Implementation and evaluation of a community health workers-led digital integrated diseases screening system to provide healthcare for patients at community level in Rwanda.
prospective_cohort · Level II
Where this comes from
- Record sourced from PubMed, PMID 41687454.
- Also identified by DOI 10.1016/j.ebiom.2026.106168 and PMC identifier 12917523.
- Licence recorded as CC BY-NC-ND.
- Because redistribution is not established, this page shows the abstract only. Follow the links below for the full text.
Abstract
Community health workers (CHWs) play a vital role in identifying patients within the community. To enhance their decision-making and reduce unnecessary referrals, Rwanda introduced a digital integrated disease screening tool (d-IDS), embedded within the national community Electronic Medical Records (cEMR) system. This study aimed to design, integrate, and evaluate the d-IDS to support its broader national scale-up. This study employed a pre-post effectiveness-implementation hybrid design to implement the d-IDS and evaluate its effectiveness in improving patient management at the community level in five districts during April-July 2024. The d-IDS was designed into a single decision-support workflow embedded within the cEMR platform, and deployed on CHWs' smartphones. The workflow automatically guides CHWs through case registration, symptom assessment, diagnostic testing, and treatment or referral decisions. The d-IDS tool consolidated the screening processes for tuberculosis, malaria, pneumonia, and diarrhoeal diseases. Referral data extracted from the cEMR following d-IDS implementation and retrospective data from similar period (April-July 2023) collected under the paper-based approach; Standard of Care (SOC), were analysed using Chi-square tests. Qualitative feedback from CHWs were gathered through structured interviews to assess acceptability and feasibility. The implementation of d-IDS led to a statistically significant 24.2% reduction in overall referrals to health facilities (p < 0.0001) when compared to the SOC period. Of the 3060 individuals screened using the d-IDS, 45.6% triggered further assessment, and 1687 (55.1%) were successfully managed by CHWs at the community level. Notably, in Rwamagana district, referral rates dropped from 79.8% to 32.5%, a 59.2% reduction (p < 0.0001). CHWs reported that d-IDS improved workflow efficiency, data accuracy, and decision-making compared to the paper-based approach, especially with features like offline functionality and symptom-guided screening protocols. The findings confirm that d-IDS is both feasible and acceptable for CHW use in community settings. It improves community-based patient management and reduces the burden on health facilities. However, close follow-up mechanisms are necessary to ensure early detection of any worsening conditions. These promising results support the future national rollout of d-IDS as a scalable solution to strengthen primary healthcare and CHW-led service delivery. The study received financial support from the United Kingdom (FCDO 40105983), Canada (DFATD 7429348) and Germany (BMZ ACT Accelerator support 25.04.2022).
Medical subject headings
- Community Health Workers
- Mass Screening