Minimizing electronic health record patient-note mismatches |
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Authors: | Adam B Wilcox Yueh-Hsia Chen George Hripcsak |
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Affiliation: | Department of Biomedical Informatics, Columbia University Medical Center, New York, New York, USA |
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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. |
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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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