This paper is in the following e-collection/theme issue:

Presentations, Abstracts, or Demonstrations (740) Public Health Surveillance Practice (162) Public Health Data Analytics (72)

Published on in Vol 5, No 1 (2013):

Evaluation of Heat-related Illness Surveillance Based on Chief Complaint Data from New Jersey Hospital Emergency Rooms

Evaluation of Heat-related Illness Surveillance Based on Chief Complaint Data from New Jersey Hospital Emergency Rooms

Evaluation of Heat-related Illness Surveillance Based on Chief Complaint Data from New Jersey Hospital Emergency Rooms

Authors of this article:

Michael Berry1 ;   Jerald Fagliano1 ;   Stella Tsai1 ;   Katharine McGreevy1 ;   Andrew Walsh2 ;   Teresa Hamby1
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    The NJ Department of Health‰Ûªs syndromic surveillance system developed an algorithm to categorize heat-related illness (HRI) based on a patient‰Ûªs chief complaint during an emergency room visit, then matched these data with subsequent Uniform Billing (UB) diagnosis data. The overall sensitivity of the algorithm was 16% and the positive predictive value was 40%. Evaluation of a major heat event found both the sensitivity and positive predictive value increased to about 23% and 60%, respectively. While the HRI algorithm was relatively insensitive, sensitivity improved during major heat events and all excursions in HRI were identified using chief complaint data.