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Journal of General Internal Medicine

, Volume 34, Issue 8, pp 1522–1529 | Cite as

Emergency Physician Opioid Prescribing and Risk of Long-term Use in the Veterans Health Administration: an Observational Analysis

  • Michael L. Barnett
  • Xinhua Zhao
  • Michael J. Fine
  • Carolyn T. Thorpe
  • Florentina E. Sileanu
  • John P. Cashy
  • Maria K. Mor
  • Thomas R. Radomski
  • Leslie R. M. Hausmann
  • Chester B. Good
  • Walid F. GelladEmail author
Article

Abstract

Background

Treatment by high-opioid prescribing physicians in the emergency department (ED) is associated with higher rates of long-term opioid use among Medicare beneficiaries. However, it is unclear if this result is true in other high-risk populations such as Veterans.

Objective

To estimate the effect of exposure to high-opioid prescribing physicians on long-term opioid use for opioid-naïve Veterans.

Design

Observational study using Veterans Health Administration (VA) encounter and prescription data.

Setting and Participants

Veterans with an index ED visit at any VA facility in 2012 and without opioid prescriptions in the prior 6 months in the VA system (“opioid naïve”).

Measurements

We assigned patients to emergency physicians and categorized physicians into within-hospital quartiles based on their opioid prescribing rates. Our primary outcome was long-term opioid use, defined as 6 months of days supplied in the 12 months subsequent to the ED visit. We compared rates of long-term opioid use among patients treated by high versus low quartile prescribers, adjusting for patient demographic, clinical characteristics, and ED diagnoses.

Results

We identified 57,738 and 86,393 opioid-naïve Veterans managed by 362 and 440 low and high quartile prescribers, respectively. Patient characteristics were similar across groups. ED opioid prescribing rates varied more than threefold between the low and high quartile prescribers within hospitals (6.4% vs. 20.8%, p < 0.001). The frequency of long-term opioid use was higher among Veterans treated by high versus low quartile prescribers, though above the threshold for statistical significance (1.39% vs. 1.26%; adjusted OR 1.11, 95% CI 0.997–1.24, p = 0.056). In subgroup analyses, there were significant associations for patients with back pain (adjusted OR 1.25, 95% CI 1.01–1.55, p = 0.04) and for those with a history of depression (adjusted OR 1.28, 95% CI 1.08–1.51, p = 0.004).

Conclusions

ED physician opioid prescribing varied by over 300% within facility, with a statistically non-significant increased rate of long-term use among opioid-naïve Veterans exposed to the highest intensity prescribers.

KEY WORDS

opioid emergency prescribing Veteran 

Notes

Funding Information

This study is financially supported by a grant from VA Health Services Research & Development (HSR&D) I01 HX001765-01 to Dr. Gellad.

Compliance with Ethical Standards

This study was approved by the institutional review board at the VA Pittsburgh Healthcare System.

Conflict of Interest

Dr. Barnett receives consulting fees unrelated to this work from Greylock McKinnon Associates Inc. and serves as a paid expert witness for plaintiffs in lawsuits against opioid manufacturers and distributors. The authors have no other conflicts of interest to disclose.

Disclaimer

This work represents the opinions of the authors alone and does not necessarily represent the views of the Department of Veterans Affairs, the National Institute on Aging, or the US Government.

Supplementary material

11606_2019_5023_MOESM1_ESM.docx (94 kb)
ESM 1 (DOCX 94 kb)

