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First published August 23, 2006 as JAMIA PrePrint; doi:10.1197/jamia.M2078
Journal of the American Medical Informatics Association 2006;13(6):691-695
© 2006 American Medical Informatics Association

A more recent version of this article appeared on November 1, 2006
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Submitted on February 7, 2006
Accepted on August 8, 2006

Using Regular Expressions to Abstract Blood Pressure and Treatment Intensification Information from the Text of Physician Notes

Alexander Turchin MD, MS1*, Nikheel S. Kolatkar MD2, Richard W. Grant MD, MPH3, Eric C. Makhni4, Merri L. Pendergrass MD, PhD2, and Jonathan S. Einbinder MD, MPH5

Affiliation of the authors: 1 Division of Endocrinology, Brigham and Women’s Hospital, Boston, MA; Harvard Medical School, Boston, MA; Clinical Informatics Research and Development, Partners HealthCare System, Boston, MA ; 2 Division of Endocrinology, Brigham and Women’s Hospital, Boston, MA; Harvard Medical School, Boston, MA ; 3 Division of General Medicine, Massachusetts General Hospital, Boston, MA; Harvard Medical School, Boston, MA ; 4 Harvard Medical School, Boston, MA; 5 Harvard Medical School, Boston, MA; Clinical Informatics Research and Development, Partners HealthCare System, Boston, MA; 5Division of General Medicine, Brigham and Women’s Hospital, Boston, MA

* To whom correspondence should be addressed.

This case study examined the utility of regular expressions to identify clinical data relevant to the epidemiology of treatment of hypertension. We designed a software tool that employed regular expressions to identify and extract instances of documented blood pressure values and anti-hypertensive treatment intensification from the text of physician notes. We determined sensitivity, specificity and precision of identification of blood pressure values and anti-hypertensive treatment intensification using a gold standard of manual abstraction of 600 notes by two independent reviewers. The software processed 370 Mb of text per hour, and identified elevated blood pressure documented in free text physician notes with sensitivity and specificity of 98%, and precision of 93.2%. Anti-hypertensive treatment intensification was identified with sensitivity 83.8%, specificity of 95.0%, and precision of 85.9%. Regular expressions can be an effective method for focused information extraction tasks related to high-priority disease areas such as hypertension.




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