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. Author manuscript; available in PMC: 2021 Mar 1.
Published in final edited form as: J Subst Abuse Treat. 2020 Mar;112 Suppl:41–48. doi: 10.1016/j.jsat.2020.02.001

Documented opioid use disorder and its treatment in primary care patients across six U.S. health systems

Denise M Boudreau 1, Gwen Lapham 1, Eric A Johnson 1, Jennifer F Bobb 1, Abigail G Matthews 2, Jennifer McCormack 2, David Liu 3, Cynthia I Campbell 4, Rebecca C Rossom 5, Ingrid A Binswanger 6, Bobbi Jo Yarborough 7, Julia H Arnsten 8, Chinazo O Cunningham 8, Joseph E Glass 1, Mark T Murphy 9, Mohammad Zare 10, Rulin C Hechter 11, Brian Ahmedani 12, Jordan M Braciszewski 12, Viviana E Horigian 13, José Szapocznik 13, Jeffrey H Samet 14, Andrew J Saxon 15, Robert P Schwartz 16, Katharine A Bradley 1
PMCID: PMC7107675  NIHMSID: NIHMS1568657  PMID: 32220410

Abstract

Background:

The United States is in the middle of an opioid overdose epidemic, and experts are calling for improved detection of opioid use disorders (OUDs) and treatment with buprenorphine or extended release (XR) injectable naltrexone which can be prescribed in general medical settings. To better understand the magnitude of opportunities for treatment among primary care (PC) patients, we estimated the prevalence of documented OUD and medication treatment of OUD among PC patients.

Methods:

This cross-sectional study included patients with ≥ 2 visits to PC clinics across 6 health care delivery systems who were ≥16 years of age during the study period (fiscal years 2014–2016). Diagnoses, prescriptions, and healthcare utilization were ascertained from electronic health records and insurance claims (5 systems which also offer health insurance). Documented OUDs were defined as ≥ 1 International Classification of Diseases code for OUDs (active or remission), and OUD treatment was defined as ≥ 1 prescription(s) for buprenorphine formulations indicated for OUD or naltrexone XR, during the 3-year study period. The prevalence of documented OUD and treatment (95% confidence intervals) across health systems were estimated, and characteristics of patients by treatment status were compared. Prevalence of OUD and OUD treatment were adjusted for age, gender, and race/ethnicity. Combined results were also adjusted for site.

Result:

Among 1,403,327 eligible PC patients, 54–62% were female and mean age ranged from 4651 years across health systems. The 3-year prevalence of documented OUD ranged from 0.7–1.4% across the health systems. Among patients with documented OUD, the prevalence of medication treatment (primarily buprenorphine) varied across health systems: 3%, 12%, 16%, 20%, 22%, and 36%.

Conclusion:

The prevalence of documented OUD and OUD treatment among PC patients varied widely across health systems. The majority of PC patients with OUD did not have evidence of treatment with buprenorphine or naltrexone XR, highlighting the opportunities for improved identification and treatment in medical settings. These results can inform initiatives aimed at improving treatment of OUD in PC. Future research should focus on why there is variation and how much of the variation can be addressed by improving access to medication treatment.

Keywords: opioid use disorder, buprenorphine, naltrexone, treatment, addiction, primary care

1. INTRODUCTION

The nation’s opioid crisis includes problematic patterns of opioid use leading to clinically significant impairment or distress (opioid use disorder – OUD) in some patients. Over 2 million persons in the US currently are known to suffer from OUD (Substance Abuse and Mental Health Services Administration, 2019a), and there were nearly 48,000 opioid overdose deaths in 2017 (Center for Disease Control and Prevention, 2019). Despite declines in prescription opioid use, the prevalence of OUD continues to increase, in part due to use of illicit opioids (Saha et al., 2016). Leaders across the US are calling for improvements in the ability to identify individuals with OUD, and in delivering effective prevention and treatment (Collins, Koroshetz, & Volkow, 2018; Hudson & Collins, 2017; Substance Abuse and Mental Health Services Administration, 2018). Many believe that the relatively high prevalence of OUD, and US federal regulations requiring methadone treatment to be provided solely in specialized opioid treatment programs (OTPs) indicate that the majority of patients with OUDs will need to be treated in medical settings, particularly in primary care (PC). However, the extent of the need for treatment in PC patients is not well quantified.

