Conference Abstract | Volume 9 (ConfPro8): Abstract 66 | Published: 09 Oct 2026
Priscilla Mensah1, &, Rita Asante2
1Food and Drugs Authority, Kumasi, Ghana; 2Ghana Field Epidemiology Training Programme, School of Public Health, Legon- Accra, Ghana
&Corresponding author: Priscilla Mensah, Food and Drugs Authority, Kumasi, Ghana, Email: priscilla.ymensah@fda.gov.gh
Received: 11 Mar 2026, Accepted: 30 Aug 2026, Published: 09 Oct 2026
Domain: Infectious Disease Epidemiology
Keywords: Surveillance, data quality, root cause analysis, supportive supervision
©Priscilla Mensah 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: Priscilla Mensah et al., Incomplete data fields in surveillance reports at the Enforcement and Safety Monitoring Units, Food and Drugs Authority Regional Office, Kumasi, Ashanti, Ghana, April, 2026. Journal of Interventional Epidemiology and Public Health. 2026;9(ConfPro8):66. https://doi.org/10.37432/JIEPH-CONFPRO8-0066
Incomplete data fields in surveillance reports compromise data quality, limit regulatory decision-making, and weaken public health response. This study aimed to identify the root causes of incomplete data fields in Enforcement and Safety Monitoring reports at the Food and Drugs Authority (FDA), Kumasi, and determine the most critical cause within organizational control.
A qualitative problem analysis was conducted using staff brainstorming sessions. Root causes were explored using a fishbone (Ishikawa) diagram and the 5-Whys technique. Identified causes were categorized into five domains: human factors, management, methods, tools, and external factors. Causes were further classified according to the level of organizational control as total (T), partial (P), or not within control (N).
Twenty-three root causes of incomplete data fields were identified: seven (7) related to management, six (6) human factors, four (4) external factors, and three each to tools and methods. Key contributing factors included poor supervision, inadequate subject-matter knowledge, fatigue, operational pressure, low motivation, lack of staff training, and limited confidence in delegated responsibilities. Most, 74.0% (17/23) identified causes were fully within organizational control (T), while 21.7% (5/23) were partially controllable and 4.3% (1/23) were outside organizational control. Poor supervision emerged as the critical root cause due to its influence on multiple contributing factors.
Strengthening supportive supervision is essential to improving surveillance data completeness and overall data quality. FDA management should enhance delegation practices, strengthen staff capacity through regular training, and implement routine supervisory mechanisms to support effective regulatory action and public health decision-making.
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