Evidence map›Paper›PMID 41960325›Full record

ArticleResearch square2026

"This whole thing is relationship medicine": A qualitative analysis of mobile and street-delivered medication for opioid use disorder in King County, Washington, using RE-AIM.

Marin Strong, Chelsea Rodgers, Kaitlyn Harbick, Kathy Wang, Ohshue S Gatanaga, Sara N Glick, Maria Corcorran, Omeid Heidari

Abstract readPreprint
In one paragraph

Article in Research square, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Marin StrongUniversity of Washington.
Chelsea RodgersUniversity of Washington.
Kaitlyn HarbickPublic Health - Seattle & King County.
Kathy WangUniversity of Washington.
Ohshue S GatanagaUniversity of Washington.
Sara N GlickPublic Health - Seattle & King County.
Maria CorcorranUniversity of Washington.
Omeid HeidariUniversity of Washington.

Funding

University of Washington/Fred Hutch Center for AIDS ResearchP30AI027757 · NIAID · UNIVERSITY OF WASHINGTON · PI CONNIE L CELUM · 1988 to 2026
$104.9M
Community-Based Opioid Treatment (CBOT): Development and testing of a novel nurse-led model to deliver opioid use disorder treatment and HIV prevention and care in the community setting.DP2DA063123 · NIDA · UNIVERSITY OF WASHINGTON · PI HEIDARI, OMEID · 2025 to 2025
$2.3M
RiNGH (Research in Nursing & Global Health) Training ProgramT32NR019761 · NINR · UNIVERSITY OF WASHINGTON · PI KOHLER, PAMELA, PINTYE, JILLIAN · 2021 to 2025
$1.4M
Training in Equity and Structural Solutions in Addictions (TESSA)T32DA057920 · NIDA · UNIVERSITY OF WASHINGTON · PI GEETANJALI CHANDER, Judith Tsui · 2023 to 2026
$1.3M
NIAID NIH HHS P30 AI027757NIDA NIH HHS DP2 DA063123NIDA NIH HHS T32 DA057920NINR NIH HHS T32 NR019761
6 · The paper itself

Abstract

Background: Nationally, drug overdose deaths have increased 3-fold over the past two decades, and as of 2023 were significantly higher in Washington (WA) state. Medication for opioid use disorder (MOUD) reduces morbidity and mortality of opioid use; however, delivery often occurs in clinics with multilevel barriers to care. Mobile and street-based models are strategies for engaging individuals at high risk of an overdose by bringing MOUD directly to people who use drugs (PWUD) in the community. This study used the RE-AIM (Reach Effectiveness Adoption Implementation Maintenance) framework to systematically examine cross-programmatic care delivery and sustainability of mobile and street-based MOUD models in King County, WA. Methods: We conducted semi-structured interviews with frontline providers and administrators between January-June 2025. Eligible programs provided MOUD in King County, WA, and delivered care using a mobile and/or street team model. Using team-based iterative coding, we developed initial codes deductively from REAIM and refined the codebook during consensus coding, allowing inductive codes to emerge. A qualitative descriptive methodology informed by RE-AIM was applied for thematic analysis. Results: Participants (n = 21) were from 13 unique MOUD programs and were mostly female (57%), held a master's degree or higher (67%), and had an average of 7 years of work experience with opioid use disorder. Patients reached were often living unhoused with complex comorbidities and were identified through referrals, outreach, and co-location with social services. Effectiveness was often measured by funder-driven metrics that participants felt focused on clinical and process outcomes rather than accurately capturing patient well-being. Flexibility in training, staff roles, practice, and medication protocols was key to the adoption of MOUD in mobile and street environments. Implementation was facilitated by interdisciplinary teams, the combination of established mobile vans with targeted high-touch outreach, and holistic wraparound care. Programmatic maintenance depended on strong community partnerships and diverse funding streams. Sustainability hinged on program capacity meeting increasing demand and on transitioning clients to clinic care, so outreach efforts could continue to center on PWUD with the highest needs. Conclusions: Programs can leverage these mechanisms to initiate and retain individuals at high risk of opioid overdose with MOUD services.

Indexed as

buprenorphineharm reductionmobile health unitsopioid-related disordersprogram evaluation

Identifiers

PMID41960325
PMCPMC13060497

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.