Sage Journals: Discover world-class research

Abstract

Substance use disorders (SUD) remain a significant source of morbidity and mortality in the United States, and access to treatment continues to be inadequate. Primary Care Clinicians (PCCs) are well-positioned to provide long-term SUD care for patients. However, multiple provider-level barriers exist. Collaborative Care Management (CoCM) has proven successful in supporting PCCs in treating psychiatric conditions, such as depression. Our group proposes an addiction-focused modified CoCM that leverages telemedicine and an electronic platform (Senyo) into primary care. This study assesses PCCs’ attitudes toward this proposed model and their likelihood (with support) of prescribing medications for alcohol and opioid use disorder. To achieve this, an anonymized and confidential electronic survey was deployed to all 489 of our institutions’ PCCs. Eighty-five completed the survey (17.4% response); the majority (94%) agreed that digital CoCM for SUD will be helpful for their practice, and 85% expressed agreement that such a model will increase their confidence and likelihood to prescribe anti-craving medications. Additionally, we found that PCCs’ comfort level in addressing SUD with patients is not associated with years in practice, clinician type (attending physicians, resident/fellow physicians, nurse practitioner or physician assistant), or their perception of currently available SUD treatment resources. Future work to evaluate practice changes, including rates of anti-craving medication prescribing and SUD-treatment outcomes after implementation of our digital CoCM will prove useful in determining the effectiveness of this model.

Keywords

mobile application substance use disorders addiction primary care collaborative care medications for opioid use disorder (MOUD)medications for alcohol use disorder (MAUD)

Background

With an estimated 16.8% of individuals in the United States 12 years and older having a substance use disorder (SUD) in 2024,¹ and 1 in 10 adults reporting illicit opioid use in the past year,² there is an urgent need to expand access to SUD treatment. A mere 20% of those needing SUD treatment received services in 2024.¹ Integrating SUD treatment into primary care has been demonstrated to be cost-effective and efficacious.^3-5 Primary care clinicians (PCC) are uniquely positioned to provide the continuity of care needed to optimize long-term outcomes,⁶ while simultaneously addressing other healthcare needs, including preventive services and chronic disease management.⁷ Despite the potential benefits, widespread provider-level barriers exist, including inadequate knowledge and mentorship, limited behavioral health resources and institutional support, and administrative challenges.^8-12

Collaborative care management (CoCM), in which behavioral health care managers are integrated into primary care practices with the oversight of consultant psychiatrists to support PCCs in managing patients with mental health conditions, has become the standard of care in a growing number of healthcare systems.¹³ Our institution incorporated CoCM into primary care nearly 2 decades ago,¹⁴ which has led to improved behavioral health access and depression treatment outcomes.^15-17 Similar CoCM models have been employed elsewhere for SUD with promising results.^18-20

Our group recently proposed integrating digital CoCM for SUD in primary care, which leverages telemedicine capabilities that became commonplace during the Covid-19 pandemic. The goal is to expand access to those with logistical or geographical barriers to in-person care.²¹ This model utilizes a mobile phone application, Senyo, developed by our group.^22,23 This platform incorporates modules based on contingency management, behavioral activation and cognitive behavioral therapy, while providing patients with direct support from a licensed alcohol and drug counselor (LADC), who also functions as the care coordinator.²⁴ Over the 12-week intervention, the LADC meets with patients weekly via video visits and maintains ongoing communication through the mobile phone application, sending modules to complete, offering reassurance and answering questions. All care is provided under the supervision of an addiction psychiatrist. PCCs would receive updates and recommendations to prescribe medications for addiction treatment (eg, buprenorphine for OUD or acamprosate for alcohol use disorder, AUD, which are considered the gold standard for these conditions),^25,26 if indicated. Additional details related to our CoCM workflow, the Senyo mobile app, and care team membership was previously published by our group.²³

The sustainable implementation of this digital CoCM model depends on PCCs’ willingness to engage patients in SUD treatment. Although the intervention provides structured support, PCCs will remain the point of contact for prescribing medications and coordinating care, consistent with CoCM. Assessing PCCs’ attitudes and comfort level is critical to refining this model and ensuring its feasibility. To inform the implementation of digital CoCM for SUD in primary care, we designed and deployed an anonymized and confidential electronic survey to assess PCCs’ views within our institution.

