• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to secondary sidebar
  • Skip to footer

  • Opinion
  • Health IT
    • Behavioral Health
    • Care Coordination
    • EMR/EHR
    • Interoperability
    • Patient Engagement
    • Population Health Management
    • Revenue Cycle Management
    • Social Determinants of Health
  • Digital Health
    • AI
    • Blockchain
    • Precision Medicine
    • Telehealth
    • Wearables
  • Life Sciences
  • Investments
  • M&A
  • Value-based Care
    • Accountable Care (ACOs)
    • Medicare Advantage

LLMs Outperforms Clinicians in Predicting Mental Health Crises, Study Reveals

by Fred Pennic 08/06/2024 Leave a Comment

  • LinkedIn
  • Twitter
  • Facebook
  • Email
  • Print
LLMs Outperforms Clinicians in Predicting Mental Health Crises, Study Reveals

What You Should Know: 

– Brightside Health, a telemental health company released research demonstrating the potential of large language models (LLM) in predicting mental health crises. 

– The study, published in JMIR Mental Health, compared the performance of OpenAI’s GPT-4 to human clinicians in identifying patients at risk of suicide.

Study Background and Key Findings

The research analyzed data from over 460 patients, including those who had reported suicidal ideation with a plan. Both clinicians and GPT-4 were tasked with predicting the likelihood of a mental health crisis based solely on the patient’s initial complaint.

The study resulted in the following: 

  • GPT-4 Achieved Similar Accuracy: The AI model demonstrated comparable overall accuracy to human clinicians in identifying patients at risk of suicide.
  • Superior Sensitivity: GPT-4 exhibited higher sensitivity, meaning it was better at correctly identifying patients who would later develop suicidal ideation.
  • Time Efficiency: GPT-4 completed the analysis significantly faster than human clinicians, highlighting the potential for increased efficiency in mental healthcare.

While the study demonstrates the potential of LLMs in this area, researchers emphasize the need for further development and testing before clinical implementation. The model’s performance was influenced by the specific data used for training, and it is essential to address potential biases in LLMs.

“In line with our commitment to utilize AI in a safe and controlled manner, this research highlights the potential of large language models for triage and clinical decision support in mental health,” said Dr. Mimi Winsberg, Co-Founder and Chief Medical Officer of Brightside Health. “While clinical oversight remains paramount, technologies such as these can help alleviate provider time shortage and empower providers with risk assessment tools, which is especially crucial for patients at risk of suicide.”

  • LinkedIn
  • Twitter
  • Facebook
  • Email
  • Print

Tagged With: Artificial Intelligence, Behavioral Health, Large Languard Model (LLM), Mental Health

Tap Native

Get in-depth healthcare technology analysis and commentary delivered straight to your email weekly

Reader Interactions

Primary Sidebar

Subscribe to HIT Consultant

Latest insightful articles delivered straight to your inbox weekly.

Submit a Tip or Pitch

HLTH 2025 Coverage

HLTH 2025 Day 1 Summary & Insights: AMA Launches AI Governance Center, Google Cloud, Microsoft, ChatGPT for Medicine

Featured Interview

ConcertAI VP Shares View on AI Hallucinations and the Fabricated Data Crisis in Scientific Publishing

Most-Read

Cleveland Clinic and Khosla Ventures Form Strategic Alliance to Accelerate Healthcare Innovation

Cleveland Clinic and Khosla Ventures Form Strategic Alliance to Accelerate Healthcare Innovation

Northwell Health Selects to Deploy Abridge’s Ambient AI Across 28 Hospitals

Northwell Health to Deploy Abridge’s Ambient AI Across 28 Hospitals

Omada Health Launches "Nutritional Intelligence" with AI Agent OmadaSpark

Omada Health Launches AI-Powered Meal Map to Transform Nutrition for Cardiometabolic Patients

From Overwhelmed to Optimized: How AI Agents Address Staffing Challenges and Burnout in Healthcare

From Overwhelmed to Optimized: How AI Agents Address Staffing Challenges and Burnout in Healthcare

Qualtrics Acquires Press Ganey Forsta for $6.75B to Create the Most Comprehensive AI Experience Platform

Qualtrics Acquires Press Ganey Forsta for $6.75B to Create the Most Comprehensive AI Experience Platform

Pfizer and Trump Administration Announce Landmark Agreement to Lower Drug Costs

Pfizer and Trump Administration Announce Landmark Agreement to Lower Drug Costs

KLAS Report: Epic's Native Ambient Speech Tool Reshapes Customer AI Strategies

KLAS Report: Epic’s Native Ambient Speech Tool Reshapes Customer AI Strategies

Epic Unveils MyChart Central and New APIs to Advance Interoperability at Open@Epic

Epic Outlines Roadmap for Next-Generation Data Sharing at Open@Epic

Epic Launches Comet: A New AI Platform to Predict Patient Health Journeys

Epic Launches Comet: A New AI Platform to Predict Patient Health Journeys

RevSpring to Acquire Kyruus Health, Creating a Unified Patient Experience

RevSpring to Acquire Kyruus Health, Creating a Unified Patient Experience

Secondary Sidebar

Footer

Company

  • About Us
  • Advertise with Us
  • Reprints and Permissions
  • Op-Ed Submission Guidelines
  • Contact
  • Subscribe

Editorial Coverage

  • Opinion
  • Health IT
    • Care Coordination
    • EMR/EHR
    • Interoperability
    • Population Health Management
    • Revenue Cycle Management
  • Digital Health
    • Artificial Intelligence
    • Blockchain Tech
    • Precision Medicine
    • Telehealth
    • Wearables
  • Startups
  • Value-Based Care
    • Accountable Care
    • Medicare Advantage

Connect

Subscribe to HIT Consultant Media

Latest insightful articles delivered straight to your inbox weekly

Copyright © 2025. HIT Consultant Media. All Rights Reserved. Privacy Policy |