Telemedicine Notifications With Machine Learning for Postoperative Care (ODIN-Report)

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.

Study Overview

• Status: Withdrawn
• Conditions: Acute Kidney Injury; Surgery--Complications; Perioperative/Postoperative Complications; Hospital Mortality
• Intervention / Treatment: Device: Anesthesia Control Tower Notification

Detailed Description

This will be a single center, randomized, controlled, pragmatic clinical trial. The investigators will screen surgical patients enrolled in TECTONICS (NCT03923699) and randomized to intraoperative contact. Near the end of the operation, the investigators will calculate the same machine learning risk forecasts of major complications as TECTONICS, and enroll patients if all of the following are true: (1) No ICU admission is intended (2) ML mortality risk forecast is in top 15% of historical PACU patients.

Patients will be randomized 1:1:1 to no contact, brief contact, and full contact. The postoperative provider (PACU physician, anesthesiologist, ward clinician) will be notified before arrival of the risk forecast in the contact groups, and in the full contact group an additional set of explanatory ML outputs will be provided. The intention-to-treat principle will be followed for all analyses.

• Study Type: Interventional
• Phase: Not Applicable

Contacts and Locations

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Enrolled in TECTONICS Study (ID 201903026, NCT03923699), in OR randomized to contact
• workweek hours
• preoperative assessment completed
• estimated risk of mortality in top 15% of historical PACU patients

Exclusion Criteria:

• Not enrolled in TECTONICS Study
• Operating room randomized to non-contact in TECTONICS
• Planned ICU admission

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Other
• Allocation: Randomized
• Interventional Model: Parallel Assignment
• Masking: Double

Number of Arms

3

Arms and Interventions

Participant Group / Arm	Intervention / Treatment
No Intervention: Non-Contact; Participants in the non-contact group will be monitored by anesthesia control tower clinicians who will utilize AlertWatch and integrating machine-learning forecasting algorithms for adverse outcomes predictions, but who will not contact the postoperative provider unless it is clinically necessary for patient safety purposes.
Experimental: Brief contact; PACU and ward providers caring for participants in the brief contact group will be notified by Anesthesia Control Tower clinicians before arrival if the patient's forecast for mortality is in the top 15% of historical PACU patients. The notification will contain a brief summary of the patient's forecast risk of major adverse events.	Device: 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.
Experimental: Full contact; PACU and ward providers caring for participants in the full contact group will be notified by Anesthesia Control Tower clinicians before arrival if the patient's forecast for mortality is in the top 15% of historical PACU patients. The notification will contain a report card of the patient's forecast risk of major adverse events, explanatory machine-learning outputs, most influential pre- and intraoperative data, and predicted treatments.	Device: 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Unplanned ICU admission	Admission to a "critical care" bed regardless of rationale or duration at any point in the follow up time frame. Patients who expire without transfer to ICU will be marked as positive.	7 days post-op

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Acute Kidney Injury	Postoperative laboratory values and urine output will be used to calculate Kidney Disease Improving Global Outcomes grades of acute kidney injury. Where unavailable, baseline Glomerular filtration rate will be assumed to be age, sex, and body size normal.	7 days post-op
Hospital length of stay	The duration in days between end of anesthesia care and discharge from the performing hospital.	30 days post-op

Collaborators and Investigators

• Sponsor: Washington University School of Medicine
• Investigators: Principal Investigator: Christopher R King, MD, PhD, Washington University School of Medicine

Study record dates

Study Major Dates

• Study Start (Actual): October 6, 2025
• Primary Completion (Actual): October 6, 2025
• Study Completion (Actual): October 6, 2025

Study Registration Dates

• First Submitted: June 2, 2019
• First Submitted That Met QC Criteria: June 4, 2019
• First Posted (Actual): June 5, 2019

Study Record Updates

• Last Update Posted (Actual): May 12, 2026
• Last Update Submitted That Met QC Criteria: May 6, 2026
• Last Verified: May 1, 2026

More Information

Terms related to this study

• Keywords: Telemedicine; Randomized Controlled Trial; Machine Learning; PACU; Anesthesia Control Tower; Forecasting Algorithms
• Additional Relevant MeSH Terms: Urogenital Diseases; Pathologic Processes; Male Urogenital Diseases; Kidney Diseases; Urologic Diseases; Female Urogenital Diseases; Female Urogenital Diseases and Pregnancy Complications; Renal Insufficiency; Pathological Conditions, Signs and Symptoms; Acute Kidney Injury; Postoperative Complications; Physiological Effects of Drugs; Central Nervous System Depressants; Anesthetics
• Other Study ID Numbers: 201905127

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: Data are a subset of TECTONICS and will be have the same sharing plan / restrictions.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: Yes
• product manufactured in and exported from the U.S.: Yes