US general population data from the 2018 National Survey on Drug Use and Health (NSDUH) indicate that 0.8% of adults meet DSM-IV criteria for OUD in the past year (National Survey on Drug Use and Health, 2018). It is unclear if applying DSM-5 criteria would result in an increase in prevalence (Substance Abuse and Mental Health Services Administration, 2016). However, data from the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) survey conducted in 2012–2013 indicate that the prevalence of DSM-5 prescription OUD alone was 0.9% (Saha et al., 2016). The prevalence of OUD is likely higher in patients seen in PC, where opioids are commonly prescribed (Levy, Paulozzi, Mack, & Jones, 2015; Nataraj, Zhang, Guy, & Losby, 2019). The published studies that used diagnostic interviews to determine the prevalence of OUD in PC are limited by small sample sizes, lack of geographic diversity, or are restricted to patients on prescription opioids for chronic pain (Boscarino et al., 2010; Fleming, Balousek, Klessig, Mundt, & Brown, 2007; McNeely et al., 2016). Studies that use automated heath data to estimate the prevalence of OUD and OUD treatment in general medical settings included insured populations that were not restricted to PC (e.g. samples covered by Medicare, the Veterans Health Administration, or commercial insurance) (Dufour et al., 2014; Morgan, Schackman, Leff, Linas, & Walley, 2018).

Many experts advocate that PC-based treatment models will be critical to expanding access to treatment of OUD (Korthuis et al., 2017; Lagisetty et al., 2017). OUD due to prescription opioid medications constitute over 80% of OUD in the US (2005–2013) (Wu, Zhu, & Swartz, 2016), and many patients experience poor outcomes without medication treatment of OUD (Weiss et al., 2011). Of the three FDA-approved medications to treat OUD, two can be prescribed in general medical settings including mental health and primary care—buprenorphine, a partial mu-opioid agonist, and naltrexone, a mu-opioid antagonist. Oral naltrexone was not demonstrated to be efficacious for OUD due to poor patient adherence (Minozzi et al., 2011). An extended-release (XR) injectable formulation of naltrexone is approved for the prevention of OUD relapse, but its initiation is challenging even in residential drug use disorder treatment programs (Lee et al., 2018). Another effective medication treatment for OUD, methadone, can only be provided in specialized OTPs, limited to approximately 1,300 federally approved locations (Substance Abuse and Mental Health Services Administration, 2019b). Due to greater potential availability through physician offices, its superior safety profile to methadone (Ducharme, Fraser, & Gill, 2012; Saxon, Hser, Woody, & Ling, 2013), and its equivalent effectiveness in suppressing illicit opioid use (Mattick, Breen, Kimber, & Davoli, 2014), buprenorphine has the potential to bring effective treatment to the greatest number of individuals with OUD including reducing risk of all-cause and overdose mortality (Dunlap & Cifu, 2016; Sordo et al., 2017). Observational studies report that OUD treatment with medications is associated with decreases in illicit opioid use, increases in abstinence, and improvements in health status and survival compared to behavioral treatments alone (Evans et al., 2015; Mattick et al., 2014; Pierce et al., 2016; Saxon et al., 2013; Sordo et al., 2017). Persistent buprenorphine treatment for 12 months is associated with decreased emergency department (ED) visits, hospitalizations, and deaths (Lo-Ciganic et al., 2015). Nevertheless, a study using 2005–2013 NSDUH data reported that less than 1 in 5 persons with OUD receive medication treatment (Wu et al., 2016). However, this estimate is self-reported data from the general population.

Using data from electronic health records (EHR) and insurance claims data, we estimated the three-year prevalence of documented OUD diagnoses and, OUD treatment with buprenorphine or naltrexone XR in a large sample of PC patients at six geographically diverse health systems in the US during fiscal years (FYs) 2014–2016 (Oct 1, 2013 – September 30, 2016). This information can be used to inform initiatives and interventions aimed at improving treatment of OUD in PC patients.

