Evidence map›Paper›PMID 36692880›Full record

ArticleJAMA network open2023

Telemedicine Use and Quality of Opioid Use Disorder Treatment in the US During the COVID-19 Pandemic.

Ruth Hailu, Ateev Mehrotra, Haiden A Huskamp, Alisa B Busch, Michael L Barnett

Full text read
In one paragraph

Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
45citing papers in PubMed, 1 pooled it
–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

45 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  5. Comparison of buprenorphine treatment by virtual-only vs. traditional clinicians.Journal of substance use and addiction treatment · 2026
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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

5 authors.

Ruth HailuDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Ateev MehrotraDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Haiden A HuskampDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Alisa B BuschDepartment of Health Care Policy, Harvard Medical School, Boston, Massachusetts.
Michael L BarnettDepartment of Health Policy and Management, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.

Funding

Research Support CoreP30DA035772 · NIDA · BRANDEIS UNIVERSITY · PI Haiden A Huskamp, SHARON REIF · 2015 to 2026
$11.3M
Telemedicine for Treatment of Opioid Use Disorder: NIDA Summer Research Internship ProgramR01DA048533 · NIDA · HARVARD MEDICAL SCHOOL · PI Haiden A Huskamp, Ateev Mehrotra · 2019 to 2026
$5.6M
The Changing Landscape of Post-Acute Care and Health Outcomes for Older AdultsK23AG058806 · NIA · HARVARD SCHOOL OF PUBLIC HEALTH · PI BARNETT, MICHAEL LAWRENCE · 2018 to 2022
$1.0M
NIA NIH HHS K23 AG058806NIDA NIH HHS P30 DA035772NIDA NIH HHS R01 DA048533
6 · The paper itself

Abstract

Importance: Little is known about the potential implications of the rapid transition to telehealth during the COVID-19 pandemic for treatment of opioid use disorder (OUD). Objective: To examine the association between telemedicine adoption during the COVID-19 pandemic and indicators of OUD treatment quality. Design, Setting, and Participants: This cohort study analyzed deidentified administrative claims data from OptumLabs Data Warehouse. Claims for telemedicine visits were included for both the prepandemic period (March 14, 2019, to March 13, 2020) and pandemic period (March 14, 2020, to March 13, 2021). Patients with OUD and continuous enrollment in either commercial insurance or Medicare Advantage plans were included. Clinicians who provided office-based OUD care were included and categorized into low, medium, or high telemedicine use groups. Patients were attributed to the clinician (and corresponding telemedicine use group) from whom they received a plurality of OUD visits. Main Outcomes and Measures: The 4 outcomes were all outpatient visits, OUD visits (in person vs telemedicine) within 90 days of an index visit, medications for OUD (MOUD) prescribing, and OUD-related clinical events (including drug overdose, inpatient detoxification and rehabilitation center stay, or injection drug use-related infections). Results: The analysis included 11 801 patients (mean [SD] age, 53.9 [15.7] years; 5902 males [50.0%]) who were treated by 1768 clinicians. Clinicians with low vs high telemedicine use conducted a mean (SD) of 2.1% (2.5%) vs 69.5% (18.6%) of their office visits virtually in the pandemic period. While telemedicine use for OUD increased significantly from the prepandemic to pandemic periods, total OUD visit volume (in person plus telemedicine) per patient episode remained stable among both high (2.6 to 2.7 visits per patient episode) and low (3.1 to 3.3 visits per patient episode) telemedicine use groups. In adjusted analyses comparing the prepandemic with pandemic periods, there was no differential change in MOUD initiation (adjusted odds ratio [OR], 1.00; 95% CI, 0.84-1.19), MOUD days' supply (differential change in days' supply, -0.27; 95% CI, -1.84 to 1.30), or OUD-related clinical events (adjusted OR, 1.01; 95% CI, 0.73-1.24) among patients who were treated by clinicians in low vs high telemedicine use groups. Conclusions and Relevance: Results of this study revealed that clinical outcomes were similar among patients who were treated by clinicians with high and low telemedicine use during the COVID-19 pandemic, suggesting that telemedicine is a comparable alternative to in-person OUD care. There was no evidence that telemedicine was associated with increased access to or improved quality of OUD treatment.

Indexed as

COVID-19Opioid-Related DisordersTelemedicineAgedCohort StudiesHumansMaleMedicareMiddle AgedPandemicsUnited States

Identifiers

PMID36692880
PMCPMC10038015

What OpenQuestion holds

Textfull text, public
LicenceCC BY
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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.