

  • A realistic evaluation will tell us how, why and for whom the approach worked or did not work. Understanding the relationship between the county context, how people responded and outcomes (e.g., political agendas; team working; motivation; local pregnancy beliefs) makes it easier to adapt the approach to other contexts.
  • A pragmatic cluster-randomised controlled trial in Homa Bay will tell us the impact of linking digital data and the added value (if any) of combining this with training work improvement teams in data use to drive ANC uptake. We will measure the impact on the number of ANC visits and the effects on pregnancy outcomes and quality of care.
  • Health economic evaluation will identify whether C-it DU it reduces health expenditure for pregnant women accessing and engaging with ANC care and whether the intervention is cost effective.
  • We will adapt and scale-up the interventions using toolkits developed in the trial county to control clusters and three additional counties. There will be a chance to refine as results from our research emerge.

This research is funded by the NIHR (GH 150178) using UK aid from the UK Government to support global health research. The views expressed in this publication are those of the author(s) and not necessarily those of the NIHR or the UK government.