Background: As medical care moves towards an outpatient focus, monitoring systems for ambulatory patients are increasingly important. Because adverse outcomes due to medications are an important problem in outpatients, the authors developed an automated monitoring system for detecting adverse drug reactions (ADRs) in ambulatory patients.
Methods: The authors obtained a set of approximately 110 000 ambulatory care notes from the medicine clinic at Bellevue Hospital Centre for 2003–4, and manually analysed a representative sample of 1250 notes to obtain a gold standard. To detect ADRs in the text of electronic ambulatory notes, the authors used a “trigger phrases” methodology, based on a simple grammar populated with a limited set of keywords.
Results: Under current functionality, this system detected 38 of 54 cases in the authors’ gold standard set, of which 17 were true positives, for a sensitivity of 31%, a specificity of 98%, and a positive predictive value of 45%. Their proxy measure correlated with 70% of the ADRs in the gold standard. These values are comparable or superior to other systems described in the literature.
Conclusions: These results show that an automated system can detect ADRs with moderate sensitivity and high specificity, and has the potential to serve as the basis for a larger scale reporting system.
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Supported by the Department of Medicine, New York University School of Medicine, and grant 2002-DT-CX-K002 from the US Department of Homeland Security.
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