2. METHODS

2.1. Setting and Population

This cross-sectional study resulted from a feasibility test as a prelude to a National Institute on Drug Abuse (NIDA) Clinical Trials Network (CTN) pragmatic implementation trial to improve treatment of OUDs in PC—the Primary Care Opioid Use Disorders (PROUD) trial. Eleven health systems participated in this feasibility phase of the project. The six health systems that provided data necessary for the present study include Kaiser Permanente of Washington, Kaiser Permanente Northwest (Oregon), Kaiser Permanente Northern California, Kaiser Permanente Colorado, HealthPartners (Minnesota), and Multicare (Washington). All six health systems use the Epic EHR system. Five of the sites were integrated delivery systems (4 Kaiser Permanente and HealthPartners) that provide comprehensive medical care and provide health insurance; as a result, they receive claims from care delivered in external facilities. The number of individuals covered across these 5 health systems is approximately 7 million. The sixth site (Multicare) is a community health care system serving approximately 880,000 individuals in Washington state. It provides all levels of care including inpatient, primary care, mental health, and pharmacy services. As with the other health systems, the EHR data are linkable across these settings and included in this study.

This study sample included patients with ≥ 2 visits to PC clinics who were ≥16 years of age during FY 2014–2016. Four health systems included patients seen in any of their PC clinics, one health system included patients seen in five of their large PC clinics (≥ 20,000 patients per clinic), and another health system included patients seen in PC clinics that were not close to or co-located with addiction treatment services. The range was 5–25 PC clinics per health system.

2.2. Data Collection

Data on patient demographics, diagnoses, medication use, procedures, and health care utilization from all settings (e.g., outpatient, inpatient, urgent care, and ED) were ascertained for all eligible PC patients from each health systems’ EHR and claims during the 3-year study period. Outpatient medication use was determined from pharmacy dispensings for the five integrated delivery systems. Medication orders were used for the community health care system.

2.3. Measures

Documented OUD was defined as ≥ 1 International Classification of Diseases, 9th and 10th Revision, Clinical Modification (ICD-9 and ICD-10) code for OUD (active or remission) in the EHR or claims data from any setting during the study period.

OUD treatment was defined as ≥ 1 medication order(s), dispensing(s), or procedure code(s) for buprenorphine (sublingual, implant, extended-release subcutaneous injection) or injectable naltrexone XR in the ambulatory care settings (e.g., primary care and specialty care, including chemical dependency treatment). Among patients treated, we estimate in exploratory analyses the proportion with > 6 prescriptions (dispensing or order) or procedure codes for buprenorphine or injectable naltrexone XR. Retention in treatment for 6+ months is a common outcome in studies of buprenorphine treatment for OUD (Hsu, Marsteller, Kachur, & Fingerhood, 2019; Saloner, Daubresse, & Caleb Alexander, 2017; Timko, Schultz, Cucciare, Vittorio, & Garrison-Diehn, 2016). Greater than 6 prescriptions or procedure codes (to identify injections) was chosen as a proxy for, at a minimum, regular use and, often use for at least 6-months. Oral naltrexone and methadone were not included. Oral naltrexone is primarily used for alcohol use disorder and has low efficacy for treatment of OUDs (Barocas et al., 2018). Use of methadone for OUD is limited to licensed OTPs and not permitted in medical settings without federal and state approval as an OTP or a medication unit of an OTP. None of the 6 health systems had internal methadone OTPs, and internal methadone prescriptions were assumed to be for treatment of pain.

Other medical conditions (e.g., mental health conditions, alcohol use disorder, tobacco use disorder, non-OUD substance use disorders (SUD) and opioid-related non-fatal and fatal overdose were defined using ICD codes (in-hospital deaths for all sites plus vital records for 5 sites). The Charlson Co-morbidity Index (categorized as 0, 1, 2+) was calculated as a measure of overall comorbidity (Sundararajan et al., 2004). Hospitalizations and ED visits, including urgent care, were categorized as 0, 1, 2, and ≥ 3 during the 3-year study period. Insurance status was determined at cohort entry.

