CancelRx: a health IT tool to reduce medication discrepancies in the outpatient setting
- PMID: 33835183
- PMCID: PMC8661442
- DOI: 10.1093/jamia/ocab038
CancelRx: a health IT tool to reduce medication discrepancies in the outpatient setting
Abstract
Objective: Medication list discrepancies between outpatient clinics and pharmacies can lead to medication errors. Within the last decade, a new health information technology (IT), CancelRx, emerged to send a medication cancellation message from the clinic's electronic health record (EHR) to the outpatient pharmacy's software. The objective of this study was to measure the impact of CancelRx on reducing medication discrepancies between the EHR and pharmacy dispensing software.
Materials and methods: CancelRx was implemented in October 2017 at an academic health system. For 12 months prior, and 12 months after CancelRx implementation, data were collected on discontinued medications in the health system's EHR and whether those prescriptions were successfully discontinued in the pharmacy's dispensing software. An interrupted time series analysis was conducted to model the occurrence of prescriptions successfully discontinued over time.
Results: There was an immediate (lag = 0), significant (P < 0.001), and sustained (post-implementation slope 0.02) increase in the proportion of successful medication discontinuations after CancelRx implementation (from 34% to 93%). CancelRx had variable impact based on whether the clinic was primary care (71.4% change prepost) or specialty care (53.9% change prepost). CancelRx reduced the time between when a medication was discontinued in the clinic EHR and pharmacy dispensing software.
Conclusion: CancelRx automated a manual process and illustrated the role for health IT in communicating medication discontinuations between clinics and pharmacies. Overall, CancelRx had a marked benefit on medication list discrepancies and illustrated how health IT can be used across different settings to improve patient care.
Keywords: health information technology; implementation science; interrupted time series analysis; patient safety.
© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.
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