Overview
An artificial intelligence (AI) model has significantly improved the detection and treatment of delirium in hospitalized patients, increasing the identification rate by 400%. This advancement allows healthcare teams to better assess patients at high risk for delirium and develop appropriate treatment plans.
Key Findings
- The AI model was developed by researchers at the Icahn School of Medicine at Mount Sinai and is now integrated into hospital operations.
- Delirium can affect up to one-third of hospitalized patients, leading to severe confusion and potentially life-threatening risks.
- The study, published in the May 7, 2025 issue of JAMA Network Open, is the first to demonstrate real-world benefits of an AI-powered delirium risk model.
Importance of Delirium Detection
Delirium is often undetected in hospitalized patients, which can lead to prolonged hospital stays, increased mortality risk, and poorer long-term outcomes. The AI model addresses these challenges by:
- Identifying patients at high risk for delirium.
- Alerting a specially-trained team for timely assessment and intervention.
Research Methodology
The study involved over 32,000 patients at The Mount Sinai Hospital in New York City. The AI model analyzed both structured data and clinicians’ notes from electronic health records, utilizing machine learning and natural language processing to identify patterns associated with delirium risk.
Results
Upon implementation, the AI model achieved:
- A 400% increase in identified delirium cases without extending screening time.
- Safer prescribing practices by minimizing the use of inappropriate medications in older adults.
- Reliable performance in a real-world hospital setting.
Future Directions
While the AI model has shown promising results at The Mount Sinai Hospital, further validation is necessary across different hospital systems to assess its effectiveness in varied clinical environments.
Conclusion
This research highlights the potential of AI-driven clinical decision support tools to enhance patient safety and outcomes by ensuring timely and specialized care for those at risk of delirium.