Conducting a surveillance data quality audit in Grand Bassa County, Liberia, November 2015
Joseph Asamoah Frimpong, Maame Pokuah Amo-Addae, Peter Adebayo Adewuyi, Casey Daniel Hall, Meeyoung Mattie Park, Thomas Knue Nagbe
Corresponding author: Joseph Asamoah Frimpong, Liberia Field Epidemiology Training Program, Monrovia, Liberia 
Received: 19 Apr 2017 - Accepted: 05 May 2017 - Published: 28 May 2017
Domain: Epidemiology,Health communication,Epidemiology
Keywords: Public Health, epidemiology, surveillance, data quality audit, data
This article is published as part of the supplement African Case Studies in Public Heath, commissioned by Emory University, African Field Epidemiology Network (AFENET).
©Joseph Asamoah Frimpong et al. Pan African Medical Journal (ISSN: 1937-8688). 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: Joseph Asamoah Frimpong et al. Conducting a surveillance data quality audit in Grand Bassa County, Liberia, November 2015. Pan African Medical Journal. 2017;27(1):10. [doi: 10.11604/pamj.supp.2017.27.1.12561]
Available online at: https://www.panafrican-med-journal.com//content/series/27/1/10/full
Supplement 
Conducting a surveillance data quality audit in Grand Bassa County, Liberia, November 2015
Conducting a surveillance data quality audit in Grand Bassa County, Liberia, November 2015
Joseph Asamoah Frimpong1,&, Maame Pokuah Amo-Addae1, Peter Adebayo Adewuyi1, Casey Daniel Hall2, Meeyoung Mattie Park2, Thomas Knue Nagbe3
1Liberia Field Epidemiology Training Program, Monrovia, Liberia, 2Rollins School of Public Health, Emory University, Atlanta, USA, 3Ministry of Health, Monrovia, Liberia
&Corresponding author
Joseph Asamoah Frimpong, Liberia Field Epidemiology Training Program, Monrovia, Liberia
Public health officials depend on timely, complete, and accurate surveillance data for decision making. The quality of data generated from surveillance is highly dependent on external and internal factors which may either impede or enhance surveillance activities. One way of identifying challenges affecting the quality of data generated is to conduct a data quality audit. This case study, based on an audit conducted by residents of the Liberia Frontline Field Epidemiology Training Program, was designed to be a classroom simulation of a data quality audit in a health facility. It is suited to enforce theoretical lectures in surveillance data quality and auditing. The target group is public health trainees, who should be able to complete this exercise in approximately 2 hours and 30 minutes.
General instructions: a class of up to 20 trainees is ideal for a training sessions using this case study. The instructor facilitating the session should direct a participant to read a paragraph out loud, going around the room to give each participant a chance to read. Based on the type of question, the instructor may decide to divide the class into small groups for exercises, randomly identify a trainee to respond to the question, or engage the class in a group discussion of the answer. The aim of the interaction is to allow participants to learn from each other and not just from the instructor. Specific instructor’s notes are included with each question in the instructor’s version of this case study.
Audience: residents in Frontline Field Epidemiology Training Programs (FETP-Frontline), Field Epidemiology and Laboratory Training Programs (FELTPs), and others who are interested in this topic.
Prerequisites: for this case study, trainees should have received lectures on data quality, data quality auditing, and SWOT analysis.
Materials needed: flipchart or white board with markers
Level of training and associated public health activity: Novice – Data Quality Auditing
Time required: approximately 2-3 hours
Language: English
- Download the case study student guide (PDF - 1.50 MB)
- Request the case study facilitator guide
The authors declare no competing interest.
We wish to thank African Field Epidemiology Network and Emory University for supporting African-based case study development. We acknowledge residents of the Liberia Field Epidemiology Training Program and Ministry of Health, Liberia for allowing us to use their data for this case study.
- WHO. Ebola Situation Report. Geneva, Switzerland. 2016.
- Ministry of Health (Liberia). Investment Plan for Building a Resilient Health System: 2015-2021. May 2015; 1-60. Google Scholar
- Liberia Field Epidemiology Training Program. Data Quality Audit in District 3C of Grand Bassa County. 2016. Google Scholar
- Bennett S, Myatt M, Jolley D, Radalowicz A. Data Management for Surveys and Trials: A Practical Primer using EpiData. The EpiData Association. 2001.
- Ministry of Health (Republic of Zambia). Data Quality Audit (DQA) Guidelines. 2014; 1-5
- USAID. Data Quality Audit Report: Guidelines for Implementation. 2008: 1-10.
- WHO. Manual on use of routine data quality assessment (RDQA) tool for TB monitoring. Geneva, WHO Press. 2011.
- Harrison JP. Strategic Planning and SWOT Analysis. In Essentials of Strategic Planning in Healthcare, 2010. Washington, DC. Health Administration Press. 2010; 91-97. Google Scholar
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