Implementing computer‐aided detection for TB active case finding
A qualitative study of feasibility and acceptability in Tondo, Manila
Bibliographic Data
Tuberculosis (TB) remains the leading cause of death from a single infectious agent, with over 1.23 million deaths globally in 2024. Despite available treatment and prevention strategies, timely and accurate detection remains challenging, particularly in high-burden settings such as the Philippines, which accounted for 6.8% of the global burden of TB in 2024. Computer-aided detection (CAD) software integrated with digital chest X-ray offers enhanced screening capacity, but its success depends on feasibility and acceptability within local health systems. This qualitative study explored perceptions and experiences of CAD integration during a Médecins Sans Frontières community-based TB active case finding campaign (ACF) in Tondo, Manila. In-depth interviews, focus group discussions, and direct observations were conducted with MSF staff, health center physicians, TB program personnel, ACF participants, and community leaders between January and April 2023. Thematic analysis identified four main themes: (1) Operational functionality and efficiency: Staff reported CAD increased screening capacity, supported clinical decision-making, and streamlined workloads; ACF participants reported a convenient process. (2) Human resources and role adaptation: Staff perceived role redistribution as initially challenging, highlighting the need for adequate capacity building and technical support; (3) Technical feasibility and system design: project managers and staff emphasized understanding CAD’s capabilities and limitations to plan infrastructure, set thresholds, and compensate for inherent limitations. (4) Community acceptability and ethical considerations: community participants expressed mixed views on the reliability of novel “high-tech” tools and stressed the importance of aligning with local healthcare needs. This study demonstrates that implementing CAD in TB ACF is both feasible and acceptable when supported by careful planning and adaptation to local contexts. Sustainable implementation hinges on technical support and the meaningful involvement of healthcare workers and communities, whose insights help ensure ethical and effective digital health innovation. The experience in Tondo offers lessons on deploying CAD in high-burden, resource-constrained settings.
Capacity building · community acceptability · computer-aided detection · digital health implementation · ethical considerations · feasibility and acceptability · Médecins Sans Frontières · resource-limited settings · technical support · tuberculosis screening · COVID-19 diagnosis using AI · Lung Cancer Diagnosis and Treatment · Tuberculosis Research and Epidemiology
| Highly cited | No |
|---|