Methods

Study Setting

Our institution’s PCCs work in the Departments of Community Internal Medicine, Family Medicine, and Community Pediatrics and Adolescent Medicine across 8 outpatient clinics and 2 express care clinics in Rochester and Kasson, Minnesota. There are 257 providers (physicians, nurse practitioners [NP] and physician assistants [PA]), 159 Internal Medicine Residents, 27 Family Medicine Residents and 46 Pediatric Residents.

This study was deemed exempt for Institutional Review Board (IRB) ethical review by our institution in accordance with the Code of Federal Regulations, 45 CFR 46.102.

Survey Content, Design, and Deployment

Our survey consisted of 9 questions (see Supplemental Material); the first 4 questions were on demographics, including specialty, type of clinician (staff physician, advanced practice providers, or residents/fellows), geographic region of practice, and years in practice since completing residency training or NP/PA school. Questions 5 to 8 ask respondents to rate their attitudes toward currently available resources for SUD treatment, comfort level in SUD treatment if a digital CoCM were to be in place, and their comfort level in discussing SUD treatment with patients when compared to other chronic medical conditions such as hypertension and diabetes. Responses to these questions were scored on a 5-point Likert scale (“strongly agree,” “somewhat agree,” “neither agree nor disagree,” “somewhat disagree,” and “strongly disagree”). The final question is open-ended to elicit additional comments about SUD treatment support and resources for PCCs.

To ensure optimal anonymity, our survey did not ask respondents to provide demographic details, such as identified gender, race/ethnicity, and age.

Qualtrics was used to build and deploy the anonymized, confidential electronic survey. To ensure respondent anonymity, Internet Protocol (IP) address collection was disabled. Four physician participants pilot-tested the survey, and feedback on language and content was incorporated into the final version. All participants completed the electronic survey in under 5 min. Survey items were not validated.

After obtaining approval from our department leadership to distribute the survey, it was electronically deployed to 489 PCCs on July 9, 2025, with a 4-week window to complete (July 9-August 6, 2025).

Data Analysis

Demographic data and responses to questions (Questions 4-8) were summarized. Likert-scale responses were treated as ordinal variables. A Kruskal-Wallis test (KW) compared comfort talking about SUD across specialties and types of clinicians. Spearman’s correlations assessed the association between comfort talking and years in practice, satisfaction with SUD resources, finding digital CoCM for SUD helpful, and agreement with the idea that digital CoCM for SUD in primary care will increase their confidence to prescribe anti-craving medications. Additionally, bootstrapping (5000 iterations) provided confidence intervals around Spearman’s correlations.

Results

Demographic Characteristics

Eighty-five respondents completed the survey (85/489; response rate 17.4%), with 45% in Internal Medicine, 43% in Family Medicine, and 12% in Pediatrics. The majority (55%) were physicians. Most respondents were 0 to 10 years into practice (36%), with those between 11 and 22 years in practice (22%) representing the second largest group (Table 1).

Table 1.

Respondent Demographics.

Specialty
Community internal medicine	45% (38)
Family medicine	43% (37)
Community pediatrics and adolescent medicine	12% (10)
Clinician type
Attending physician	55% (47)
Advanced practice provider (nurse practitioner or physician assistant)	28% (24)
Resident or fellow physician	16% (14)
Practice location
Rochester or Kasson, Minnesota	100% (85)
Outside of Rochester or Kasson, Minnesota	0%
Years in practice
Still in training	13% (11)
0-10	36% (31)
11-20	22% (19)
21-30	18% (15)
31+	9% (8)
Retired	1% (1)

With 85 respondents, our study had 79.7% power to detect a Spearman ρ of 0.30, thus providing adequate power to find meaningful correlates.

Current Attitudes and Comfort Level

Almost half of the respondents (49%) expressed disagreement with the statement that “I am satisfied with the level of resources available at [our institution] or in the community related to substance use disorder treatment” (31% “somewhat disagree” and 18% “strongly disagree”), with 16% neither agreeing nor disagreeing with this statement (Figure 1).

Figure 1.

Survey responses.

The degree of agreement/disagreement regarding comfort level in discussing SUD with patients compared to other chronic medical conditions is relatively similar, with 48% agreeing to having an equal comfort level between SUD and other chronic medical conditions and 44% disagreeing (8% neither agree nor disagree; Figure 1).

