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Journal of General Internal Medicine

, Volume 34, Issue 6, pp 936–943 | Cite as

The Role of Primary Care in Improving Access to Medication-Assisted Treatment for Rural Medicaid Enrollees with Opioid Use Disorder

  • Evan S. ColeEmail author
  • Ellen DiDomenico
  • Gerald Cochran
  • Adam J. Gordon
  • Walid F. Gellad
  • Janice Pringle
  • Jack Warwick
  • Chung-Chou H. Chang
  • Joo Yeon Kim
  • Julie Kmiec
  • David Kelley
  • Julie M. Donohue
Original Research

Abstract

Background

The opioid epidemic has disproportionately affected rural areas, where a limited number of health care providers offer medication-assisted treatment (MAT), the mainstay of treatment for opioid use disorder (OUD). Rural residents with OUD may face multiple barriers to engagement in MAT including long travel distances.

Objective

To examine the degree to which rural residents with OUD are engaged with primary care providers (PCPs), describe the role of rural PCPs in MAT delivery, and estimate the association between enrollee distance to MAT prescribers and MAT utilization.

Design

Retrospective cohort study.

Participants

Medicaid-enrolled adults diagnosed with OUD in 23 rural Pennsylvania counties.

Main Measures

Primary care utilization, MAT utilization, distance to nearest possible MAT prescriber, mean distance traveled to actual MAT prescribers, and continuity of pharmacotherapy.

Key Results

Of the 7930 Medicaid enrollees with a diagnosis of OUD, a minority (18.6%) received their diagnosis during a PCP visit even though enrollees with OUD had 4.1 visits to PCPs per person-year in 2015. Among enrollees with an OUD diagnosis recorded during a PCP visit, about half (751, 50.8%) received MAT, most of whom (508, 67.6%) received MAT from a PCP. Enrollees with OUD with at least one PCP visit were more likely than those without a PCP visit to receive MAT (32.7% vs. 25%; p < 0.001), and filled more buprenorphine and naltrexone prescriptions (mean = 11.1 vs. 9.3; p < 0.001). The median of the distances traveled to actual MAT prescribers was 48.8 miles, compared to a median of 4.2 miles to the nearest available MAT prescriber. Enrollees traveling a mean distance greater than 45 miles to MAT prescribers were less likely to receive continuity of pharmacotherapy (OR = 0.71, 95% CI = 0.56–0.91, p = 0.007).

Conclusions

PCP utilization among rural Medicaid enrollees diagnosed with OUD is high, presenting a potential intervention point to treat OUD, particularly if the enrollee’s PCP is located nearer than their MAT prescriber.

KEY WORDS

primary care medication-assisted treatment rural opioid use disorder 

Notes

Funding Information

This study was funded by a grant from the Agency for Healthcare Research & Quality (1R18HS025072-01).

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they do not have a conflict of interest.

