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First published October 12, 2005 as JAMIA PrePrint; doi:10.1197/jamia.M1780
Journal of the American Medical Informatics Association 2006;13(1):61-66
© 2006 American Medical Informatics Association


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Submitted on December 20, 2004
Accepted on September 21, 2005

Acute Infections in Primary Care: Accuracy of Electronic Diagnoses and Electronic Antibiotic Prescribing

Jeffrey A. Linder MD, MPH1*, David W. Bates MD, MSc1, Deborah H. Williams2, Meghan A. Connolly3, and Blackford Middleton MD, MPH, MSc4

Affiliation of the authors: 1 Division of General Medicine, Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA ; 2 Division of General Medicine, Brigham and Women's Hospital, Boston, MA ; 3 Yale School of Nursing and Yale University School of Medicine, Yale University, New Haven, CT ; 4 Division of General Medicine, Brigham and Women's Hospital, Boston, MA; Harvard Medical School, Boston, MA; Clinical Informatics Research and Development, Partners HealthCare System, Boston, MA

* To whom correspondence should be addressed.

Objective To maximize effectiveness, clinical decision support systems must have access to accurate diagnostic and prescribing information. We measured the accuracy of electronic claims diagnoses and electronic antibiotic prescribing for acute respiratory infections (ARI) and urinary tract infections (UTI) in primary care.

Design Retrospective, cross-sectional study of randomly selected visits to 9 clinics in the Brigham and Women's Practice-Based Research Network between 2000 and 2003 with a principle claims diagnosis of an ARI or UTI (n = 827).

Measurements We compared electronic billing diagnoses and electronic antibiotic prescribing to the gold standard of blinded chart review.

Results Claims-derived, electronic ARI diagnoses had a sensitivity of 98%, specificity of 96%, and positive predictive value of 96%. Claims-derived, electronic UTI diagnoses had a sensitivity of 100%, specificity of 87%, and positive predictive value of 85%. According to the visit note, physicians prescribed antibiotics in 45% of ARI visits and 73% of UTI visits. Electronic antibiotic prescribing had a sensitivity of 43%, specificity of 93%, positive predictive value of 90%, and simple agreement of 64%. The sensitivity of electronic antibiotic prescribing increased over time from 22% in 2000 to 58% in 2003 (p for trend < 0.0001).

Comclusion Claims-derived, electronic diagnoses for ARIs and UTIs appear accurate. Although closing, a large gap persists between antibiotic prescribing documented in the visit note and the use of electronic antibiotic prescribing. Barriers to electronic antibiotic prescribing in primary care must be addressed to leverage the potential that computerized decision support systems offer in reducing costs, improving quality, and improving patient safety.




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