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Related Experiment Video

Updated: Jun 29, 2025

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
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Randomized Controlled Comparative Effectiveness Trial of Risk Model-Guided Clinical Decision Support for Suicide

Colin G Walsh, Michael A Ripperger, Laurie Novak

    Medrxiv : the Preprint Server for Health Sciences
    |April 2, 2024
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    Summary
    This summary is machine-generated.

    Interruptive clinical decision support (CDS) significantly increased screening for suicide risk in neurology clinics compared to non-interruptive CDS. This approach shows promise for improving suicide prevention strategies.

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    Area of Science:

    • Clinical Informatics
    • Psychiatry
    • Public Health

    Background:

    • Suicide prevention necessitates effective risk identification, intervention, and follow-up.
    • Traditional methods rely on self-reporting, support networks, or in-person screenings.
    • Statistical risk models are emerging tools to aid clinical judgment in identifying suicide risk.

    Approach:

    • A pragmatic randomized controlled trial (RCT) was conducted in adult neurology outpatient clinics.
    • The study compared Interruptive and Non-Interruptive Clinical Decision Support (CDS) systems.
    • The primary endpoint was the decision to screen for suicidal ideation in patients predicted to be at high risk.

    Key Points:

    • Interruptive CDS resulted in significantly higher rates of screening decisions (42%) compared to Non-Interruptive CDS (4%).
    • Despite lower documentation rates of assessment among those screened in the interruptive arm, overall documented suicide risk assessments were higher.
    • No suicidal ideation or attempts were documented in either trial arm.

    Conclusions:

    • Real-time predictive CDS, particularly the interruptive type, enhances the decision to screen for suicide risk and increases documented risk assessments.
    • Further large-scale trials are needed to confirm the effectiveness of this CDS approach in reducing suicidal self-harm.
    • The study utilized a validated statistical risk model for real-time suicide attempt risk prediction.