References

  1. 1.
    Hedegaard H, Miniño AM, Warner M. Drug overdose deaths in the United States, 1999–2017, NCHS Data Brief, no 329. 2018;(Accessed 4 March 2019 at https://www.cdc.gov/nchs/products/databriefs/db329.htm)
  2. 2.
    Targeting The Opioid Drug Crisis: A Health And Human Services Initiative. Health Aff. (Millwood). (Accessed March 4, 2019 at http://healthaffairs.org/blog/2015/04/03/targeting-the-opioid-drug-crisis-a-health-and-human-services-initiative/)
  3. 3.
    U.S. Department of Health and Human Services Behavioral Health Coordinating Committee. Addressing prescription drug abuse in the United States: current activities and future opportunities. 2014;(Accessed 4 March 2019 at https://www.cdc.gov/drugoverdose/pdf/hhs_prescription_drug_abuse_report_09.2013.pdf)
  4. 4.
    Muhuri PK, Gfroerer JC, Christine Davies M. Associations of Nonmedical Pain Reliever Use and Initiation of Heroin Use in the United States. 2013;(Accessed 4 March 2019 at https://www.samhsa.gov/data/sites/default/files/DR006/DR006/nonmedical-pain-reliever-use-2013.htm)
  5. 5.
    National Institute on Drug Abuse. Prescription opioid use is a risk factor for heroin use. (Accessed 4 March 2019 at https://www.drugabuse.gov/publications/research-reports/relationship-between-prescription-drug-heroin-abuse/prescription-opioid-use-risk-factor-heroin-use)
  6. 6.
    Barnett ML, Gray J, Zink A, Jena AB. Coupling Policymaking with Evaluation — The Case of the Opioid Crisis. N Engl J Med 2017;377(24):2306–9.CrossRefGoogle Scholar
  7. 7.
    Veterans Face Greater Risks Amid Opioid Crisis. FRONTLINE. (Accessed 4 March 2019 at https://www.pbs.org/wgbh/frontline/article/veterans-face-greater-risks-amid-opioid-crisis/)
  8. 8.
    Seal KH, Shi Y, Cohen G, et al. Association of Mental Health Disorders With Prescription Opioids and High-Risk Opioid Use in US Veterans of Iraq and Afghanistan. JAMA 2012;307(9):940–7.CrossRefGoogle Scholar
  9. 9.
    Bohnert ASB, Ilgen MA, Galea S, McCarthy JF, Blow FC. Accidental poisoning mortality among patients in the Department of Veterans Affairs Health System. Med Care 2011;49(4):393–6.CrossRefGoogle Scholar
  10. 10.
    Brat GA, Agniel D, Beam A, et al. Postsurgical prescriptions for opioid naive patients and association with overdose and misuse: retrospective cohort study. BMJ 2018;360:j5790.CrossRefGoogle Scholar
  11. 11.
    Shah A. Characteristics of Initial Prescription Episodes and Likelihood of Long-Term Opioid Use — United States, 2006–2015. MMWR Morb Mortal Wkly Rep 2017;66. (Accessed 4 March 2019 at https://www.facebook.com/CDCMMWR )
  12. 12.
    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):663–73.CrossRefGoogle Scholar
  13. 13.
    Hastings SN, Smith VA, Weinberger M, Schmader KE, Olsen MK, Oddone EZ. Emergency department visits in Veterans Affairs medical facilities. Am J Manag Care 2011;17(6 Spec No.):e215–223.Google Scholar
  14. 14.
    Gundlapalli AV, Jones AL, Redd A, et al. Characteristics of the Highest Users of Emergency Services in Veterans Affairs Hospitals: Homeless and Non-Homeless. Stud Health Technol Inform 2017;238:24–7.PubMedPubMedCentralGoogle Scholar
  15. 15.
    Dowell D, Haegerich TM, Chou R. CDC guideline for prescribing opioids for chronic pain. JAMA 2016;315(15):1624–45.CrossRefGoogle Scholar
  16. 16.
    Jena AB, Goldman D, Weaver L, Karaca-Mandic P. Opioid prescribing by multiple providers in Medicare: retrospective observational study of insurance claims. BMJ 2014;348:g1393.CrossRefGoogle Scholar
  17. 17.
    Quan H, Li B, Couris CM, et al. Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol 2011;173(6):676–82.CrossRefGoogle Scholar
  18. 18.
    Davis MA, Lin LA, Liu H, Sites BD. Prescription Opioid Use among Adults with Mental Health Disorders in the United States. J Am Board Fam Med 2017;30(4):407–17.CrossRefGoogle Scholar
  19. 19.
    Abuse NI on D. Part 1: The Connection Between Substance Use Disorders and Mental Illness. (Accessed 4 March 2019 at https://www.drugabuse.gov/publications/common-comorbidities-substance-use-disorders/part-1-connection-between-substance-use-disorders-mental-illness)
  20. 20.
    HCUP-US Tools & Software Page. Accessed 4 March 2019 at https://www.hcup-us.ahrq.gov/toolssoftware/ccs/ccs.jsp
  21. 21.
    White H. A heteroskedasticity-consistent covariance matrix and a direct test for heteroskedasticity. Econometrica 1980;48:817–38.CrossRefGoogle Scholar
  22. 22.
    Azur MJ, Stuart EA, Frangakis C, Leaf PJ. Multiple Imputation by Chained Equations: What is it and how does it work? Int J Methods Psychiatr Res 2011;20(1):40–9.CrossRefGoogle Scholar
  23. 23.
    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):1661–7.CrossRefGoogle Scholar
  24. 24.
    Friedman BW, Dym AA, Davitt M, et al. Naproxen With Cyclobenzaprine, Oxycodone/Acetaminophen, or Placebo for Treating Acute Low Back Pain: A Randomized Clinical Trial. JAMA 2015;314(15):1572–80.CrossRefGoogle Scholar
  25. 25.
    Sun EC, Darnall BD, Baker LC, Mackey S. Incidence of and Risk Factors for Chronic Opioid Use Among Opioid-Naive Patients in the Postoperative Period. JAMA Intern Med 2016;176(9):1286–93.CrossRefGoogle Scholar
  26. 26.
    Boscarino JA, Rukstalis M, Hoffman SN, et al. Risk factors for drug dependence among out-patients on opioid therapy in a large US health-care system: Risk factors for drug dependence among out-patients. Addiction 2010;105(10):1776–82.CrossRefGoogle Scholar
  27. 27.
    Sullivan MD, Edlund MJ, Fan M-Y, DeVries A, Brennan Braden J, Martin BC. Risks for possible and probable opioid misuse among recipients of chronic opioid therapy in commercial and medicaid insurance plans: The TROUP Study. PAIN 2010;150(2):332–9.CrossRefGoogle Scholar
  28. 28.
    Webster BS, Verma SK, Gatchel RJ. Relationship between early opioid prescribing for acute occupational low back pain and disability duration, medical costs, subsequent surgery and late opioid use. Spine 2007;32(19):2127–32.CrossRefGoogle Scholar

