The investigators 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). The trial design is a 2-arm, cluster-randomised controlled superiority trial in Homa Bay County to determine the efficacy of 'C-it DU-it' intervention (data use arm) to increase ANC contacts when compared to the 'C-it' enhanced standard of care (control arm).

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. As of February 2023, national scale up of the national electronic community health information systems (eCHIS) for standard of care is ongoing, and there are increased efforts to scale-up use of the nationally approved Kenya Electronic Medical Records (KenyaEMR) Maternal and Child Health Module (MNH) to capture ANC, delivery and postnatal (PNC) data at health facilities. Data between eCHIS and Kenya EMR do not link. There are plans within the Community Health Division at national level to link eCHIS to facility EMRs, but this has yet to be developed. The investigators 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. The 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). The overarching research question the investigators 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?" The investigators will use mixed methods implementation research to evaluate this in 4 counties in Western Kenya (Homa Bay, Migori, Kisumu, Kakamega) over a period of four years. The proposed methods include: (a) Realist evaluation to generate, empirically test and refine a transferrable programme theory to understand the causal relationship between context, participant response and outcomes; (b) A 2-arm, cluster-randomised controlled superiority trial in Homa Bay County to determine the efficacy of 'C-it DU-it' intervention (data use arm) to increase ANC contacts when compared to the 'C-it' enhanced standard of care (control arm); (c) Health economic evaluation and equity analysis to compare costs and catastrophic 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; and (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. This protocol describes the pragmatic cluster randomised trial and health economic evaluation. The realist evaluation and scale up will be addressed in a separate sister protocol.

Inclusion Criteria:

• Pregnant women of all ages willing to participate
• Written informed consent
• A resident of the study area (catchment area) for the duration of the pregnancy
• Delivered and still within the 6-week post-partum period.

Exclusion Criteria:

• Currently enrolled in another interventional study targeting pregnant women
• Outside the 6-week post-partum period.

Pregnant women

Data will be shared via data transfer agreements with the collaborating institutions to minimise the risk of unauthorised analysis beyond the scope of the agreed parameters. The full protocol will be available on request to any interested professional and may be published in a peer-reviewed journal or deposited in an online repository. Individual, de-identified participant data will be made available for meta-analyses as soon as the data analysis is completed, with the understanding that the meta-analysis results will not be published before the individual trial results without the prior agreement of the investigators. The de-identified data set of the complete participant-level data will be available for sharing purposes. A Data Access Committee will consider all requests for data for secondary analysis to ensure that the use of data is within the terms of consent and ethics approval and in line with the Kenya Data Protection Act 2019.

The full anonymised research database will be made publicly available as soon as the full study findings have been published or based on any data requests that may occur during the study or analysis is still ongoing.

Data access will be provided to researchers after a proposal has been approved by an independent review committee identified for this purpose. An agreement on how to collaborate will be reached based on any overlap between the proposal and any ongoing efforts. Proposals can be directed to email addresses provided in the publications and websites. To gain access, data requesters will need to sign a data-sharing agreement.