References

  1. 1.
    Substance Abuse and Mental Health Services Administration. Medication-Assisted Treatment. 2017; https://www.samhsa.gov/medication-assisted-treatment. Accessed 13 Aug 2017.
  2. 2.
    Dick AW, Pacula RL, Gordon AJ, et al. Growth In Buprenorphine Waivers For Physicians Increased Potential Access To Opioid Agonist Treatment, 2002-11. Health Aff. 2015;34(6):1028–1034.CrossRefGoogle Scholar
  3. 3.
    PA Health Care Cost Containment Council. Hospitalizations for Overdose of Pain Medication and Heroin. Harrisburg, PA; 2016.Google Scholar
  4. 4.
    Rosenblatt RA, Andrilla CH, Catlin M, Larson EH. Geographic and specialty distribution of US physicians trained to treat opioid use disorder. Ann Fam Med. 2015;13(1):23–26.CrossRefGoogle Scholar
  5. 5.
    Substance Abuse and Mental Health Services Administration. 2014 Buprenorphine Summit. Rockville, MD; 2014.Google Scholar
  6. 6.
    Barry DT, Irwin KS, Jones ES, et al. Integrating buprenorphine treatment into office-based practice: a qualitative study. J Gen Intern Med. 2009;24(2):218–225.CrossRefGoogle Scholar
  7. 7.
    Oliva EM, Maisel NC, Gordon AJ, Harris AH. Barriers to use of pharmacotherapy for addiction disorders and how to overcome them. Curr Psychiatry Rep. 2011;13(5):374.CrossRefGoogle Scholar
  8. 8.
    Hutchinson E, Catlin M, Andrilla CHA, Baldwin L-M, Rosenblatt RA. Barriers to primary care physicians prescribing buprenorphine. Ann Fam Med. 2014;12(2):128–133.CrossRefGoogle Scholar
  9. 9.
    Kissin W, McLeod C, Sonnefeld J, Stanton A. Experiences of a national sample of qualified addiction specialists who have and have not prescribed buprenorphine for opioid dependence. J Addict Dis. 2006;25(4):91–103.CrossRefGoogle Scholar
  10. 10.
    Buzza C, Ono SS, Turvey C, et al. Distance is relative: unpacking a principal barrier in rural healthcare. J Gen Intern Med. 2011;26 Suppl 2:648–654.CrossRefGoogle Scholar
  11. 11.
    Kelly C, Hulme C, Farragher T, Clarke G. Are differences in travel time or distance to healthcare for adults in global north countries associated with an impact on health outcomes? A systematic review. BMJ Open. 2016;6(11):e013059.CrossRefGoogle Scholar
  12. 12.
    Luu H, Slavova S, Freeman PR, Lofwall M, Browning S, Trends H. Trends and Patterns of Opioid Analgesic Prescribing: Regional and Rural-Urban Variations in Kentucky From 2012 to 2015. J Rural Health. 2018.Google Scholar
  13. 13.
    Zur J, Tolbert J. The Opioid Epidemic and Medicaid's Role in Facilitating Access to Treatment. 2018. https://www.kff.org/medicaid/issue-brief/the-opioid-epidemic-and-medicaids-role-in-facilitating-access-to-treatment/. Accessed 16 May 2018.
  14. 14.
    Centers for Medicare and Medicaid Services. Medicaid Enrollment Data Collected Through MBES. 2018. https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/enrollment-mbes/index.html. Accessed 17 Sept 2018.
  15. 15.
  16. 16.
    United States Census Bureau. Lists of Population, Land Area, and Percent Urban and Rural in 2010 and Changes from 2000 to 2010. 2010. https://www.census.gov/geo/reference/ua/urban-rural-2010.html. Accessed 19 Jan 2018.
  17. 17.
    McKenna RM. Treatment use, sources of payment, and financial barriers to treatment among individuals with opioid use disorder following the national implementation of the ACA. Drug Alcohol Depend. 2017;179:87–92.CrossRefGoogle Scholar
  18. 18.
    Kim HM, Smith EG, Stano CM, et al. Validation of key behaviourally based mental health diagnoses in administrative data: suicide attempt, alcohol abuse, illicit drug abuse and tobacco use. BMC Health Serv Res. 2012;12(1):18.CrossRefGoogle Scholar
  19. 19.
    Rowe C, Vittinghoff E, Santos GM, Behar E, Turner C, Coffin PO. Performance Measures of Diagnostic Codes for Detecting Opioid Overdose in the Emergency Department. Acad Emerg Med Off J Soc Acad Emerg Med. 2017;24(4):475–483.CrossRefGoogle Scholar
  20. 20.
    National Quality Forum. Behavioral Health 2016-2017. Washington DC; 2017.Google Scholar
  21. 21.
    Chronic Conditions Data Warehouse. Condition Categories. 2018. https://www.ccwdata.org/web/guest/condition-categories. Accessed 16 May 2018.
  22. 22.
    Elixhauser A, Steiner C, Harris DR, Coffey RM. Comorbidity measures for use with administrative data. Med Care. 1998;36(1):8–27.CrossRefGoogle Scholar
  23. 23.
    Health Maintenance Organization Act, § 9.679 The Administrative Code of 1929. 2001.Google Scholar

Copyright information

© Society of General Internal Medicine 2019

Authors and Affiliations

  • Evan S. Cole
    • 1
    Email author
  • Ellen DiDomenico
    • 2
  • Gerald Cochran
    • 3
  • Adam J. Gordon
    • 3
  • Walid F. Gellad
    • 1
    • 4
  • Janice Pringle
    • 5
  • Jack Warwick
    • 5
  • Chung-Chou H. Chang
    • 4
  • Joo Yeon Kim
    • 1
  • Julie Kmiec
    • 6
  • David Kelley
    • 7
  • Julie M. Donohue
    • 1
  1. 1.Department of Health Policy and ManagementUniversity of Pittsburgh Graduate School of Public HealthPittsburghUSA
  2. 2.Pennsylvania Department of Drug and Alcohol ProgramsHarrisburgUSA
  3. 3.Department of Internal Medicine, Division of EpidemiologyUniversity of Utah School of MedicineSalt Lake CityUSA
  4. 4.Division of General Internal MedicineUniversity of Pittsburgh School of MedicinePittsburghUSA
  5. 5.Program Evaluation and Research UnitUniversity of Pittsburgh School of PharmacyPittsburghUSA
  6. 6.Department of PsychiatryUniversity of PittsburghPittsburghUSA
  7. 7.Pennsylvania Department of Human ServicesHarrisburgUSA

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