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Telemedicine Notifications With Machine Learning for Postoperative Care
Sponsor: Washington University School of Medicine
Summary
The ODIN-Report study will be a randomized controlled trial of the effect of providing machine learning risk forecasts to providers caring for patients immediately after surgery on serious complications. The complications studied will be ICU admission or death on wards, acute kidney injury, and hospital length of stay.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
INTERVENTIONAL
Enrollment
0
Start Date
2025-10-06
Completion Date
2025-10-06
Last Updated
2026-05-12
Healthy Volunteers
No
Conditions
Interventions
Anesthesia Control Tower Notification
Real-time data will be monitored through the AlertWatch system as well as the electronic health record. Risk forecasts of adverse events (30 day mortality, acute kidney injury, postoperative delirium, respiratory failure), PACU length of stay, and hospital length of stay will be generated by a machine learning algorithm. Additional outputs identifying the most important predictors and their effects will be combined with risk forecasts to form a report card.