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Minimizing electronic health record patient-note mismatches
Authors:Adam B Wilcox  Yueh-Hsia Chen  George Hripcsak
Affiliation:Department of Biomedical Informatics, Columbia University Medical Center, New York, New York, USA
Abstract:We measured the prevalence (or rate) of patient-note mismatches (clinical notes judged to pertain to another patient) in the electronic medical record. The rate ranged from 0.5% (95% CI 0.2% to 1.7%) before a pop-up window intervention to 0.3% (95% CI 0.1% to 1.1%) after the intervention. Clinicians discovered patient-note mismatches in 0.05–0.03% of notes, or about 10% of actual mismatches. The reduction in rates after the intervention was statistically significant. Therefore, while the patient-note mismatch rate is low compared to published rates of other documentation errors, it can be further reduced by the design of the user interface.
Keywords:Data mining   electronic health records   machine learning   informatics research   national health it agenda   evaluation and surveys   health IT workforce education   innovation in health it
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