Copyright information

© Society of General Internal Medicine (This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply) 2019

Authors and Affiliations

  • Michael L. Barnett
    • 1
    • 2
  • Xinhua Zhao
    • 3
  • Michael J. Fine
    • 3
    • 4
  • Carolyn T. Thorpe
    • 3
    • 5
  • Florentina E. Sileanu
    • 3
  • John P. Cashy
    • 3
  • Maria K. Mor
    • 3
    • 6
  • Thomas R. Radomski
    • 3
    • 4
  • Leslie R. M. Hausmann
    • 3
    • 4
  • Chester B. Good
    • 3
    • 4
    • 7
  • Walid F. Gellad
    • 3
    • 4
    Email author
  1. 1.Department of Health Policy and Management Harvard T.H. Chan School of Public HealthBostonUSA
  2. 2.Division of General Internal Medicine and Primary Care, Department of MedicineBrigham and Women’s HospitalBostonUSA
  3. 3.Center for Health Equity Research and Promotion (CHERP) VA Pittsburgh Healthcare SystemPittsburghUSA
  4. 4.Department of Medicine, Division of General Internal MedicineUniversity of PittsburghPittsburghUSA
  5. 5.Division of Pharmaceutical Outcomes and PolicyUniversity of North Carolina Eshelman School of PharmacyChapel HillUSA
  6. 6.Department of Biostatistics, Graduate School of Public HealthUniversity of PittsburghPittsburghUSA
  7. 7.Center for High Value Health CareUniversity of Pittsburgh Medical Center (UPMC)PittsburghUSA

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