Paralysis Analysis: Investigating Paralysis Visit Anomalies in New Jersey

Authors

  • Teresa Hamby NJ Department of Health, Trenton, NJ
  • Stella Tsai NJ Department of Health, Trenton, NJ
  • Carol Genese NJ Department of Health, Trenton, NJ
  • Andrew Walsh Health Monitoring Systems, Inc, Pittsburgh, PA
  • Lauren Bradford Health Monitoring Systems, Inc, Pittsburgh, PA
  • Edward Lifshitz NJ Department of Health, Trenton, NJ

DOI:

https://doi.org/10.5210/ojphi.v5i1.4441

Abstract

The NJ Department of Health's syndromic surveillance system developed an algorithm to categorize heat-related illness (HRI) based on a patient's 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.

Author Biography

Teresa Hamby, NJ Department of Health, Trenton, NJ

Teresa Hamby, MSPH, is a data analyst on the surveillance staff of the Communicable Disease Service of the New Jersey Department of Health. She has extensive experience working with New Jersey's emergency department surveillance data and provides technical expertise for surveillance activities within CDS and for the Department.

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Published

2013-03-23

How to Cite

Hamby, T., Tsai, S., Genese, C., Walsh, A., Bradford, L., & Lifshitz, E. (2013). Paralysis Analysis: Investigating Paralysis Visit Anomalies in New Jersey. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4441

Issue

Section

Poster Presentations