TBLIS

TBLIS: Transforming TB Laboratory Data Management in Africa

A novel LIMS that supports the unique needs of TB laboratory information management in resource-limited settings. The system is appropriate for both TB patient care and research laboratories.

In the fight against Tuberculosis (TB), timely and accurate laboratory data is critical for effective patient care and public health response. However, many TB laboratories in Africa struggle with outdated paper-based systems or generic electronic tools that fail to meet their specific needs.

TBLIS—our groundbreaking electronic laboratory information management system tailored specifically for TB laboratories. Currently deployed across 15 laboratories in eight African countries, TBLIS ensures seamless workflow monitoring, real-time inventory tracking, and proactive equipment maintenance, all aligned with the ISO 15189 standard for laboratory quality management.

First implemented by the Uganda TB Supranational Reference Laboratory (SRL) in 2014, TBLIS has revolutionized TB lab operations. The system has significantly improved data accuracy, reduced test reporting delays, and enhanced monitoring of laboratory quality indicators. This transformation directly impacts patient care, ensuring that test results are delivered swiftly, enabling quicker diagnosis and treatment. Moreover, the system played a crucial role in managing laboratory data for the Uganda TB Prevalence Survey 2014/15, demonstrating its reliability in both clinical and research settings. The success of TBLIS has led to its expansion into countries like Somalia, Tanzania, South Sudan, Malawi, Nigeria, and Eritrea, empowering TB laboratories with efficient data management, streamlined reporting, and enhanced compliance with international standards. By addressing the unique challenges faced by TB laboratories, TBLIS is not just a digital tool—it’s a game-changing solution that strengthens healthcare systems, improves patient outcomes, and sets a new benchmark for laboratory information management in resource-limited settings.