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Randomized trial measures diagnostic accuracy of software vs. paper-based methods for medication discrepancies.
BACKGROUND: The Veterans Affairs Portland Healthcare System developed a medication history collection software that displays prescription names and medication images. OBJECTIVE: This article measures the frequency of medication discrepancy reporting using the medication history collection software and compares with the frequency of reporting using a paper-based process. This article also determines the accuracy of each method by comparing both strategies to a best possible medication history. STUDY DESIGN: Randomized, controlled, single-blind trial. SETTING: Three community-based primary care clinics associated with the Veterans Affairs Portland Healthcare System: a 300-bed teaching facility and ambulatory care network serving Veteran soldiers in the Pacific Northwest United States. PARTICIPANTS: Of 212 patients with primary care appointments, 209 patients fulfilled the study requirements. INTERVENTION: Patients randomized to a software-directed medication history or a paper-based medication history. Randomization and allocation to treatment groups were performed using a computer-based random number generator. Assignments were placed in a sealed envelope and opened after participant consent. The research coordinator did not know or have access to the treatment assignment until the time of presentation. MAIN OUTCOME MEASURES: The primary analysis compared the discrepancy detection rates between groups with respect to the health record and a best possible medication history. RESULTS: Of 3,500 medications reviewed, we detected 1,435 discrepancies. Forty-six percent of those discrepancies were potentially high risk for causing an adverse drug event. There was no difference in detection rates between treatment arms. Software sensitivity was 83% and specificity was 91%; paper sensitivity was 81% and specificity was 94%. No participants were lost to follow-up. CONCLUSION: The medication history collection software is an efficient and scalable method for gathering a medication history and detecting high-risk discrepancies. Although it included medication images, the technology did not improve accuracy over a paper list when compared with a best possible medication history. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02135731.
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Lesselroth et al. (2018) studied this question.
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