Digital Data Linkage and Scheduling to Track Pregnancy With or Without Community Data Use to Increase Antenatal Clinic Uptake in Western Kenya. (C-it-DU-it)

Liverpool School of Tropical Medicine

Status: Not yet enrolling

Conditions: Electronic Community Health Information Systems; Antenatal Clinic Uptake; Pregnancy; Health Systems

Treatments: Other: The combined "C-it DU-it" intervention: community data use for ANC

Study type: Interventional

Funder types: Other

Identifiers

NCT05929586

22-073

Details and patient eligibility

About

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).

Full description

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.

Enrollment: 1,440 estimated patients

Sex: Female

Volunteers: Accepts Healthy Volunteers

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.

Trial design

Primary purpose: Health Services Research

Allocation: Randomized

Interventional model: Parallel Assignment

Masking: None (Open label)

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1,440 participants in 2 patient groups

Digital data linkage and scheduling ('C-it'): The "C-it" enhanced standard of care

No Intervention group

Description:

Linking facility to community digital data via linkage-app: Data between electronic Community Health Information System (eCHIS) and facility-based Kenya Electronic Medical Record (Kenya EMR) do not link. We do not have an existing digital data linkage module or app to track successful pregnancy referrals or allow the facility staff to view community contacts and vice versa. We will engage with national and county teams and software developers to build a digital data linkage module, linking eCHIS and Kenya EMR Maternal and Child Health (MCH) module.

The combined "C-it DU-it" intervention: community data use for ANC

Experimental group

Description:

Combining "C-it" and work improvement teams (WITs) for community data use: We will establish and train integrated WITs in intervention sites consisting of community health members, health facility staff and community members and train them on how they will use linkage-app. The resultant combined "C-it DU-it" intervention has three building blocks: We make the following assumptions about the building blocks at the bottom of figure 1. 1. Building block 1: We assume that high-quality digital data that can trace the entire journey through pregnancy is accessible to CHVs 2. Building block 2: We also assume that integrated work improvement teams (WITs) will have the right people around the table with clearly defined roles and responsibilities will use the data. 3. Building block 3: Community ANC contacts will be implemented.

Treatment:

Other: The combined "C-it DU-it" intervention: community data use for ANC