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Journal of General Internal Medicine

, Volume 33, Issue 4, pp 409–411 | Cite as

Association between Electronic Medical Record Implementation of Default Opioid Prescription Quantities and Prescribing Behavior in Two Emergency Departments

  • M. Kit Delgado
  • Frances S. Shofer
  • Mitesh S. Patel
  • Scott Halpern
  • Christopher Edwards
  • Zachary F. Meisel
  • Jeanmarie Perrone
Concise Research Report

INTRODUCTION

Larger quantities of opioid tablets for initial prescriptions are associated with transition to continued use.1 Default options, or conditions that are set in place unless an alternative is actively chosen, have been shown to influence behavior in many contexts, including increasing the rates of prescribing generic versus brand-name drugs to over 98% in primary care.2,3 Leveraging default options in electronic medical record (EMR) prescribing orders thus represents a promising approach to guide clinicians towards prescribing smaller quantities of opioid tablets, thus reducing continued use, misuse, and diversion.

In 2015, the emergency departments (EDs) of the Hospital of the University of Pennsylvania (HUP, annual volume 68,000) and Penn Presbyterian Medical Center (PMC, annual volume 41,000) adopted a new EMR (Epic, Verona, WI) to replace a homegrown EMR (EMTRAC). EMTRAC required the clinician to enter the number of tablets for opioid prescriptions. Since the...

KEY WORDS

opioid prescribing defaults EMR 

Notes

Acknowledgments

Research reported in this manuscript was supported by the National Institute on Drug Abuse and the National Institute of Child Health and Human Development of the National Institutes of Health under award numbers P30DA040500 (MKD, ZM, JP) K23HD090272001 (MKD). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Compliance with Ethical Standards

Conflict of Interest

Dr. Delgado reports receiving an honorarium for participating in an Expert Roundtable on Opioid Prescribing convened by United Health Group. Dr. Patel is the founder/owner of Catalyst Health, a technology and behavioral change consulting firm, and is a member of the advisory boards of Healthmine, Inc. and Life.io. All other authors declare that they have no conflict of interest.

References

  1. 1.
    Shah A, Hayes CJ, Martin BC. Characteristics of initial prescription episodes and likelihood of long-term opioid use—United States, 2006–2015. MMWR Morb Mortal Wkly Rep. 2017;66:265–69.  https://doi.org/10.15585/mmwr.mm6610a1.
  2. 2.
    Halpern SD, Ubel PA, Asch DA. Harnessing the power of default options to improve health care. N Engl J Med 2007;357(13):1340.CrossRefPubMedGoogle Scholar
  3. 3.
    Patel MS, Day SC, Halpern SD, Hanson WC, Martinez JR, Honeywell S, Volpp KG. Generic medication prescription rates after health system-wide redesign of default options within the electronic health record. JAMA Intern Med. 2016;176(6):847–8.Google Scholar
  4. 4.
    Weiner SG, Baker O, Poon SJ, Rodgers AF, Garner C, Nelson LS, Schuur J. The effect of opioid prescribing guidelines on prescriptions by emergency physicians in Ohio. Ann Emerg Med. 2017;70(6):799–808.Google Scholar
  5. 5.
    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):1567–69.Google Scholar

Copyright information

© Society of General Internal Medicine 2018

Authors and Affiliations

  • M. Kit Delgado
    • 1
    • 2
    • 3
    • 4
  • Frances S. Shofer
    • 1
  • Mitesh S. Patel
    • 3
    • 5
  • Scott Halpern
    • 2
    • 3
    • 5
    • 6
  • Christopher Edwards
    • 1
  • Zachary F. Meisel
    • 1
    • 4
  • Jeanmarie Perrone
    • 1
  1. 1.Center for Emergency Care Policy and Research, Department of Emergency Medicine, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaUSA
  2. 2.Department of Biostatistics, Epidemiology, and Informatics, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaUSA
  3. 3.Center for Health Incentives and Behavioral Economics, Perelman School of Medicine University of PennsylvaniaPhiladelphiaUSA
  4. 4.Penn Injury Science CenterUniversity of PennsylvaniaPhiladelphiaUSA
  5. 5.Department of Medicine, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaUSA
  6. 6.Department of Medical Ethics and Health Policy, Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaUSA

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