Conference Abstract | Volume 9, Abstract 077 (ConfProc7) | Published: 13 Aug 2026
Prince Antwi Bosiako1,&, Albert Mensah2, Rafiq Haruna3, Emmanuel Adongo4, Emmanuel Frimpong5, Richard Kutame6 Ebenezer Kofi Mensah7
1Paga Port Health Laboratory, Paga, Ghana, 2Paga District Hospital, Paga, Ghana, 3Kassena Nankana West District Health Directorate, Kassena Nankana, Ghana, 4Upper East Regional Health Directorate, Bolgatanga, Ghana, 5Upper East Regional Hospital, Bolgatanga, Ghana, 6National Public Health and Reference Laboratory, Ghana Health Service, Accra, Ghana, 7Sekondi Zonal Public Health Laboratory, Sekondi, Ghana
&Corresponding author: Prince Antwi Bosiako, Paga Port Health Laboratory, Paga, Ghana, Email: princeantwi1988@gmail.com
Received: 29 Aug 2025, Accepted: 28 Oct 2025, Published: 13 Aug 2026
Domain: Infectious Disease Epidemiology
Keywords: Tuberculosis, Sputum, Paga, Root Cause Analysis
©Prince Antwi Bosiako 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: Prince Antwi Bosiako et al. Contributing factors to inadequate sputum samples at Paga Port Health Laboratory: A root cause analysis approach, 2025. Journal of Interventional Epidemiology and Public Health. 2026;9(ConfProc7):077. https://doi.org/10.37432/JIEPH-CONFPRO7-0077
Tuberculosis (TB) diagnosis relies heavily on the adequacy of sputum samples. Inadequate sputum samples compromise laboratory accuracy, delay treatment and worsen patient outcomes. Over a 6 months period, Paga Port Health Laboratory rejected approximately 40% of sputum samples due to contamination and 30% of sputum samples due to incorrect labelling. We investigated to determine contributing factors to inadequate sputum samples received and developed targeted interventions.
A cross-sectional study using Root Cause Analysis (RCA) was conducted across nine health facilities. Data were collected through brainstorming sessions, questionnaires and training assessments with healthcare workers. Contributing factors were categorized using a fishbone diagram (staff, processes, logistics, environment) and prioritized through a Weighted Scoring Prioritization Matrix (Impact–Effort Matrix). A training intervention was implemented for 30 healthcare workers, with pre- and post-test scores analysed to assess knowledge gain. Data was analysed using Excel and results presented in tables and charts.
Twenty-two contributing factors with an assigned degree of control were identified: 18.2% were fully within control, 22.7% were partially within control, and 59.1% were outside our control. The impact effort matrix reveals inadequate staff training as the most significant underlying factor, followed by incorrect storage temperature, inadequate collection procedures, and poor labelling. Training intervention significantly improved participant knowledge, with post-test mean score showing highly significant gains 17.5±1.67, 16.87,18.13, p < 0.001.
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