2.4. Analyses

Descriptive statistics were used to characterize the sample overall and by health system. The denominator for the prevalence estimates was all eligible subjects for OUD and subjects with documented OUD for OUD medication treatment. Logistic regression models for each of the binary OUD and treatment measures defined above were fitted that included a categorical variable for the health care system and adjusted for age in FY 2014, gender, and race/ethnicity. From the models, marginal predictions (and 95% Confidence Intervals) assuming the same covariate distribution across health care systems were calculated to describe the adjusted prevalence per person over 3-years of each outcome (Basu & Rathouz, 2005). A similar approach, adjusted for health system, was taken to compare patients with and without OUD treatment. We did not require an OUD diagnosis in the treatment group for this model because the majority of patients (91%) treated with buprenorphine or naltrexone XR had a documented OUD diagnosis. Due to missing data, site A was excluded from analyses of insurance type and ED visits.

The study was approved by the Kaiser Permanente Washington Institutional Review Board (IRB), and other sites ceded to the Kaiser Permanente Washington IRB.

3. RESULTS

3.1. Patient Characteristics

Across the 6 health systems, there were 1,403,327 eligible patients seen in PC over the 3-year study period. The average age in FY 2014 across the health plans ranged from 46–51 years, and 54–62% were female (Table 1). Patient characteristics varied across the health plans: 43–79% Caucasian and 3–22% insured through Medicaid and 21–29% through Medicare. The prevalence of SUDs other than OUD ranged from 3–5% for alcohol, 11–24% for nicotine, and 2–4% for other non-opioid substances. Mental health conditions varied from 25 to 39%. The majority of patients (72–98% across health plans) had a comorbidity index of zero, and a small proportion (2–11%) had an index of ≥2. Additional details on patient characteristics overall and by health system are in Table 1.

Table 1.

Characteristics of primary care patients seen in the six health care systems, 2014–2016 fiscal years

Health Care System
All sites A B C D E F
N=1,403,327 N=423,324 N=24,382 N=351,948 N=288,257 N=280,999 N=34,417
Mean (SD) age in fiscal year 2014, years 49 (18) 48 (18) 51 (18) 47 (18) 50 (18) 50 (18) 46 (18)
Age in fiscal year 2014, years %
 16–17 2.5 2.5 2.7 2.5 2.8 2.1 2.4
 18–25 10.0 10.3 8.3 11.2 8.6 9.5 13.1
 26–35 15.5 16.4 11.7 17.9 13.1 13.6 17.8
 36–45 15.7 16.0 14.8 16.6 15.6 14.1 16.1
 46–55 18.2 19.1 17.8 17.7 17.8 17.7 20.3
 56–65 19.1 18.6 22.8 16.5 20.4 21.6 16.2
 66–75 11.7 10.3 14.5 10.7 13.9 13.0 9.0
 >75 7.3 6.8 7.4 7.0 7.8 8.5 5.1
Female 56.8 56.0 63.9 54.2 56.8 59.8 62.3
Race/Ethnicity
 Caucasian 68.4 78.4 76.0 43.2 79.4 72.9 69.5
 Non-Caucasian 29.0 20.1 20.4 53.0 18.2 24.1 29.7
 Unknown 2.6 1.6 3.6 3.8 2.4 3.0 0.8
Insurance type at study entry
 Medicare 24.4 NA 28.6 21.2 26.8 26.0 21.8
 Commercial 68.2 65.2 74.1 66.6 64.2 56.1
 Medicaid/State Subsidized 5.4 4.7 2.9 5.5 6.2 22.1
 Uninsured 2.0 1.5 1.8 1.1 3.5 0.0
During 3-year study period
%
Charlson co-morbidity index
 0 95.8 97.6 96.4 96.5 95.5 95.5 71.8
 1 1.0 0.7 0.7 0.4 0.6 0.7 17.2
 2+ 3.2 1.7 2.8 3.1 3.9 3.8 10.9
 
