Evaluating community digital data linkage with or without community data use to increase antenatal clinic uptake in Western Kenya: protocol for a pragmatic open-label, cluster randomised controlled superiority trial

Gerald Ong'ayo^1*Hellen Barsosio¹Lilian Otiso²Alice Kamau¹James Dodd³Linet Okoth²Mandela Oguche²Vicki Doyle⁴Eleanor Ochodo⁵Gordon Okomo⁶Feiko Ter Kuile³Miriam Taegtmeyer³

• ¹Centre for Global Health Research, Kenya Medical Research Institute (KEMRI), Kisumu, Kenya
• ²LVCT Health, Nairobi, Kenya
• ³Liverpool School of Tropical Medicine, Liverpool, United Kingdom
• ⁴Capacity Development International, Liverpool, United Kingdom
• ⁵Stellenbosch University, Stellenbosch, South Africa
• ⁶Homabay County, Homabay, Kenya

Background: Less than 10% of pregnant women in Sub Saharan Africa achieve the World Health Organization recommended eight antenatal care (ANC) contacts for optimal pregnancy management. Robust strategies that involve community outreach programs, integrated service delivery and continuity of care could help improve ANC uptake and quality. Kenya, as in other countries, has promoted use of digital health records at the community and facility level to improve quality and access to data and promote continuity of care. These records however are not always linked and access to data does not guarantee its use to drive quality improvement. C-it-DU-it is a 2-arm pragmatic cluster-randomised trial set in Homabay County, Kenya. The trial will implement digital linkage of community and facility electronic patient data (control arm) and assess the impact of having quality improvement teams reviewing and acting on the linked data (intervention arm). While several areas are captured in the community health records, we will focus on uptake of ANC services as a lens. Methods: Eighteen healthcare facilities (clusters) will be randomly allocated to either the control or intervention arms at a ratio of 1:1. A data linkage module will be deployed in all clusters, enabling digital referral of pregnant women between the community and health facilities. In each intervention cluster, work improvement teams will be established and trained on reviewing these electronic ANC data, identifying problems, developing and deploying context-specific solutions to these problems, and evaluating the impact of their interventions. ANC data will be extracted for 1440 recruited pregnant women. The primary outcome will be the proportion of pregnant women with at least eight ANC contacts. Secondary outcomes will be ANC uptake before 16 weeks gestation, adverse pregnancy outcomes, uptake of required investigations, medication and skilled birth attendance. Discussion: This trial intends to generate evidence on the benefit of community work improvement teams to review and act on linked digital data to develop and deploy solutions to local problems. This strategy, if successful, will promote antenatal service uptake and quality resulting in improved pregnancy outcomes and progress towards sustainable development goals if appropriately scaled up.