Conference Abstract | Volume 9 (ConfPro8): Abstract 20 | Published: 05 Oct 2026
Richmond Ofosu1,2, &, George Akowuah1, Martha Arkaa Frimpong1, Courage Anku1,2, Magdalene Akos Odikro1, Samuel Sackey1
1Ghana Field Epidemiology and Laboratory Training Program (GFELTP), School of Public Health, University of Ghana, 2Ghana Health Service, Municipal Health Directorate, Ejura Sekyedumase
&Corresponding author: Richmond Ofosu, Municipal Health Directorate, Ejura, Ashanti, Email: rich85fosu@gmail.com
Received: 11 Mar 2026, Accepted: 29 Aug 2026, Published: 05 Oct 2026
Domain: Health Systems
Keywords: Surveillance, decision-making, problem analysis, fishbone diagram, DHIMS2, Ghana Health Service
©Richmond Ofosu 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: Richmond Ofosu et al., Inadequate surveillance data use for decision-making in health facilities: A systematic problem analysis of Ejura Sekyedumase Municipality, 2026. Journal of Interventional Epidemiology and Public Health. 2026;9(ConfPro8):20. https://doi.org/10.37432/JIEPH-CONFPRO8-0020
Surveillance data are essential for evidence-based decision-making in public health. Despite routine data collection and reporting in Ejura Sekyedumase Municipality, surveillance data are not adequately reviewed or utilized for appropriate public health action. We analysed underlying causes of inadequate use of surveillance data for decision-making in health facilities within the municipality.
A descriptive problem analysis was conducted in May 2026 in Ejura Sekyedumase Municipality. Brainstorming sessions were held with 19 key surveillance officers at the Municipal Health Directorate conference hall. Contributing factors were categorized using a fishbone (Ishikawa) diagram. The Totally (T), Partially (P), and Not (N) controllable framework assessed the degree of control over each identified cause.
Out of 19 participants, Health Information Officers constituted the highest (26.3%). Eighteen factors were identified under five categories: Staff (poor data analysis skills, limited interpretive capacity, high workload, inadequate training, poor knowledge of data importance, inadequate officers); Administrative (weak supervision, poor data review, inadequate feedback, limited motivation, funding gaps); Data Management (late reporting, poor documentation, poor data presentation); Tools (limited computer access); and Environmental (network challenges affecting DHIMS2). The critical cause was poor knowledge of the importance of surveillance data, a totally controllable factor directly influencing data interpretation and utilization.
Inadequate use of surveillance data for decision-making in Ejura Sekyedumase Municipality is driven by interrelated staff, administrative, data management, tools, and environmental factors, with poor knowledge of surveillance data importance as the critical cause. Targeted training, routine data review meetings, strengthened feedback, and supportive supervision are critical to improving evidence-based decision-making.
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