The Impact of Documentation Style on Influenza-Like Illness Rates in the Emergency Department | Zendy

Dino P. Rumoro | Zendy; Shital Shah | Zendy; Gillian Gibbs | Zendy; Marilyn M. Hallock | Zendy; Gordon M. Trenholme | Zendy; Michael Waddell | Zendy; Joseph P. Bernstein | Zendy

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The Impact of Documentation Style on Influenza-Like Illness Rates in the Emergency Department

Author(s) -

Dino P. Rumoro,

Shital Shah,

Gillian Gibbs,

Marilyn M. Hallock,

Gordon M. Trenholme,

Michael Waddell,

Joseph P. Bernstein

Publication year - 2016

Publication title -

online journal of public health informatics

Language(s) - English

Resource type - Journals

ISSN - 1947-2579

DOI - 10.5210/ojphi.v8i1.6449

Subject(s) - emergency department , standardization , documentation , false positive paradox , medicine , influenza like illness , medical emergency , complaint , data science , computer science , artificial intelligence , nursing , virology , virus , political science , law , programming language , operating system

Emergency department (ED) data are key components for syndromic surveillance systems. However, the lack of standardization for the content in chief complaint (CC) free-text fields may make it challenging to use these elements in syndromic surveillance systems. Furthermore, little is known regarding how ED data sources should be structured or combined to increase sensitivity without elevating false positives. In this study, we constructed two different models of ED data sources and evaluated the resulting ILI rates obtained in two different institutions.

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