Attitudes Toward Digital CoCM for SUD in Primary Care

Most respondents (82%) strongly agreed and 12% somewhat agreed that they would find digital CoCM for SUD helpful, with only 1% disagreeing. Furthermore, the majority agreed that a digital CoCM for SUD in primary care will increase their confidence and likelihood to prescribe anti-craving medications (59% strongly agreeing and 26% somewhat agreeing; Figure 1).

Most free-text comments reinforced the strong agreement and enthusiasm of having such a platform in their practice, although several respondents expressed hesitation that such a program may not be adequate or could increase administrative burden (eg, in-basket messages; Table 2).

Table 2.

Free-text Comments from Survey Respondents.

Positive	Patients with alcohol use disorder or opioid use disorder are often not well served within traditional medical practices, including our institution. Yet their issues impact medical comorbidities we are often treating. Having additional resources to refer patients to would greatly aid in the care of these patients. As a primary care clinician, I am dealing with multiple other problems and simply lack the time (and somewhat the training) to effectively provide the ongoing counseling and behavioral therapy necessary to treat these patients. This proposed intervention would be very welcome!
	It would be helpful to know the resources for alcohol abuse that is in the Rochester area.
	Having education or topics that are specifically steered toward being applicable in pediatrics (or adolescents) would be helpful.
	Just thank you for doing this. I think a lot of patients will benefit.
	Please do this!
	Very excited about this possibility, thank you!
	This is a great idea!
Negative	IBH’s (traditional CoCM) tendency to offer brief interventions (rather than an ongoing relationship) may be even more of a problem for SUD than for the other mental health conditions they treat.
	The IBH care coordination model (traditional CoCM) of them charging for the opinion then expecting the primary care clinician to do all the prescribing and communication of the recommendations with the patient continues to be problematic. With all the other non-visit care we are expected to provide in an over-empaneled environment (and) with support staff that have production quotas that generally don’t include helping providers with all this non-visit busy work.
	How available will the service be to clinicians. It is a good idea but if it becomes another source of inbox messages for the clinician, it will not be utilized. So many current practices at our institution add hours to the clinician without obviously improving the clinician’s ability to provide care.
Neutral	Do we have a team that does substance use counseling internally?

Relationship Between Demographic Characteristics and Attitudes Toward Digital CoCM

Neither specialty (KW χ2 = 1.92, df = 2, P > .38) nor type of clinician (KW χ2 = 0.01, df = 2, P > .99) was related to comfort talking about SUD with patients. None of the correlations were significant between comfort talking about SUD with patients and years in practice (r_s = −0.05, P > .62, 95% CI: −0.27 to 0.17), satisfaction with SUD resources (r_s = 0.13, P > .25, 95% CI: −0.09 to 0.34), finding digital CoCM for SUD helpful (r_s = −0.12, P > .26, 95% CI: −0.32 to 0.09), and agreement with a digital CoCM for SUD in primary care will increase confidence (r_s = 0.12, P > .28, 95% CI: −0.10 to 0.35).

Discussion

Findings from our survey study suggest that incorporating digital CoCM for SUD in primary care would be viewed as a welcome addition by PCCs and will increase confidence and likelihood to prescribe anti-craving medications. Most did not feel the current SUD treatment resources were adequate. A similar number of respondents expressed agreement and disagreement regarding comfort level in discussing SUD with patients when compared to other chronic medical conditions (48% agreeing vs 44% disagreeing).

Interestingly, our analysis did not show any association between comfort level and years in practice, clinician type, or perceived adequacy of currently available SUD treatment resources. This is noteworthy because, for OUD, existing literature suggests that inadequate behavioral health and SUD resources are significant barriers to prescribing buprenorphine.^8,12 However, a prior study by our group demonstrated that, at least among PCCs providing care for adolescent patients, having guaranteed access to SUD treatment referral endorsed by and communicated through practice leadership did not lead to changes in addressing and treating SUD, even when patients admitted to using illicit substances.²⁷ Our current analysis seems to support findings from our prior study. Therefore, the availability of behavioral health and addiction resources in the community alone may be insufficient to improve PCCs’ readiness to address SUD.

