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JAMIA 2009;16:18-24 doi:10.1197/jamia.M2848
  • The Practice of Informatics
  • Viewpoint Paper

Electronic Support for Public Health: Validated Case Finding and Reporting for Notifiable Diseases Using Electronic Medical Data

  1. Ross Lazarusa,b,
  2. Michael Klompasa,b,
  3. Francis X Campionc,
  4. Scott J N McNabbd,
  5. Xuanlin Houa,b,
  6. James Daniele,
  7. Gillian Haneye,
  8. Alfred DeMariae,
  9. Leslie Lenertd,
  10. Richard Platta,b
  1. aDepartment of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, Boston MA
  2. bChanning Laboratory, Brigham and Women's Hospital, Boston MA
  3. cAtrius Health, Boston, MA
  4. dNational Center for Public Health Informatics, Centers for Disease Control and Prevention, Atlanta, GA
  5. eMassachusetts Department of Public Health, Boston, MA
  1. Correspondence: Dr Ross Lazarus, Channing Laboratory, 181 Longwood Ave., Boston, MA 02115; e-mail: <ross.lazarus{at}gmail.com>
  • Received 7 May 2008
  • Accepted 23 September 2008

Abstract

Health care providers are legally obliged to report cases of specified diseases to public health authorities, but existing manual, provider-initiated reporting systems generally result in incomplete, error-prone, and tardy information flow. Automated laboratory-based reports are more likely accurate and timely, but lack clinical information and treatment details. Here, we describe the Electronic Support for Public Health (ESP) application, a robust, automated, secure, portable public health detection and messaging system for cases of notifiable diseases. The ESP application applies disease specific logic to any complete source of electronic medical data in a fully automated process, and supports an optional case management workflow system for case notification control. All relevant clinical, laboratory and demographic details are securely transferred to the local health authority as an HL7 message. The ESP application has operated continuously in production mode since January 2007, applying rigorously validated case identification logic to ambulatory EMR data from more than 600,000 patients. Source code for this highly interoperable application is freely available under an approved open-source license at http://esphealth.org.

Footnotes

  • Supported by grants from the Centers for Disease Control (PH000238D) and from the Agency for Healthcare Research and Quality (HS 17045).

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