CI

At a glance

ClinicalIndex Comparison Record
N/ACompleted· 64,996 enrolled
Drug / intervention
Processing of clinical notes in the EHR data collected during routine careother
Likely dose
Not stated in record
Structured eligibility isn't available for this trial yet — see the full criteria in the Eligibility tab below.

Standardized by ClinicalIndex from the ClinicalTrials.gov record · verify against the source.

Search/NCT03833804
NCT03833804N/ACompleted

Data-driven Strategies for Substance Misuse Identification in Hospitalized Patients

University of Wisconsin, Madison·interventional·Posted Feb 7, 2019·Updated Oct 24, 2025

In Brief

A clinical study evaluating Processing of clinical notes in the EHR data collected during routine care for Substance Use and 2 related conditions. Completed, enrolled 64,996 participants across 1 site.

Detailed 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.

Study Details

Study Typeinterventional
Allocation--
Masking--
Primary Purpose--
CountriesUnited States

Timeline

N/ACompletedFinished
20192020202120222023202420252026
First PostedFeb 7, 2019
Enrollment StartSep 19, 2022
Primary CompletionSep 19, 2024
TodayJul 2, 2026
Enrollment to primary: 2 yearsPosted 7.4 years ago

Interventions

Processing of clinical notes in the EHR data collected during routine careother

Clinical notes collected in the first day of hospital admission during usual care as input to natural language processing and machine learning algorithm.