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

Berry, M., Fagliano, J., Tsai, S., McGreevy, K., Walsh, A., & Hamby, T. (2013). Evaluation of Heat-related Illness Surveillance Based on Chief Complaint Data from New Jersey Hospital Emergency Rooms. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4438

Abstract

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.
https://doi.org/10.5210/ojphi.v5i1.4438
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