Digital Data Linkage and Scheduling to Track Pregnancy With or Without Community Data Use to Increase Antenatal Clinic Uptake in Western Kenya.

Study Overview
=================
Brief Summary
-----------------
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).

Detailed 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.

Official Title
-----------------
A Pragmatic Open-label, Community-based, Cluster Randomised Controlled Superiority Trial to Evaluate the Efficacy and Cost-effectiveness of Digital Data Linkage and Scheduling ('C-it') With or Without Community Data Use ('DU-it') to Increase Antenatal Clinic Uptake in Western Kenya.

Conditions
-----------------
Health Systems, Electronic Community Health Information Systems, Antenatal Clinic Uptake, Pregnancy

Intervention / Treatment
-----------------
* Other: The combined C-it DU-it intervention: community data use for ANC


Participation Criteria
=================
Eligibility Criteria
-----------------
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.
Sexes Eligible for Study
-----------------
Female

Accepts Healthy Volunteers
-----------------
Accepts Healthy Volunteers

Study Plan
=================
How is the study designed?
-----------------

Design Details

Primary Purpose: Health Services Research
Allocation: Randomized
Intervention Model: Parallel Assignment
Interventional Model Description: Allocation: cluster randomised; intervention model: parallel assignment; arms: 2; allocation ratio: 1:1; restricted or stratified randomisation. Masking: none
Masking: None (Open Label)


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| No Intervention: Digital data linkage and scheduling ('C-it'): The C-it enhanced standard of care<br>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. | |
| Experimental: The combined C-it DU-it intervention: community data use for ANC<br>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. Building block 1: We assume that high-quality digital data that can trace the entire journey through pregnancy is accessible to CHVs 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. Building block 3: Community ANC contacts will be implemented. | Other: The combined C-it DU-it intervention: community data use for ANC<br>* Combining data linkage (C-it) with work improvement teams for community data use (DU-it) to improve antenatal clinic uptake. 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)<br>* Other names: community data use (DU-it);|

What is the study measuring?
-----------------
Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Increasing antenatal clinic uptake | The proportion of women having at least eight ANC contacts during the antenatal period, defined as either a scheduled ANC visit in the facility or a scheduled ANC contact with a CHV in the community assessed at birth (or within the first 6-8 weeks for home births) using the ANC cards. | 14 months | 
| Estimate socioeconomic impact and access to social protection | Defined as the proportion of women using financial coping strategies and their frequency and distribution | 14 months | 
| Estimate the costs to pregnant women and their households | Absolute costs to the pregnant woman and their household and the costs as a proportion of the pregnant woman and their household's monthly income or expenditure/consumption will be calculated for the following variables: Out-of-pocket medical costs Out-of-pocket non-medical costs Lost income, time, and productivity | 14 months | 

Secondary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| The proportion of women having at least four scheduled ANC visits in the facility | assessed at birth (or within the first 6-8 weeks after birth for home births) using the ANC cards. | 14 months | 
| The proportion of women having at least eight scheduled ANC visits in the facility | assessed at birth (or within the first 6-8 weeks after birth for home births) using the ANC cards. | 14 months | 
| The frequency (count) of scheduled ANC visits | assessed at birth (or within the first 6-8 weeks after birth for home births) using the ANC cards. | 14 months | 
| The frequency (count) of of ANC visits in the community | assessed at birth (or within the first 6-8 weeks after birth for home births) using the ANC cards. | 14 months | 
| Early antenatal clinic attendance | The proportion of women with a first ANC contact before 16 weeks gestation. | 14 months | 
| Quality of antenatal care | The proportion of women with at least three courses of IPTp The proportion of women who received iron and folate for 90 days. The proportion of women receiving testing and management for HIV. The proportion of women receiving testing and management for malaria. The proportion of women receiving testing and management for syphilis. The proportion of women receiving testing and management for anaemia. | 14 months | 
| Uptake of skilled birth attendance. | The proportion of women who had a skilled birth attendance. | 14 months | 
| Reducing the risk of adverse pregnancy outcomes. | The proportion of women with adverse pregnancy outcomes- defined as a composite of foetal loss (stillbirth or spontaneous miscarriage), low birth weight or neonatal mortality) | 14 months | 
| prevalence of catastrophic health expenditure (CHE) of accessing ANC care with C-it enhanced standard of care | CHE prevalence at two World Health Organization-defined thresholds: out-of-pocket medical costs of more than 10% of a patient household's total monthly expenditure/consumption (10%-threshold); and out-of-pocket medical costs of more than 40% of a patient household's monthly capacity to pay (non-food/housing/utilities expenditure/consumption) • A sensitivity analysis of the proportion of women's households incurring CHE due to pregnancy and ANC visits using varying additional recognised calculations and thresholds including, as per WHO Tuberculosis Patient Cost Survey methodology, the addition of non-medical out-of-pocket costs and lost income in the numerator | 14 months | 
| Cost-effectiveness of C-it and C-it DU-it intervention | Incremental cost-effectiveness ratios (ICERs) compared across trial arms | 14 months | 
| Assess equity of access to ANC and C-it and C-it DU-it intervention. | Equity of access to ANC and the interventions will be evaluated by exploratory distributional (or extended) cost-effectiveness analysis of the intervention across the following sub-groups: poverty quintiles, age groups including adolescents vs adults, study sites, HIV status, and by eligibility for health insurance including NHIF and Linda Mama. | 14 months |