Other barriers, such as lack of knowledge and time, stigma, and beliefs about the effectiveness of anti-craving medications for AUD and OUD, have been previously cited.^11,28-31 Yet, interventions where support is embedded into PCCs’ workflow (rather than being peripherally available), such as involving pharmacists or nurses to follow-up and co-manage patients with OUD, have led to improved patient outcomes, an increased number of patients prescribed anti-craving medications, as well as provider satisfaction.^32,33 CoCM may be better accepted by PCCs than traditional referrals because they receive regular updates and are able to provide feedback on proposed treatments, thus can actively participate in their patients’ continued care. Indeed, a recent study integrating CoCM for OUD into primary care shows promising results, although the majority of participants in this study were already prescribed anti-craving medications at the time of enrollment.¹⁹ We anticipate that embedding digital CoCM for SUD will yield similar positive patient outcomes while enhancing PCCs’ comfort level in addressing SUD, and with the added benefit of providing access to those with logistical challenges to seek in-person care.

Limitations

Our survey study was limited to PCCs working within a single academic medical center in the upper Midwest. The overall response rate (17.4%) was low, and only 12% of our responses came from pediatric providers. Therefore, findings from our study may not generalize to all PCCs within our institution and those working in other healthcare systems and regions. Those working in more rural and under-resourced settings may face additional barriers, such as unreliable cellular network connections or limited data, which could further complicate the implementation of digital CoCM.

Our respondents were also not asked to specify their clinic location. It is possible that clinician attitudes between clinics differ. Future efforts to evaluate differences in comfort level between clinics could prove helpful when implementing our digital CoCM.

Another limitation is selection bias. Respondents may have more favorable attitudes toward digital CoCM and are more likely to address SUD compared to non-respondents. Future work to more actively engage PCCs within our institution, as well as to those working in other institutions, could provide more comprehensive insight. Work to re-survey PCCs’ comfort level in addressing and treating SUD, anti-craving medication prescribing rates, as well as patient outcomes after the launch of our proposed digital CoCM, will help determine the effectiveness of this model. Plans to include pediatric patients into our digital CoCM are also currently under consideration.

Conclusions

Our study suggests an overall positive attitude from PCCs in having digital CoCM for SUD to support their practice; most respondents expressed increased willingness to prescribe anti-craving medications when such support is available. We also did not find an association between PCCs’ comfort level in addressing SUD and years in practice, and clinician type. Contrary to existing literature, our study did not find an association between comfort level and perceived adequacy of existing treatment resources in the community. Given ongoing barriers to SUD care, integrating digital CoCM into PCCs’ practice could serve as a valuable tool to enhance their confidence in treating SUD and improve access to evidence-based treatment for this patient population.

Supplemental Material

sj-docx-1-inq-10.1177_00469580261440482 – Supplemental material for Primary Care Clinicians’ Attitudes on Digital Care Collaborative Management for Substance Use Disorders

Supplemental material, sj-docx-1-inq-10.1177_00469580261440482 for Primary Care Clinicians’ Attitudes on Digital Care Collaborative Management for Substance Use Disorders by Benjamin Lai, Nicholas L. Bormann, Stephan Arndt, Jamie Smith, Margaret Paul, Cynthia Stoppel, Kelsey Tuen, Danielle Cox, Scott Breitinger, Mark Williams and Tyler S. Oesterle in INQUIRY: The Journal of Health Care Organization, Provision, and Financing

Footnotes

Acknowledgements

Mayo Clinic, Tyler Oesterle MD MPH and Scott Breitinger MD have a financial interest related to this research. This relationship has been reviewed and managed by the Mayo Clinic Conflict of Interest Review Board in compliance with institutional policies.

ORCID iD

Benjamin Lai

Ethical Considerations

The Digital Care Collaborative Management protocol described within the survey was approved by Mayo Clinic’s Institutional Review Board (IRB; Mayo IRB Protocol Number: 24-007758). The anonymized and confidential survey described in this manuscript was deemed exempt from Institutional Review Board ethical review by Mayo Clinic’s IRB in accordance with the Code of Federal Regulations, 45 CFR 46.102.

Consent to Participate

All eligible respondents received information about the study, including its anonymous and confidential nature, estimated completion time, voluntary participation, and minimal risk. Research team contact details were provided. Consent was implied through survey completion, which was appropriate given the minimal risk, absence of vulnerable populations, and anonymous nature of the survey. Collecting signed consent would have increased the risk of participant identification.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Research reported in this publication was supported by the Agency for Healthcare Research and Quality of the National Institutes of Health (award R18HS029774). Additionally, Benjamin Lai, MB BCh BAO receives financial support for research through Mayo Clinic’s Robert D. and Patricia E. Center for the Science of Health Care Delivery.

