Evidence map›Paper›PMID 40638840›Full record

ArticleJournal of medical Internet research2025

Facilitators and Challenges to Adoption of a Digital Health Tool for Opioid Use Disorder Treatment in Primary Care: Mixed Methods Study.

Omar Nieto, Allison D Rosen, Mariah M Kalmin, Li Li, Steven J Shoptaw, Steven P Jenkins, Zahra Zarei Ardestani, Bengisu Tulu

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Omar NietoDepartment of Family Medicine, University of California, Los Angeles, 10880 Wilshire Boulevard, Suite 1800, Los Angeles, CA, 90024, United States, 1 3107940229.ORCID http://orcid.org/0000-0003-1196-6874
Allison D RosenDepartment of Family Medicine, University of California, Los Angeles, 10880 Wilshire Boulevard, Suite 1800, Los Angeles, CA, 90024, United States, 1 3107940229.ORCID http://orcid.org/0000-0002-1630-0222
Mariah M KalminDepartment of Behavioral and Policy Sciences, RAND Corporation, Santa Monica, CA, United States.ORCID http://orcid.org/0000-0002-7329-8931
Li LiUCLA Center for HIV Identification, Prevention, and Treatment Services (CHIPTS), University of California, Los Angeles, Los Angeles, CA, United States.ORCID http://orcid.org/0000-0002-3402-142X
Steven J ShoptawDepartment of Family Medicine, University of California, Los Angeles, 10880 Wilshire Boulevard, Suite 1800, Los Angeles, CA, 90024, United States, 1 3107940229.ORCID http://orcid.org/0000-0002-3583-0026
Steven P JenkinsQ2i LLC, Boston, MA, United States.ORCID http://orcid.org/0009-0000-4333-5116
Zahra Zarei ArdestaniDepartment of Data Science, Worcester Polytechnic Institute, Worcester, MA, United States.ORCID http://orcid.org/0009-0006-4374-2831
Bengisu TuluThe WPI Business School, Worcester Polytechnic Institute, Worcester, MA, United States.ORCID http://orcid.org/0000-0001-7226-1830

Funding

Technology Improving Success of Medication-Assisted Treatment in Primary CareR42DA050398 · NIDA · Q2I, LLC · PI JENKINS, STEVEN PAUL · 2019 to 2021
$1.7M
NIDA NIH HHS R42 DA050398
6 · The paper itself

Abstract

Background: The United States is facing an opioid overdose epidemic resulting in an unprecedented number of preventable deaths. The use of medications including buprenorphine and methadone has proven effective for opioid use disorder (OUD), but many patients struggle to stay in treatment. Novel solutions, such as digital health tools, offer one option to help improve clinic management and improve treatment engagement. Objective: Using a mixed methods approach, we investigated facilitators and barriers to the use of a third-party digital health platform called Opioid Addiction Recovery Support (OARS) to aid OUD treatment engagement and adherence in a primary care setting. Methods: Patient and provider use of OARS was observed for 10 months and summarized using descriptive statistics. Differences in use were assessed using Wilcoxon signed rank tests. Additionally, key informant interviews were conducted with providers who prescribe medication for opioid use disorder (MOUD) and their case managers to understand the facilitators and barriers to implementation. Qualitative data were analyzed using a coding reliability thematic analysis approach. Results: Among 205 patients invited to use OARS, the median age was 37 (IQR 31-44) years, 130 (63.4%) identified as men, and 193 (94.1%) identified as non-Hispanic White. Of these 205 patients, 158 (77.1%) used the app at least 1 time. The median number of days the 158 patients viewed test results was 1 (IQR 1-3), progress was 1 (IQR 0-2), and educational content was 0 (IQR 0-1). The 55 patients whose providers had manually entered their results into OARS when the electronic health record (EHR) integration failed viewed test results (P=.002), progress (P<.001), and educational content (P<.001) more days than the 103 patients who could not view their results in OARS. Providers and the lead case manager reported that OARS increased patient-provider communication, allowed patients to better track their overall MOUD treatment, and enhanced providers' ability to identify patients at risk for relapse. They also acknowledged that the lack of integration between OARS with the EHR resulted in administrative burdens, which impacted provider use of the system. Conclusions: Findings from this study highlight the challenges of successfully implementing OARS with patients who receive MOUD in primary care settings. Our results show a lack of OARS uptake among providers, case managers, and patients, despite positive assessments made by participants. We also show several barriers that impacted provider use, including the lack of integration between OARS and EHR. Future research is needed (1) to determine whether digital health tools like OARS are efficacious in improving OUD outcomes and, if proved efficacious, (2) to identify ways to routinize the use of digital health tools in MOUD treatment, primarily by solving technical and organizational challenges associated with EHR integration and patient engagement.

Indexed as

Opioid-Related DisordersPrimary Health CareAdultDigital HealthFemaleHumansMaledigital health toolsimplementation barriersopioid use disorder treatmentprimary care clinicssystem integration

Identifiers

PMID40638840
PMCPMC12287979

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.