Opioid overdose 0.1 0.06 0.11 0.06 0.14 0.08 0.09
1+ mental health conditions* 33.3 34.0 36.9 24.7 38.7 36.8 35.3
Nicotine Use Disorder 16.0 11.5 17.4 14.4 24.3 15.9 19.6
Alcohol Use Disorder 3.7 3.7 2.9 2.7 4.2 4.8 3.1
Other non-opioid substance use disorders 2.6 2.5 2.0 2.0 2.9 3.1 3.6
 Cannabis 1.2 1.0 1.0 0.9 1.4 1.6 2.0
 Stimulant 0.7 0.6 0.4 0.6 0.8 0.6 1.1
 Other 1.4 1.6 1.1 1.1 1.4 1.6 1.4
Emergency department visits
 0 67.1 NA 60.5 63.7 63.1 76.8 61.5
 1 17.7 22.0 20.1 19.4 12.7 18.0
 2 6.9 8.3 7.5 7.7 5.1 7.9
 3+ 8.2 9.2 8.7 9.8 5.4 12.7
Number of hospitalizations
 0 86.1 88.3 82.6 86.5 83.8 85.0 84.5
 1 8.5 4.8 11.5 9.2 10.8 10.0 10.7
 2 2.9 3.2 3.5 2.5 3.1 3.0 2.8
 3+ 2.5 3.7 2.4 1.8 2.3 2.0 2.0
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*

Includes depression, anxiety, bipolar disorder, schizophrenia

3.2. Opioid use disorder, OUD treatment, and opioid-related overdose

Among PC patients, the adjusted prevalence of OUD varied from 0.7% to 1.4% across health systems during the 3-year study period (Table 2). Among PC patients with an OUD diagnosis, the proportion treated with buprenorphine or naltrexone XR ranged from 3–36% across the health systems. Twenty-eight to 75% of those treated with buprenorphine or naltrexone XR had >6 prescriptions or injections. The majority of medication treatment was with buprenorphine and there was little use of naltrexone XR. Across health systems, the prevalence of fatal and non-fatal opioid overdose ranged from 0.06–0.14% of PC patients.

Table 2.

Documented opioid use disorder (OUD) and OUD treatment with buprenorphine or injectable extended release (XR) naltrexone among primary care patients across six health care systems, 2014–2016 fiscal years

Health Care System
A B C D E F
N=423,324 N=24,382 N=351,948 N=288,257 N=280,999 N=34,417
% (95% Confidence Interval)
Prevalence1 of ≥1 OUD diagnosis code(s) in PC Patients during the 3 Year Study
Active and/or Remission 0.7 (0.7, 0.8) 0.8 (0.7, 0.9) 0.8 (0.7, 0.8) 1.3 (1.2, 1.3) 1.4 (1.3, 1.4) 1.1 (1.0, 1.2)
 Active 0.7 (0.7, 0.7) 0.8 (0.7, 0.9) 0.7 (0.7, 0.7) 1.2 (1.1, 1.2) 1.3 (1.2, 1.3) 1.1 (1.0, 1.2)
 Remission 0.1 (0.1, 0.2) 0.1 (0.1, 0.2) 0.3 (0.2, 0.3) 0.5 (0.4, 0.5) 0.3 (0.3, 0.3) 0.1 (0.1, 0.1)
Prevalence1 of Medication treatment of OUD among PC Patients with Documented OUDs During the 3 Year Study
N=3464 N=194 N=2172 N=3860 N=3876 N=414
% (95% Confidence Interval)
Buprenorphine or naltrexone XR 3.1 (2.6, 3.7) 16.4 (11.3, 21.6) 22.3 (20.5, 24.0) 36.3 (34.9, 37.8) 19.6 (18.4, 20.8) 12.5 (9.4, 15.6)
 Among those with treatment, >6 prescriptions or injections 28.5 (20.4, 36.7) 52.3 (34.7, 69.9) 72.7 (68.7, 76.7) 75.1 (72.9, 77.2) 71.9 (68.6, 75.1) 62.7 (50, 75.4)
Buprenorphine 3.1 (2.5, 3.7) 15.9 (10.8, 21.0) 21.6 (19.9, 23.4) 35.8 (34.4, 37.2) 19.1 (17.9, 20.4) 9.7 (7.0, 12.5)
Naltrexone XR 0.1 (0, 0.2) 0.6 (0, 1.7) 1.0 (0.5, 1.4) 1.9 (1.4, 2.3) 0.8 (0.5, 1.1) 3.0 (1.4, 4.6)
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1

Adjusted for differences in age, gender, and race/ethnicity across the health care systems

3.3. Patient characteristics by OUD treatment

Table 3 shows patient characteristics at sample entry as well as health care utilization during the three-year study period by treatment with or without buprenorphine or naltrexone XR.

Table 3.

