Developing syndrome definitions based on consensus and current use
- Wendy W Chapman1,
- John N Dowling1,
- Atar Baer2,
- David L Buckeridge3,
- Dennis Cochrane4,
- Michael A Conway1,
- Peter Elkin5,
- Jeremy Espino6,
- Julia E Gunn7,
- Craig M Hales8,
- Lori Hutwagner8,
- Mikaela Keller9,
- Catherine Larson10,
- Rebecca Noe11,
- Anya Okhmatovskaia12,
- Karen Olson13,14,
- Marc Paladini15,
- Matthew Scholer16,
- Carol Sniegoski17,
- David Thompson18,
- Bill Lober19
- 1Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- 2Public Health – Seattle and King County, Seattle, USA
- 3McGill Clinical and Health Informatics, McGill University, Québec, Canada
- 4Emergency Medical Associates Research Foundation, Livingston, New Jersey, USA
- 5Mount Sinai School of Medicine, New York, New York, USA
- 6RODS Laboratory, Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- 7Infectious Disease Bureau, Boston Public Health Commission, Boston, Massachusetts, USA
- 8Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- 9Children's Hospital Boston, Boston, Massachusetts, USA
- 10Management Information Systems Department, University of Arizona, Phoenix, Arizona, USA
- 11National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
- 12Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Québec, Canada
- 13Division of Emergency Medicine, Children's Hospital Boston, Boston, Massachusetts, USA
- 14Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
- 15New York City Department of Health and Mental Hygiene, New York, New York, USA
- 16Department of Emergency Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
- 17The Johns Hopkins University Applied Physics Laboratory, Baltimore, Maryland, USA
- 18Department of Emergency Medicine, Northwestern University, Chicago, Illinois, USA
- 19Schools of Medicine, Nursing, and Public Health, University of Washington, Seattle, Washington, USA
- Correspondence to Wendy W Chapman, Department of Biomedical Informatics, University of California, San Diego Division of Biomedical Informatics 9500 Gilman Drive, Bldg 2 #0728 La Jolla, CA 92093-0728, USA; wendy.w.chapman{at}gmail.com
- Received 5 January 2010
- Accepted 25 June 2010
Abstract
Objective Standardized surveillance syndromes do not exist but would facilitate sharing data among surveillance systems and comparing the accuracy of existing systems. The objective of this study was to create reference syndrome definitions from a consensus of investigators who currently have or are building syndromic surveillance systems.
Design Clinical condition–syndrome pairs were catalogued for 10 surveillance systems across the United States and the representatives of these systems were brought together for a workshop to discuss consensus syndrome definitions.
Results Consensus syndrome definitions were generated for the four syndromes monitored by the majority of the 10 participating surveillance systems: Respiratory, gastrointestinal, constitutional, and influenza-like illness (ILI). An important element in coming to consensus quickly was the development of a sensitive and specific definition for respiratory and gastrointestinal syndromes. After the workshop, the definitions were refined and supplemented with keywords and regular expressions, the keywords were mapped to standard vocabularies, and a web ontology language (OWL) ontology was created.
Limitations The consensus definitions have not yet been validated through implementation.
Conclusion The consensus definitions provide an explicit description of the current state-of-the-art syndromes used in automated surveillance, which can subsequently be systematically evaluated against real data to improve the definitions. The method for creating consensus definitions could be applied to other domains that have diverse existing definitions.
Footnotes
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Funding Funding for WWC was provided by NLM 1 R01LM009427-01 NLP Foundational Studies and Ontologies for Syndromic Surveillance from ED Reports.
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Competing interests None.
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Provenance and peer review Not commissioned; externally peer reviewed.
