Detecting Unanticipated Increases in Emergency Department Chief Complaint Keywords

Authors

  • Ramona Lall New York City Department of Health and Mental Hygiene, Queens, NY, United States
  • Alison Levin-Rector New York City Department of Health and Mental Hygiene, Queens, NY, United States
  • Robert Mathes New York City Department of Health and Mental Hygiene, Queens, NY, United States
  • Don Weiss New York City Department of Health and Mental Hygiene, Queens, NY, United States

DOI:

https://doi.org/10.5210/ojphi.v6i1.5069

Abstract

The chief complaint (CC) text field is a rich source of information, but its current use for syndromic surveillance is limited to a fixed set of syndromes defined a priori using keywords. To identify unanticipated sudden increases in word frequency, we developed a simple method that compares the frequency of every word in the CC text field on a given day against the average frequency of the same word during a baseline period. This could prove useful for situational awareness during routine surveillance and emergencies.

Author Biography

Robert Mathes, New York City Department of Health and Mental Hygiene, Queens, NY, United States

Robert Mathes is the Director of the Syndromic Surveillance Unit in the Bureau of Communicable Disease at the New York City Department of Health and Mental Hygiene.

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Published

2014-03-09

How to Cite

Lall, R., Levin-Rector, A., Mathes, R., & Weiss, D. (2014). Detecting Unanticipated Increases in Emergency Department Chief Complaint Keywords. Online Journal of Public Health Informatics, 6(1). https://doi.org/10.5210/ojphi.v6i1.5069

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Section

Lightning Talks