Characteristics of primary care patients by buprenorphine and injectable extended release naltrexone treatment status during fiscal years 2014–2016, across 6 health care systems

OUD and no Buprenorphine or Naltrexone XR Buprenorphine or Naltrexone XR with or without an OUD diagnosis p-value
N=11,106 N=3,172
% (95% Confidence Interval)1
Age in fiscal year 2014
 16–17 1.4 (1.2, 1.7) 1.1 (0.7, 1.4) <0.0001
 18–25 11.9 (11.3, 12.5) 25.7 (24.1, 27.3)
 26–35 18.6 (17.8, 19.3) 26.3 (24.7, 28.0)
 36–45 16 (15.3, 16.7) 19.4 (17.9, 20.8)
 46–55 20.6 (19.9, 21.4) 15.6 (14.3, 16.9)
 56–65 19.0 (18.3, 19.8) 9.1 (8.1, 10.1)
 65–75 8.0 (7.5, 8.5) 2.1 (1.6, 2.6)
 >75 4.4 (4, 4.8) 0.8 (0.5, 1.1)
Female 54.7 (53.7, 55.6) 47.4 (45.6, 49.3) <0.0001
Race/Ethnicity
 Caucasian 77.7 (76.9, 78.5) 81.8 (80.4, 83.2) <0.0001
 Non-Caucasian 20.2 (19.5, 21.0) 16.4 (15, 17.7)
 Unknown 2 (1.8, 2.3) 1.9 (1.4, 2.3)
Insurance at study entry2
 Medicare 23.7 (23, 24.4) 18.4 (17, 19.8) <0.0001
 Commercial 55.6 (54.6, 56.6) 66.2 (64.6, 67.9)
 Medicaid/State Subsidized 17.6 (16.8, 18.5) 13.0 (11.9, 14.1)
 Uninsured 3.1 (2.7, 3.5) 2.4 (1.9, 3.0)
Charlson co-morbidity index
 0 91.2 (90.7, 91.7) 95.3 (94.4, 96.1) <0.0001
 1 1.7 (1.5, 2.0) 1.1 (0.7, 1.5)
 2+ 7.1 (6.6, 7.5) 3.6 (2.9, 4.4)
Opioid overdose 3.6 (3.2, 4.0) 3.9 (3.2, 4.6) 0.48
1+ mental health conditions3 80.2 (79.4, 80.9) 76.3 (74.8, 77.8) <0.0001
Nicotine Use Disorder 60.3 (59.4, 61.2) 58.8 (57, 60.6) 0.16
Alcohol Use Disorder 28.8 (27.9, 29.6) 29.1 (27.4, 30.7) 0.74
1+ other substance use disorders 52.4 (51.5, 53.3) 54.3 (52.6, 56.1) 0.06
 Cannabis 17.2 (16.5, 17.9) 16.8 (15.6, 18) 0.60
 Stimulant 17.8 (17.1, 18.5) 19.7 (18.4, 21) 0.02
 Other non-opioid substance 43.4 (42.5, 44.4) 46.9 (45.1, 48.7) 0.001
Emergency Department visits2
 0 31.7 (30.7, 32.7) 41.0 (39.2, 42.7) <0.0001
 1 16.4 (15.6, 17.3) 18.7 (17.2, 20.1)
 2 11.6 (10.9, 12.3) 11.5 (10.3, 12.7)
 3+ 40.3 (39.2, 41.4) 28.9 (27.2, 30.5)
Number of hospitalizations
 0 61.2 (60.3, 62.1) 69.6 (68.1, 71.2) <0.0001
 1 16.6 (15.9, 17.3) 14.6 (13.3, 15.8)
 2 8.3 (7.8, 8.8) 6.2 (5.3, 7)
 3+ 13.9 (13.3, 14.6) 9.6 (8.5, 10.7)
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1

Adjusted for differences in age, gender, health care system, and race/ethnicity

2

Site A not included due to missing insurance type and emergency department visits.

3

Includes depression, anxiety, bipolar disorder, schizophrenia Abbreviations: XR – extended release

Compared to patients who did not receive these treatments, treated patients were younger and more likely to be male, Caucasian, commercially insured, and have certain other non-opioid SUDs (Table 3). Compared to patients who were not treated, treated patients appeared to have lower comorbidity (Charlson co-morbidity index), fewer mental health conditions, and fewer ED visits and inpatient stays.