Declaration of Conflicting Interests

The authors declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: Mayo Clinic, Tyler Oesterle MD MPH and Scott Breitinger MD have a financial interest related to this research. This relationship has been reviewed and managed by the Mayo Clinic Conflict of Interest Review Board in compliance with institutional policies.

Data Availability Statement

The data that supports findings of this study are available on request for the corresponding author on reasonable request.

Trial Registration Number/Date

ClinicalTrials.gov Identifier: NCT024007758 (“Senyo Health With Substance Use Disorder (SUD) in Primary Care”).

Grant Number

R18HS029774.

Supplemental Material

Supplemental material for this article is available online.

References

Key substance use and mental health indicators in the United States: results from the 2024 national survey on drug use and health. Accessed September 17, 2025, https://www.samhsa.gov/data/sites/default/files/reports/rpt56287/2024-nsduh-annual-national-report.pdf

Powell

Jacobson

Estimates of illicit opioid use in the US. JAMA Health Forum. 2025;6(5):e250809. doi:10.1001/jamahealthforum.2025.0809

Buresh

Stern

Rastegar

Treatment of opioid use disorder in primary care. BMJ. 2021;373:n784. doi:10.1136/bmj.n784

Jawa

Tin

Nall

, et al. Estimated clinical outcomes and cost-effectiveness associated with provision of addiction treatment in US primary care clinics. JAMA Netw Open. 2023;6(4):e237888. doi:10.1001/jamanetworkopen.2023.7888

Wakeman

Rigotti

Chang

, et al. Effect of integrating substance use disorder treatment into primary care on inpatient and emergency department utilization. J Gen Intern Med. 2019;34(6):871-877. doi:10.1007/s11606-018-4807-x

McKay

JR.

Impact of continuing care on recovery from substance use disorder. Alcohol Res. 2021;41(1):01. doi:10.35946/arcr.v41.1.01

Samet

Friedmann

Saitz

Benefits of linking primary medical care and substance abuse services: patient, provider, and societal perspectives. Arch Intern Med. 2001;161(1):85-91. doi:10.1001/archinte.161.1.85

Hutchinson

Catlin

Andrilla

Baldwin

Rosenblatt

RA.

Barriers to primary care physicians prescribing buprenorphine. Ann Fam Med. 2014;12(2):128-133. doi:10.1370/afm.1595

Lai

Croghan

Ebbert

JO.

Buprenorphine waiver attitudes among primary care providers. J Prim Care Community Health. 2022;13:21501319221112272. doi:10.1177/21501319221112272

10.

Campopiano von Klimo

Nolan

Corbin

, et al. Physician reluctance to intervene in addiction: a systematic review. JAMA Netw Open. 2024;7(7):e2420837. doi:10.1001/jamanetworkopen.2024.20837

11.

Austin

Chen

Briggs

, et al. Integrating opioid use disorder treatment into primary care settings. JAMA Netw Open. 2023;6(8):e2328627. doi:10.1001/jamanetworkopen.2023.28627

12.

Lanham

Papac

Olmos

, et al. Survey of barriers and facilitators to prescribing buprenorphine and clinician perceptions on the Drug Addiction Treatment Act of 2000 Waiver. JAMA Netw Open. 2022;5(5):e2212419. doi:10.1001/jamanetworkopen.2022.12419

13.

Reist

Petiwala

Latimer

, et al. Collaborative mental health care: a narrative review. Medicine. 2022;101(52):e32554. doi:10.1097/MD.0000000000032554

14.

Angstman

DeJesus

Williams

MD.

Initial implementation of a depression care manager model: an observational study of outpatient utilization in primary care clinics. Popul Health Manag. 2009;12(5):227-230. doi:10.1089/pop.2008.0050

15.

Dejesus

Angstman

Cha

Williams

MD.

Antidepressant medication use among patients with depression: comparison between usual care and collaborative care using care managers. Clin Pract Epidemiol Ment Health. 2013;9:84-87. doi:10.2174/1745017901309010084

16.

