CompletedNot Applicable

Data-driven Identification for Substance Misuse

United States64,996 participantsStarted 2022-09-19

Plain-language summary

The investigators propose to develop an open-source, publicly available machine learning model that health systems could download and apply to their electronic health record data marts to screen for substance misuse in their patients. The investigators hypothesize that the natural language processing algorithm can provide a standardized and interoperable approach for an automated daily screen on all hospitalized patients and provide better implementation fidelity for screening, brief intervention, and referral to treatment.

Who can participate

Age range18 Years – 89 Years

SexALL

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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.

Inclusion Criteria: * Ages 18 years old to 89 years old * Inpatient status during hospitalization * Length of stay greater than 24 hours Exclusion Criteria: * Cannot participate in the usual care SBIRT intervention * Death or obtunded during first 24 hours of admission * Discharged against medical advice * Transferred from another acute care hospital * Transferred to another acute care hospital

What they're measuring

Proportion of Patients That Had a Universal Screen Positive and Received SBIRT (Screening, Brief Intervention, or Referral to Treatment)

Timeframe: 24 months

Trial details

NCT IDNCT03833804

SponsorUniversity of Wisconsin, Madison

Sponsor typeOTHER

Study typeINTERVENTIONAL

Primary completion2024-09-19

Results submitted2025-09-09

View on ClinicalTrials.gov More Substance Use trials