4. DISCUSSION

This large cross-sectional study of ~1.4 million PC patients from six large US health systems across 5 states provides novel information on the prevalence (0.7–1.4%) of documented OUD and the wide variation in treatment of OUD with buprenorphine or naltrexone XR (3–36%) in a real-world PC sample. Among patients treated with these medications, the proportion who received >6 prescriptions or injections also varied substantially across health systems (28–75%). While the sample was drawn from the PC setting, diagnoses and treatment are reflective of all care captured within the health systems or from claims for outside services. Standards of care in several health systems required that treatment of OUD be in specialty addiction treatment programs and did not therefore treat OUD in PC at the time of this study. The divergent prevalence of OUD and OUD treatment across health systems are likely due to a variety of factors that include differences in screening and diagnosis practices, geographic variation in underlying patient demographics and prevalence of OUD, and availability of integrated specialty addiction treatment programs or external OTPs. They also likely reflect differences in number of providers who are waivered and willing to treat, and the availability of medication treatment for OUDs within the health system. Regardless, these results highlight the opportunities for improvement in the diagnosis and treatment of OUD in PC patients. In this same population, we observed that medication treatment of OUD was lower among patients who were older, female, Black/African American and Hispanic (compared to Caucasian), noncommercially insured, and patients with non-cancer pain, mental health disorders, and more comorbidity (Lapham et al., 2020).

The true prevalence of OUD in PC patients may be higher than our estimates of documented OUD in the EHR and claims (Barocas et al., 2018). Reasons may include: 1) patients who have OUD may have fewer medical visits; 2) patients may be reluctant to report symptoms of OUD due to stigma, fear of the impact on health or life insurance, or because they do not want their provider to discontinue their opioids; and 3) physicians may not assess or document OUD.

Our 3-year prevalence rates of documented OUD in PC were higher than most other studies in the general population that used electronic health data to determine 1-year prevalence of OUD. For example, the 1-year prevalence of documented OUD was 0.8% in 2010 among patients in the Veterans Health Administration, 0.30%–0.65% during 2008–2010 among Medicare patients, and 0.3% in 2015 and 0.12%–0.48% during 2010–2014 in two commercially insured populations (Dufour et al., 2014; Morgan et al., 2018; Oliva, Trafton, Harris, & Gordon, 2013; Thomas et al., 2018). In these same studies and other studies of Medicare and commercially insured populations (Donohue et al., 2018; Lembke & Chen, 2016; Wu et al., 2016), rates of OUD treatment with medications among patients with OUD varied from 16% to 39% which were similar to rates we observed in some of the health systems. In a large population of commercially insured adults with OUD, rates of medication treatment decreased from 25% in 2010 to 16% in 2014 while documented OUD increased during the same period (Morgan et al., 2018). There was suggestion of a similar trend in a second commercially insured population study where treatment rates declined from 27% in 2014 to 25% in 2015 (Thomas et al., 2018). In the Veterans Administration, medication treatment of OUDs remained stable to slightly increasing from 25% to 27% during 2004 to 2010 but patients diagnosed with OUD increased by 45% (Oliva et al., 2013). However, increases in OUD treatment over time with buprenorphine were reported in other studies including one in a Medicaid population (10% in 2007 to 25% in 2012) (Gordon et al., 2015) and another from the National Ambulatory Medical Care Surveys (56% treated in 2006–2010 to 74% in 2011–2015) (Rhee & Rosenheck, 2019).

Disparities in medication treatment of OUD in PC samples may exist but more research is needed. Our data are consistent with some other reports that patients undergoing buprenorphine treatment for OUD are more likely to be younger and Caucasian than non-treated patients with OUD (Cantone et al., 2019; Manhapra, Stefanovics, & Rosenheck, 2019). However, other studies report older age and female gender to be associated with medication treatment for OUD (Neighbors et al., 2019; Ober et al., 2018). Other studies do not evaluate a co-morbidity index as we did in this study but findings on the association between co-morbidities and medication treatment of OUD are conflicting and vary depending on the specific comorbidity (Cantone et al., 2019; Rieckmann et al., 2016).

