Automated Surveillance of Outpatients with Pneumonia: A Performance Evaluation

Authors

  • Hongzhang Zheng VA Maryland Health Care System; Medicine, University of Maryland
  • Tariq Siddiqui VA Maryland Health Care System; Medicine, University of Maryland
  • Sylvain DeLisle VA Maryland Health Care System; Medicine, University of Maryland

DOI:

https://doi.org/10.5210/ojphi.v5i1.4536

Abstract

The most effective target for automated influenza surveillance systems is not known. In this work, we simulated a prospective surveillance system operating on authentic historical series of daily casecounts. We determined how long the system would take to detect an injected outbreak of synthetic cases. For influenza epidemics where >/= 5% of cases develop pneumonia, we found shorter outbreak detection delays when surveillance targeted only patients with pneumonia rather than all patients with acute respiratory infections.

Author Biography

Hongzhang Zheng, VA Maryland Health Care System; Medicine, University of Maryland

Dr. DeLisle trained in Pulmonary/Critical Care Med-icine at McGill University and at the University of Iowa, and holds an MBA from the Johns Hopkins University. He is currently an Associate Professor of Medicine at the University of Maryland. In research work supported by the CDC and the VA, he studies how electronic medical records can best be utilized to discover and guide the management of patients with acute respiratory infections.

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Published

2013-03-24

How to Cite

Zheng, H., Siddiqui, T., & DeLisle, S. (2013). Automated Surveillance of Outpatients with Pneumonia: A Performance Evaluation. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4536

Issue

Section

Oral Presentations: Influenza Surveillance Methods - Evaluation and Practice