ArticleResearch square2026
Brief Report on screening data from a randomized controlled trial of in-hospital buprenorphine initiation strategies.
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.
What it found
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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.
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.
Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
12 authors.
Funding
Abstract
Objectives: Buprenorphine (BUP) is effective for treating opioid use disorder and chronic pain (CP); however, there are missed opportunities for initiation during hospitalization. We conducted a clinical trial of in-hospital BUP initiation strategies and reviewed electronic health record data (EHR) to identify potentially eligible patients for BUP treatment. We present trial screening data to analyze the efficiency of EHR surveillance to identify BUP-eligible patients. Methods: Recruitment occurred between 10/2022 to 10/2024 at two urban teaching hospitals. An automated EHR algorithm generated a daily list of patients with likely opioid misuse or OUD. Preliminary manual review of the EHR algorithm was conducted by staff, who then contacted potentially eligible patients and their physicians before assessing for trial eligibility and BUP treatment. If patients were not assessed, research assistants use pre-specified categories to document reasons why. Results: The algorithm produced 9140 records for screening and 8534 (93%) were excluded based on preliminary manual review. Of 434 potentially eligible patients, only 43 agreed to be assessed for the trial. Of the 43 patients, 29 were eligible and 23 enrolled in the trial and started BUP, yielding a 5% initiation rate among the pool of potentially eligible patients. Conclusions: While the automated EHR algorithm identified patients potentially eligible for BUP, substantial manual review was required. Improving algorithm precision, for example with artificial intelligence applications, could better identify BUP-eligible patients; nonetheless, our experience suggests that patient concerns and potential stigma regarding BUP present as ongoing obstacles to BUP uptake.
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