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Association of Default Electronic Medical Record Settings With Health Care Professional Patterns of Opioid Prescribing in Emergency DepartmentsA Randomized Quality Improvement Study

Educational Objective
To determine whether and to what extent changes in the default settings in the electronic medical record are associated with opioid prescriptions for patients discharged from emergency departments.
1 Credit CME
Key Points

Question  Is changing the electronic medical record default settings for opioid prescriptions associated with the quantity of opioids prescribed for patients discharged from emergency departments?

Findings  In this randomized quality improvement study of 4320 opioid prescriptions, lower default settings were associated with fewer opioids prescribed and a lower proportion of prescriptions that exceeded the opioid prescribing recommendation of the Centers for Disease Control and Prevention.

Meaning  These findings suggest that default electronic medical record settings may influence prescribing behavior and should be modified to decrease the quantity of opioids prescribed.

Abstract

Importance  Prescription opioids play a significant role in the ongoing opioid crisis. Guidelines and physician education have had mixed success in curbing opioid prescriptions, highlighting the need for other tools that can change prescriber behavior, including nudges based in behavioral economics.

Objective  To determine whether and to what extent changes in the default settings in the electronic medical record (EMR) are associated with opioid prescriptions for patients discharged from emergency departments (EDs).

Design, Setting, and Participants  This quality improvement study randomly altered, during a series of five 4-week blocks, the prepopulated dispense quantities of discharge prescriptions for commonly prescribed opioids at 2 large, urban EDs. These changes were made without announcement, and prescribers were not informed of the study itself. Participants included all health care professionals (physicians, nurse practitioners, and physician assistants) working clinically in either of the 2 EDs. Data were collected from November 28, 2016, through July 9, 2017, and analyzed from July 16, 2017, through May 14, 2018.

Interventions  Default quantities for opioids were changed from status quo quantities of 12 and 20 tablets to null, 5, 10, and 15 tablets according to a block randomization scheme. Regardless of the default quantity, each health care professional decided for whom to prescribe opioids and could modify the quantity prescribed without restriction.

Main Outcomes and Measures  The primary outcome was the number of tablets of opioid-containing medications prescribed under each default setting.

Results  A total of 104 health care professionals wrote 4320 prescriptions for opioids during the study period. Using linear regression, an increase of 0.19 tablets prescribed (95% CI, 0.15-0.22) was found for each tablet increase in default quantity. When evaluating each of the 15 pairwise comparisons of default quantities (eg, 5 vs 15 tablets), a lower default was associated with a lower number of pills prescribed in more than half (8 of the 15) of the pairwise comparisons; there was a higher quantity in 1 and no difference in 6 comparisons.

Conclusions and Relevance  These findings suggest that default settings in the EMR may influence the quantity of opioids prescribed by health care professionals. This low-cost, easily implementable, EMR-based intervention could have far-reaching implications for opioid prescribing and could be used as a tool to help combat the opioid epidemic.

Trial Registration  ClinicalTrials.gov identifier: NCT04155229

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Article Information

Accepted for Publication: November 10, 2019.

Corresponding Author: Juan Carlos C. Montoy, MD, PhD, Department of Emergency Medicine, University of California, San Francisco, 1001 Potrero Ave, Bldg 5, Room 6A, San Francisco, CA 94110 (juancarlos.montoy@ucsf.edu).

Published Online: January 21, 2020. doi:10.1001/jamainternmed.2019.6544

Author Contributions: Dr Montoy had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Montoy, Coralic, Herring, Raven.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Montoy, Coralic, Herring, Clattenburg.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Montoy, Herring.

Obtained funding: Montoy.

Administrative, technical, or material support: Coralic, Herring.

Supervision: Raven.

Conflict of Interest Disclosures: Dr Montoy reported receiving grants from University of California, San Francisco (UCSF), Clinical and Translational Science Institute during the conduct of the study. Dr Coralic reported receiving grants from UCSF during the conduct of the study; serving as a paid expert witness for Par Pharmaceutical in a patent litigation case; and serving as an expert witness for the defendant in a medicolegal case where the issue of opioid administration in the emergency department was discussed. Dr Raven reported receiving grants from CareStar Foundation and the California ED BRIDGE Program and nonfinancial support from Collective Medical outside the submitted work. No other disclosures were reported.

Funding/Support: This study was supported by umbrella grant UL1 TR001872 from the National Institutes of Health National Center for Advancing Translational Sciences (UCSF Clinical and Translational Institute).

Role of the Funder/Sponsor: The sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or decision to submit the manuscript for publication.

Disclaimer: The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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