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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.


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 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 (

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.

Rudd  RA, Aleshire  N, Zibbell  JE, Gladden  RM; Centers for Disease Control and Prevention.  Increases in drug and opioid overdose deaths—United States, 2000-2014.  MMWR Morb Mortal Wkly Rep. 2016;64(50-51):1378-1382. doi:10.15585/mmwr.mm6450a3PubMedGoogle ScholarCrossref
Unick  GJ, Rosenblum  D, Mars  S, Ciccarone  D.  Intertwined epidemics: national demographic trends in hospitalizations for heroin- and opioid-related overdoses, 1993-2009.  PLoS One. 2013;8(2):e54496. doi:10.1371/journal.pone.0054496PubMedGoogle Scholar
Bohnert  AS, Valenstein  M, Bair  MJ,  et al.  Association between opioid prescribing patterns and opioid overdose-related deaths.  JAMA. 2011;305(13):1315-1321. doi:10.1001/jama.2011.370PubMedGoogle ScholarCrossref
Alam  A, Gomes  T, Zheng  H, Mamdani  MM, Juurlink  DN, Bell  CM.  Long-term analgesic use after low-risk surgery: a retrospective cohort study.  Arch Intern Med. 2012;172(5):425-430. doi:10.1001/archinternmed.2011.1827PubMedGoogle ScholarCrossref
Hoppe  JA, Kim  H, Heard  K.  Association of emergency department opioid initiation with recurrent opioid use.  Ann Emerg Med. 2015;65(5):493-499.e4. doi:10.1016/j.annemergmed.2014.11.015PubMedGoogle ScholarCrossref
Barnett  ML, Olenski  AR, Jena  AB.  Opioid-prescribing patterns of emergency physicians and risk of long-term use.  N Engl J Med. 2017;376(7):663-673. doi:10.1056/NEJMsa1610524PubMedGoogle ScholarCrossref
Volkow  ND, McLellan  TA, Cotto  JH, Karithanom  M, Weiss  SR.  Characteristics of opioid prescriptions in 2009.  JAMA. 2011;305(13):1299-1301. doi:10.1001/jama.2011.401PubMedGoogle ScholarCrossref
Sun  BC, Charlesworth  CJ, Lupulescu-Mann  N,  et al.  Effect of automated prescription drug monitoring program queries on emergency department opioid prescribing.  Ann Emerg Med. 2018;71(3):337-347.e6. doi:10.1016/j.annemergmed.2017.10.023PubMedGoogle ScholarCrossref
Kuehn  BM.  Scientists, officials eye tools aimed at combating abuse of painkillers.  JAMA. 2012;307(1):19-21. doi:10.1001/jama.2011.1900PubMedGoogle ScholarCrossref
Delgado  MK, Shofer  FS, Patel  MS,  et al.  Association between electronic medical record implementation of default opioid prescription quantities and prescribing behavior in two emergency departments.  J Gen Intern Med. 2018;33(4):409-411. doi:10.1007/s11606-017-4286-5PubMedGoogle ScholarCrossref
Zwank  MD, Kennedy  SM, Stuck  LH, Gordon  BD.  Removing default dispense quantity from opioid prescriptions in the electronic medical record.  Am J Emerg Med. 2017;35(10):1567-1569. doi:10.1016/j.ajem.2017.04.002PubMedGoogle ScholarCrossref
Chiu  AS, Jean  RA, Hoag  JR, Freedman-Weiss  M, Healy  JM, Pei  KY.  Association of lowering default pill counts in electronic medical record systems with postoperative opioid prescribing.  JAMA Surg. 2018;153(11):1012-1019. doi:10.1001/jamasurg.2018.2083PubMedGoogle ScholarCrossref
Dowell  D, Haegerich  TM, Chou  R.  CDC guideline for prescribing opioids for chronic pain—United States, 2016.  JAMA. 2016;315(15):1624-1645. doi:10.1001/jama.2016.1464PubMedGoogle ScholarCrossref
Carroll  GD, Choi  JJ, Laibson  D, Madrian  BC, Metrick  A.  Optimal defaults and active decisions.  Q J Econ. 2009;124(4):1639-1674. doi:10.1162/qjec.2009.124.4.1639PubMedGoogle ScholarCrossref
Ballantyne  JC, Sullivan  MD.  Intensity of chronic pain—the wrong metric?  N Engl J Med. 2015;373(22):2098-2099. doi:10.1056/NEJMp1507136PubMedGoogle ScholarCrossref
Montoy  JCC, Dow  WH, Kaplan  BC.  Patient choice in opt-in, active choice, and opt-out HIV screening: randomized clinical trial.  BMJ. 2016;532:h6895. doi:10.1136/bmj.h6895PubMedGoogle ScholarCrossref
Patel  MS, Day  S, Small  DS,  et al.  Using default options within the electronic health record to increase the prescribing of generic-equivalent medications: a quasi-experimental study.  Ann Intern Med. 2014;161(10)(suppl):S44-S52. doi:10.7326/M13-3001PubMedGoogle ScholarCrossref
Halpern  SD, Loewenstein  G, Volpp  KG,  et al.  Default options in advance directives influence how patients set goals for end-of-life care.  Health Aff (Millwood). 2013;32(2):408-417. doi:10.1377/hlthaff.2012.0895PubMedGoogle ScholarCrossref
Aysola  J, Tahirovic  E, Troxel  AB,  et al.  A randomized controlled trial of opt-in versus opt-out enrollment into a diabetes behavioral intervention.  Am J Health Promot. 2018;32(3):745-752. doi:10.1177/0890117116671673PubMedGoogle ScholarCrossref
Choi  J, Laibson  D, Madrian  B, Metrick  A. Saving for retirement on the path of least resistance. In: McCaffery  EJ, Slemrod  J, eds.  Behavioral Public Finance: Toward a New Agenda. New York, NY: Russell Sage Foundation; 2006:304-351.
Chang  AK, Bijur  PE, Esses  D, Barnaby  DP, Baer  J.  Effect of a single dose of oral opioid and nonopioid analgesics on acute extremity pain in the emergency department: a randomized clinical trial.  JAMA. 2017;318(17):1661-1667. doi:10.1001/jama.2017.16190PubMedGoogle ScholarCrossref
Graudins  A, Meek  R, Parkinson  J, Egerton-Warburton  D, Meyer  A.  A randomised controlled trial of paracetamol and ibuprofen with or without codeine or oxycodone as initial analgesia for adults with moderate pain from limb injury.  Emerg Med Australas. 2016;28(6):666-672. doi:10.1111/1742-6723.12672PubMedGoogle ScholarCrossref
Centers for Disease Control and Prevention. US state prescribing rates, 2016. Opioid overdose. Updated July 31, 2017. Accessed September 3, 2018.
Cal Health & Safety Code § 1165.4.
Axeen  S, Seabury  SA, Menchine  M.  Emergency department contribution to the prescription opioid epidemic.  Ann Emerg Med. 2018;71(6):659-667.e3. doi:10.1016/j.annemergmed.2017.12.007PubMedGoogle ScholarCrossref
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