A qualitative study to inform the development of a decision support tool for the diagnosis of pulmonary tuberculosis in Tigray, Ethiopia.

Background: Tuberculosis (TB) is Ethiopia's leading infectious killer disease. The war in the Tigray region of Ethiopia has resulted in the disruption of TB care services. Prediction models are recommended to aid the diagnosis of TB in resource-limited settings. However, the development of such decision-support tools without the participation of end users may not be successful. To inform the tool development, we described barriers to diagnosing TB and identified applicable and desirable parameters for the proposed tool.

Methods: We conducted a qualitative study between February and June 2023 in two cities in Tigray, Northern Ethiopia. We conducted 12 in-depth interviews and four focus group discussions with healthcare workers (HCWs). Interviews were translated, coded, and analyzed to identify predefined and emergent themes during the thematic analysis.

Results: Healthcare workers used symptoms, risk factors, signs, and investigations to diagnose TB. However, failure to ask about antibiotic use, the absence and non-affordability of investigations, and patient load were barriers affecting the diagnosis of TB. Most of the classic TB symptoms and their duration were sorted as very important, simple, reliable, generalizable, and desirable indices. In addition, a trial of antibiotics, being chronically sick-looking, having HIV, having a contact history with a TB patient, and an erythrocyte sedimentation rate fulfilled the above criteria.

Conclusions: In the TB diagnostic process, HCWs account for a variety of data, but they prefer the classic symptoms of TB to heighten their clinical suspicion. Antibiotic trials and some risk factors were also considered reasonable. However, when HCWs have a heavy workload and a shortage of investigations, they experience a suboptimal TB diagnostic process. Hence, appropriate context consideration and care providers' preferences for parameters will inform tool development.