E-health supported referral for patients with breast abnormalities at primary healthcare facilities in Ethiopia: protocol for a cluster-randomised controlled trial.
[BACKGROUND] A weak referral system combined with limited diagnostic facilities is among the key systemic barriers to the early detection of breast cancer.
APA
Getachew E, Gizaw M, et al. (2026). E-health supported referral for patients with breast abnormalities at primary healthcare facilities in Ethiopia: protocol for a cluster-randomised controlled trial.. Trials, 27(1), 86. https://doi.org/10.1186/s13063-025-09409-1
MLA
Getachew E, et al.. "E-health supported referral for patients with breast abnormalities at primary healthcare facilities in Ethiopia: protocol for a cluster-randomised controlled trial.." Trials, vol. 27, no. 1, 2026, pp. 86.
PMID
41519765
Abstract
[BACKGROUND] A weak referral system combined with limited diagnostic facilities is among the key systemic barriers to the early detection of breast cancer. Strengthening patient pathways is essential to improve follow-up and reduce delays in cancer diagnosis and care. This study aims to assess the effectiveness of the DINKNESH referral and follow-up app, a digital, app-based patient referral system linking early detection of breast-related abnormalities at primary healthcare settings with diagnostic facilities in Ethiopia.
[METHODS] A two-arm cluster randomised trial with an embedded qualitative study is being conducted at eight primary health facilities and affiliated satellite hospitals in Ethiopia. The study includes women aged ≥18 years presenting with breast abnormalities, as well as women aged ≥30 years with positive findings on clinical breast examination. In intervention cluster facilities, the referral process for further diagnosis is supported by the DINKNESH referral and follow-up app, which facilitates patient registration, data transfer, and reminder services. This is compared with the routine paper-based referral process in the control clusters. The primary outcome is the proportion of completed referrals. All outcome measures will be analysed using IBM SPSS Statistics 25.0. A mixed-effects logistic regression model will be applied, adjusting for potential confounders and accounting for clustering at the facility level. At the end of the intervention period, qualitative interviews will be conducted using the RE-AIM framework to explore the acceptability, challenges, sustainability, and scalability of the intervention.
[DISCUSSION] This study will provide robust evidence on whether app-based referral systems for women with breast symptoms can improve follow-up and facilitate early breast cancer detection in low-resource settings such as Ethiopia. The findings will support the WHO Global Breast Cancer Initiative's goal of diagnosing more than 60% of breast cancer cases at an early stage.
[TRIAL REGISTRATION] PACTR202411893209747. Registered on 25 November 2024, https://pactr.samrc.ac.za/.
[METHODS] A two-arm cluster randomised trial with an embedded qualitative study is being conducted at eight primary health facilities and affiliated satellite hospitals in Ethiopia. The study includes women aged ≥18 years presenting with breast abnormalities, as well as women aged ≥30 years with positive findings on clinical breast examination. In intervention cluster facilities, the referral process for further diagnosis is supported by the DINKNESH referral and follow-up app, which facilitates patient registration, data transfer, and reminder services. This is compared with the routine paper-based referral process in the control clusters. The primary outcome is the proportion of completed referrals. All outcome measures will be analysed using IBM SPSS Statistics 25.0. A mixed-effects logistic regression model will be applied, adjusting for potential confounders and accounting for clustering at the facility level. At the end of the intervention period, qualitative interviews will be conducted using the RE-AIM framework to explore the acceptability, challenges, sustainability, and scalability of the intervention.
[DISCUSSION] This study will provide robust evidence on whether app-based referral systems for women with breast symptoms can improve follow-up and facilitate early breast cancer detection in low-resource settings such as Ethiopia. The findings will support the WHO Global Breast Cancer Initiative's goal of diagnosing more than 60% of breast cancer cases at an early stage.
[TRIAL REGISTRATION] PACTR202411893209747. Registered on 25 November 2024, https://pactr.samrc.ac.za/.
MeSH Terms
Humans; Ethiopia; Female; Primary Health Care; Referral and Consultation; Breast Neoplasms; Telemedicine; Randomized Controlled Trials as Topic; Early Detection of Cancer; Multicenter Studies as Topic; Adult; Mobile Applications