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Updated: Jan 5, 2026

Drug Repurposing Hypothesis Generation Using the "RE:fine Drugs" System
Published on: December 11, 2016
Medication Reconciliation Improvement Utilizing Process Redesign and Clinical Decision Support
Background:
Despite years of attention, hospitals continue to struggle to implement successful medication reconciliation. This study aimed to increase the percentage of hospital admission medication reconciliation (AdmMedRec) completion to ≥ 95% in 12 months at a large academic children's hospital.
Methods:
A quality improvement (QI) project was initiated in April 2017 by an interdisciplinary team of physicians, nurses, pharmacists, and analysts, co-led by a pediatric hospitalist and chief medical information officer. Interventions were implemented through sequential Plan-Do-Study-Act cycles. Process maps, fishbone diagrams, and failure mode and effects analysis were used to identify AdmMedRec failures. Baseline data from 12,481 admission encounters July 2016-April 2017 were analyzed. Interventions included electronic health record (EHR) workflow redesign, clarification of clinicians' responsibilities, targeted training, Best Practice Advisory alert, and weekly reporting of specialty- and physician-specific performance data. Data from 13,082 postintervention period admission encounters were examined. Reconciliation by therapeutic drug classes was calculated as a proxy for quality.
Results:
AdmMedRec completion rate increased from a baseline of 73% to 95% within 7 months from the start of this project and was sustained at 94% during the postintervention period. Psychiatry and hospital medicine demonstrated the largest improvements, with rates increasing from 17% to 88% and 76% to 98%, respectively. Percentages of reconciled medications in all 13 therapeutic classes, including high-risk drugs, improved significantly (p < 0.05).
Conclusions:
Using an interdisciplinary team and interventions focused on process and culture changes, this QI initiative was successful at increasing AdmMedRec rates and reducing omission errors across all therapeutic drug classes.
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