Work

Outcomes and Cost-Effectiveness of an EHR-Embedded AI Screener for Identifying Hospitalized Adults at Risk for Opioid Use Disorder

Year: 2024

Type: preprint

Study design: Clinical Trial

Source: Research Square

DOI: 10.21203/rs.3.rs-5200964/v1

Authors: Majid Afshar, Felice Resnik, Cara Joyce, Madeline Oguss, Dmitriy Dligach, Elizabeth Burnside, Anne Sullivan, Matthew Churpek, Brian Patterson, Elizabeth Salisbury-Afshar, Frank Liao, Randall Brown, Marlon Mundt

Institutions: University of Wisconsin–Madison, Loyola University Chicago

Language: English

Topic: Opioid Use Disorder Treatment

Subfield: Public Health, Environmental and Occupational Health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Heart, Lung, and Blood Institute, National Institute on Drug Abuse, U.S. National Library of Medicine

Awards: Developing a clinical decision support tool for the identification, diagnosis, and treatment of critical illness in hospitalized patients, Temporal relation discovery for clinical text, Data Driven Strategies for Substance Misuse Identification in Hospitalized Patients, University of Wisconsin Institute for Clinical and Translational Research, Learning Universal Patient Representations with Hierarchical Transformers

OpenAlex ID: W4403402646

Cites: 43

Cited by:

Related to: 10