Shippee

Shah

Angstman

, et al. Impact of collaborative care for depression on clinical, functional, and work outcomes: a practice-based evaluation. J Ambul Care Manag. 2013;36(1):13-23. doi:10.1097/JAC.0b013e318276dc10

17.

Garrison

Angstman

O’Connor

Williams

Lineberry

TW.

Time to remission for depression with collaborative care management (CCM) in Primary Care. J Am Board Fam Med. 2016;29(1):10-17. doi:10.3122/jabfm.2016.01.150128

18.

Alford

LaBelle

Kretsch

, et al. Collaborative care of opioid-addicted patients in primary care using buprenorphine: five-year experience. Arch Intern Med. 2011;171(5):425-431. doi:10.1001/archinternmed.2010.541

19.

Fortney

Ratzliff

Blanchard

, et al. Collaborative care for opioid use disorder in primary care: a hybrid type 2 cluster randomized clinical trial. JAMA Psychiatr. 2025;82:956. doi:10.1001/jamapsychiatry.2025.2126

20.

Watkins

Ober

Lamp

, et al. Collaborative care for opioid and alcohol use disorders in primary care: the SUMMIT randomized clinical trial. JAMA Intern Med. 2017;177(10):1480-1488. doi:10.1001/jamainternmed.2017.3947

21.

Oesterle

Bormann

Paul

, et al. Treatment of substance use disorders with a mobile phone app within Rural Collaborative Care Management (Senyo Health): Protocol for a mixed methods randomized controlled trial. JMIR Res Protoc. 2025;14:e65693. doi:10.2196/65693

22.

Senyo: It’s the good times ahead. Accessed September 20, 2025. https://www.senyohealth.org/

23.

Oesterle

Hall-Flavin

Bormann

, et al. Therapeutic content of mobile phone applications for substance use disorders: an umbrella review. Mayo Clin Proc Digit Health. 2024;2(2):192-206. doi:10.1016/j.mcpdig.2024.03.004

24.

Hadani

Tarikogullari

Oesterle

, et al. Care coordination in screening, brief intervention, and referral to treatment (SBIRT): a scoping review. Am J Addict. 2026;35(1):22-35. doi:10.1111/ajad.70104

25.

National Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Health Sciences Policy; Committee on Medication-Assisted Treatment for Opioid Use Disorder. Medications for Opioid Use Disorder Save Lives. National Academies Press; 2019.

26.

McPheeters

O’Connor

Riley

, et al. Pharmacotherapy for alcohol use disorder: a systematic review and meta-analysis. JAMA. 2023;330(17):1653-1665. doi:10.1001/jama.2023.19761

27.

Lai

Good

Singh

Deyo

Marshall

Oesterle

Adolescent substance use disorder in primary care: challenges in treatment referral beyond access availability. J Prim Care Community Health. 2024;15:21501319241276817. doi:10.1177/21501319241276817

28.

Bhardwaj

Sousa

Huskamp

, et al. Prescribing medications for alcohol use disorder: a qualitative study of primary care physician decision making. Ann Fam Med. 2023;21(4):332-337. doi:10.1370/afm.2997

29.

Leung

Narayanan

Markota

, et al. Assessing naltrexone prescribing and barriers to initiation for alcohol use disorder: a multidisciplinary, multisite survey. Front Psychiatry. 2022;13:856938. doi:10.3389/fpsyt.2022.856938

30.

Fenstemaker

Abrams

Obringer

King

Dhanani

Franz

Primary care professionals’ perspectives on tailoring buprenorphine training for rural practice. J Rural Health. 2024;40(4):671-680. doi:10.1111/jrh.12832

31.

Franz

Dhanani

Hall

, et al. Buprenorphine misinformation and willingness to treat patients with opioid use disorder among primary care-aligned health care professionals. Addict Sci Clin Pract. 2024;19(1):7. doi:10.1186/s13722-024-00436-y

32.

John

Ghitza

, et al. Buprenorphine physician-pharmacist collaboration in the management of patients with opioid use disorder: results from a multisite study of the National Drug Abuse Treatment Clinical Trials Network. Addiction. 2021;116(7):1805-1816. doi:10.1111/add.15353

33.

Wartko

Bobb

Boudreau

, et al. Nurse Care Management for opioid use disorder treatment: the PROUD cluster randomized clinical trial. JAMA Intern Med. 2023;183(12):1343-1354. doi:10.1001/jamainternmed.2023.5701