Models to increase the diagnosis and treatment of OUD in PC are evolving (Korthuis et al., 2017), but there are many barriers to the provision of OUD treatment in US medical settings. These barriers include financial (uninsured or underinsured), regulatory (specialized training requirements, limits on the number of patients treated by a provider) (Health and Human Services Department, 2016), attitudinal (not wanting to treat patients with OUD, not wanting to treat with opioid agonists), clinical difficulty (initiation of buprenorphine or naltrexone XR), time during brief PC visits (managing comorbid conditions as well as early treatment of OUDs), and geographic (poor distribution of waivered providers) (Hutchinson, Catlin, Andrilla, Baldwin, & Rosenblatt, 2014; Sharma et al., 2017; Tofighi et al., 2019). Barriers can likely be overcome but work is needed to engage health care systems in order to bring treatment to scale in the US.

4.1. Limitations

This multi-site study to estimate the prevalence of documented OUD and OUD treatment across 6 health systems is a critical step for understanding the unmet treatment needs in PC patients. The study is, however, not without limitations. There is potential misclassification of OUD and/or OUD treatment. Defining OUD with diagnosis codes can result in misclassification in either direction (e.g., missed OUD due to underdiagnosis and/or under-coding or over-diagnosis due to incorrect coding of opioid physical dependence or withdrawal as OUD). Some patients may be using buprenorphine for symptom management during an opioid taper instead of for OUD treatment. Medications ordered outside the community health system site are not captured in the data, and medications dispensed outside pharmacies owned by the 5 health systems that are insurers where no claim was submitted (e.g., self-pay) are not captured in the data. The use of >6 prescriptions and/or procedures as a proxy for regular use of medications for OUD does not necessarily indicate continuous treatment. Some patients were likely receiving methadone or inpatient treatment which were not included in the analyses. In general, health care utilization is near complete for the 5 sites that receive claims for outside services and the non-integrated delivery system site reports providing comprehensive care to the majority of its patients. Based on clinical experience, patients (especially the commercially insured) may be more likely to seek substance use services outside of the insurance system than for other diseases due to fears of stigma, loss of insurance coverage, and loss of employment. This is a cross-sectional study, and we cannot make conclusions about temporality of OUD, OUD treatment, or patient characteristics. Finally, the study may not be generalizable to other PC samples. However, integrated delivery systems such as Kaiser Permanente and Health Partners are strongly represented in the US among insured individuals; 20% of the US population is enrolled in a managed care plan (National Conference of State Legislatures, 2017). These sites are excellent settings for conducting research because of high-quality data, a diverse population base that represents the underlying community, and a large population with access to comprehensive medical care, where researchers have detailed and unbiased access through EHR and claims data to information on diagnoses and medication use.

5. CONCLUSION

Based on electronic health system data, we identified high variability in the prevalence of documented OUD and receipt of treatment with buprenorphine and naltrexone XR in PC patients. While not all patients with OUD should be treated with buprenorphine or naltrexone XR, further work is needed to understand reasons for the variability and improve treatment access and retention. Replication of our study in other PC populations will be informative in further quantifying the magnitude of treatment opportunities in PC patients. Significant health system-level changes in this area are warranted. Future research should aim to increase recognition of OUD and improve penetration of evidence-based medication treatment of OUD. This includes PC-based models for the treatment of OUD (Korthuis et al., 2017), such as the one being tested in the NIDA CTN funded PROUD trial to evaluate whether implementation of the Massachusetts Model of collaborative care for management of OUDs in PC increases OUD treatment with buprenorphine or naltrexone XR, compared to usual PC (Alford et al., 2011; LaBelle, Han, Bergeron, & Samet, 2016).

Highlights.

  • The 3-year prevalence of opioid use disorder in primary care patients was 0.7–1.4% across 6 health systems.

  • Treatment of OUD with buprenorphine or extended-release naltrexone varied greatly across health systems: 3% – 36%.

  • Future research should focus on why there is variation and how to improve access to medication treatment for OUD.

Acknowledgments

Funding: Research reported in this publication was supported by the National Institute on Drug Abuse of the National Institutes of Health under Award Numbers UG1DA040314, U10DA013714, UG1DA013035, UG1DA013034, U10DA13720, UG1DA040316, HHSN271201400028C, UG1DA015831. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

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