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Detecting, reporting, and analysis of priority diseases for routine public health surveillance in 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 a...

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Detalles Bibliográficos
Autores principales: Frimpong, Joseph Asamoah, Amo-Addae, Maame Pokuah, Adewuyi, Peter Adebayo, Hall, Casey Daniel, Park, Meeyoung Mattie, Nagbe, Thomas Knue
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The African Field Epidemiology Network 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5500932/
https://www.ncbi.nlm.nih.gov/pubmed/28721174
http://dx.doi.org/10.11604/pamj.supp.2017.27.1.12561
Descripción
Sumario: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.