Title of article :
National Minimum Data Set for Antimicrobial Resistance Management: Toward Global Surveillance System
Author/Authors :
Safdari, Reza Department of Health Information Technology - School of Allied Medical Sciences, Tehran University of Medical Sciences , Ghazi Saeedi, Marjan Department of Health Information Technology - School of Allied Medical Sciences, Tehran University of Medical Sciences , Mohammadzade, Niloofar Department of Health Information Technology - School of Allied Medical Sciences, Tehran University of Medical Sciences , Masoumi-Asl, Hossein Center for Communicable Diseases Control - Ministry of Health and Medical Education, Tehran , Rezaei-Hachesu, Peyman Department of Health Information Technology - School of Management and Medical Informatics, Tabriz University of Medical Sciences , Samad-Soltani, Taha Department of Health Information Technology - School of Management and Medical Informatics, Tabriz University of Medical Sciences , Mirnia, Kayvan Department of Neonatology - School of Medicine, Tabriz University of Medical Sciences,
Abstract :
Background: Success of infection treatment depends on the
availability of accurate, reliable, and comprehensive data,
information, and knowledge at the point of therapeutic decisionmaking.
The identification of a national minimum data set will
support the development and implementation of an effective
surveillance system. The goal of this study was to develop a
national antimicrobial resistance surveillance minimum data set.
Methods: In this cross-sectional and descriptive study,
data were collected from selected pioneering countries and
organizations which have national or international antimicrobial
resistance surveillance systems. A minimum data set checklist
was extracted and validated. The ultimate data elements of the
minimum data set were determined by applying the Delphi
technique.
Results: Through the Delphi technique, we obtained 80 data
elements in 8 axes. The resistance data categories comprised
basic, clinical, electronic reporting, infection control,
microbiology, pharmacy, World Health Organization-derived,
and expert-recommended data. Relevance coding was extracted
based on the Iranian electronic health record coding system.
Conclusion: This study provides a set of data elements and a
schematic framework for the implementation of an antimicrobial
resistance surveillance system. A uniform minimum data set
was created based on key informants’ opinions to cover essential
needs in the early implementation of a global antimicrobial
resistance surveillance system in Iran.
Keywords :
Drug resistance , Microbial , Dataset , Biosurveillance , Global health , Iran
Journal title :
Astroparticle Physics