Cross-Disciplinary Consultancy to Bridge Public Health Technical Needs and Analytic Developers: Asyndromic Surveillance Use Case.

Autor:	Faigen Z; North Carolina Department of Health and Human Services., Deyneka L; North Carolina Department of Health and Human Services., Ising A; University of North Carolina at Chapel Hill, Department of Emergency Medicine., Neill D; Carnegie Mellon University, Event and Pattern Detection Laboratory., Conway M; University of Utah, Department of Biomedical Informatics., Fairchild G; Los Alamos National Laboratory, Department of Analytics, Intelligence, and Technology., Gunn J; Boston Public Health Commission, Department of Communicable Disease Control., Swenson D; New Hampshire Department of Health and Human Services, Department of Public Health Services., Painter I; University of Washington School of Public Health, Department of Health Services., Johnson L; International Society for Disease Surveillance., Kiley C; Defense Threat Reduction Agency, Chemical & Biological Defense Program., Streichert L; International Society for Disease Surveillance., Burkom H; Johns Hopkins University Applied Physics Laboratory.
Jazyk:	angličtina
Zdroj:	Online journal of public health informatics [Online J Public Health Inform] 2015 Dec 30; Vol. 7 (3), pp. e228. Date of Electronic Publication: 2015 Dec 30 (Print Publication: 2015).
DOI:	10.5210/ojphi.v7i3.6354
Abstrakt:	Introduction: We document a funded effort to bridge the gap between constrained scientific challenges of public health surveillance and methodologies from academia and industry. Component tasks are the collection of epidemiologists' use case problems, multidisciplinary consultancies to refine them, and dissemination of problem requirements and shareable datasets. We describe an initial use case and consultancy as a concrete example and challenge to developers. Materials and Methods: Supported by the Defense Threat Reduction Agency Biosurveillance Ecosystem project, the International Society for Disease Surveillance formed an advisory group to select tractable use case problems and convene inter-disciplinary consultancies to translate analytic needs into well-defined problems and to promote development of applicable solution methods. The initial consultancy's focus was a problem originated by the North Carolina Department of Health and its NC DETECT surveillance system: Derive a method for detection of patient record clusters worthy of follow-up based on free-text chief complaints and without syndromic classification. Results: Direct communication between public health problem owners and analytic developers was informative to both groups and constructive for the solution development process. The consultancy achieved refinement of the asyndromic detection challenge and of solution requirements. Participants summarized and evaluated solution approaches and discussed dissemination and collaboration strategies. Practice Implications: A solution meeting the specification of the use case described above could improve human monitoring efficiency with expedited warning of events requiring follow-up, including otherwise overlooked events with no syndromic indicators. This approach can remove obstacles to collaboration with efficient, minimal data-sharing and without costly overhead.
Databáze:	MEDLINE
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