Extracting Surveillance Data from Templated Sections of an Electronic Medical Note: Challenges and Opportunities

Authors

  • Adi Gundlapalli VA Salt Lake City Health Care System; Internal Medicine, University of Utah School of Medicine
  • Guy Divita VA Salt Lake City Health Care System; Internal Medicine, University of Utah School of Medicine
  • Marjorie Carter VA Salt Lake City Health Care System; Internal Medicine, University of Utah School of Medicine
  • Shuying Shen VA Salt Lake City Health Care System; Internal Medicine, University of Utah School of Medicine
  • Miland Palmer VA Salt Lake City Health Care System
  • Tyler Forbush VA Salt Lake City Health Care System; Internal Medicine, University of Utah School of Medicine
  • Brett South VA Salt Lake City Health Care System; Internal Medicine, University of Utah School of Medicine
  • Andrew Redd VA Salt Lake City Health Care System; Internal Medicine, University of Utah School of Medicine
  • Brian Sauer VA Salt Lake City Health Care System; Internal Medicine, University of Utah School of Medicine
  • Matthew Samore VA Salt Lake City Health Care System; Internal Medicine, University of Utah School of Medicine

DOI:

https://doi.org/10.5210/ojphi.v5i1.4535

Abstract

Apart from the traditional structured data elements used for surveillance, the free text of the medical note provides a rich source of epidemiological information. Many electronic notes use boiler-plate templates from EMR pull-downs to document information on the patient in the form of checklists, check boxes, yes/no and free text responses to questions. There is a dearth of literature on the use of natural language processing in extracting data from templates in the EMR. This study was undertaken to highlight the challenges and opportunities of addressing templates while developing NLP algorithms for surveillance using the free text of electronic notes.

Author Biography

Adi Gundlapalli, VA Salt Lake City Health Care System; Internal Medicine, University of Utah School of Medicine

AVG is a board certified infectious diseases physician, epidemiologist and informatician whose main research interest is in biosurveillance. He uses methods from informatics including natural language processing, epidemiology and mathematical modeling in his research. His current work involves applying surveillance and other data mining methods to VA big data in the high priority domains of Veteran homelessness and medically unexplained syndromes.

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Published

2013-03-23

How to Cite

Gundlapalli, A., Divita, G., Carter, M., Shen, S., Palmer, M., Forbush, T., … Samore, M. (2013). Extracting Surveillance Data from Templated Sections of an Electronic Medical Note: Challenges and Opportunities. Online Journal of Public Health Informatics, 5(1). https://doi.org/10.5210/ojphi.v5i1.4535

Issue

Vol. 5 No. 1 (2013)

Section

Oral Presentations: Syndrome Development & Validation & Natural Language Processing

License

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