Conference Abstract | Volume 8, Abstract NACNDC/19JASH021 (Oral) | Published: 20 Nov 2025
Diana Cherotin1,&, Clark Joshua Brianwong1, Richard Jjuuko1, Eddy Okwir1, Frehd Nghania1, Ssekiswa Lwanga Zimwanguyiza1, Alexander Mugume1, Dithan Kiragga1
1Baylor Foundation Uganda
&Corresponding author: Diana Cherotin, Baylor Foundation Uganda. Email: dianacherotin@baylor-uganda.org, ORCID: 0009-0004-3095-8794
Received: 12 Sept 2025, Accepted: 20 Oct 2025, Published: 20 Nov 2025
Domain: Infectious Disease Epidemiology
Keywords: Tuberculosis, digital health, quality improvement, surveillance system, Uganda
©Nebyeye Gift et al. Journal of Interventional Epidemiology and Public Health (ISSN: 2664-2824). This is an Open Access article distributed under the terms of the Creative Commons Attribution International 4.0 License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Cite this article: Nebyeye Gift et al., Digitization of tuberculosis data through a quality improvement approach: Implementation of the electronic case-based TB surveillance system in Uganda. Journal of Interventional Epidemiology and Public Health. 2025;8(ConfProc6):00021. https://doi.org/10.37432/JIEPH-CONFPRO6-00021
In 2020, Uganda’s Ministry of Health introduced the Electronic Case-Based Surveillance System (eCBSS) to strengthen the documentation, tracking, and management of tuberculosis (TB) cases. By December 2023, the system had been rolled out to 155 health facilities in Eastern Uganda; however, only 23% of facilities submitted real-time TB case reports, causing delays in follow-up and treatment initiation. To address this challenge, a Quality Improvement (QI) project was implemented under the USAID LPHS-E project led by Baylor Uganda, aiming to increase real-time reporting to at least 90% by July 2024.
A root-cause analysis conducted in January 2024 identified four major barriers to timely data entry: unclear staff roles, inconsistent internet connectivity, weak data verification processes, and large backlogs of unentered cases. A multidisciplinary QI team—comprising mentors, data officers, and facility staff—implemented four Plan-Do-Study-Act (PDSA) cycles. Interventions included clarifying staff responsibilities, introducing daily data-entry targets, providing 7.5GB monthly internet bundles per facility, offering mentorship and weekly reminders, strengthening peer support networks, and deploying additional data-entry support to high-volume facilities. Facilities used tablets or computers supplied by the Ministry of Health and implementing partners. Weekly performance reviews and run charts were used to track progress.
Real-time reporting increased from 23% at baseline to 96% by the end of the fourth PDSA cycle. Improvements were observed progressively after each cycle: 54% after PDSA 1, 62% after PDSA 2, 76% after PDSA 3, and 96% after PDSA 4, with 1,124 of 1,171 TB cases reported on time. Key enablers included mentorship, clear accountability structures, and strengthened internet access. Technical system challenges contributed to intermittent delays but were mitigated through continuous support. Faster reporting also improved patient follow-up and notification.
The QI approach demonstrated that real-time TB case reporting can be rapidly improved when frontline teams receive structured support. Sustainability has been reinforced through integration into routine supervision, district mentorship, and government-supported internet access. This model is suitable for resource-limited settings to accelerate digital health adoption and strengthen timely TB care.
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