Time of Arrival Analysis in NC DETECT to Find Clusters of Interest from Unclassified Patient Visit Records

Authors

  • Meichun Li Emergency Medicine, UNC Chapel Hill
  • Wayne Loschen Johns Hopkins University Applied Physics Laboratory
  • Lana Deyneka North Carolina Division of Public Health
  • Howard Burkom Johns Hopkins University Applied Physics Laboratory
  • Amy Ising Emergency Medicine, UNC Chapel Hill
  • Anna Waller Emergency Medicine, UNC Chapel Hill

DOI:

https://doi.org/10.5210/ojphi.v5i1.4512

Abstract

This abstract describes a collaboration with the Johns Hopkins Applied Physics Laboratory, the North Carolina Division of Public Health, and the UNC Department of Emergency Medicine Carolina Center for Health Informatics to implement time-of-arrival analysis for hospital emergency department (ED) data in NC DETECT to identify clusters of ED visits for which there is no pre-defined syndrome or sub-syndrome.

Author Biography

Meichun Li, Emergency Medicine, UNC Chapel Hill

Meichun Li, MS is a Software Engineer and Adjunct Research Instructor at the Carolina Center for Health Informatics in the Department of Emergency Medicine at UNC-Chapel Hill. She leads the design, development and maintenance of NC DETECT web portal. She received her Master's degree in Information Science from UNC-Chapel Hill.

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Published

2013-03-23

How to Cite

Li, M., Loschen, W., Deyneka, L., Burkom, H., Ising, A., & Waller, A. (2013). Time of Arrival Analysis in NC DETECT to Find Clusters of Interest from Unclassified Patient Visit Records. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4512

Issue

Section

Oral Presentations: Cluster Detection