PICTURE Pediatric: AI early-warning to spot kids likely to worsen
Official title: Pilot Randomized Controlled Trial of PICTURE-Pediatric
Run by University of Michigan · NCT07304050 · Data updated 2026-11-12
This pilot tests an AI-based early warning system that gives real-time risk scores and alerts to care teams for pediatric patients on general wards and ED boarders to see if the workflow and interface achieve high compliance.
Quick facts
| Study type | Interventional |
|---|---|
| Ages | 30 Days to 25 Years |
| Sex | All |
| Enrollment | 375 (estimated) |
| Sponsor | University of Michigan Academic / other |
| Locations | 1 site (Ann Arbor, Michigan) |
| Status | Recruiting |
| Started | February 9, 2026 |
| Main results expected | January 2027 |
| Study ends | January 2027 |
| Registry record updated | March 5, 2026 |
| Trial ID | NCT07304050 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Pediatric patients aged ≥30 days to ≤25 years who are on general care wards at Mott Children's Hospital or boarding in the ED but admitted to a pediatric floor medical team are the intended population.
✕Probably not a fit
Patients already in the ICU, those outside the specified age range, or patients located outside the enrolled wards/ED locations are not expected to be affected by this implementation.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
PICTURE Pediatric uses routine EHR data (vitals, labs, monitored values) every 15 minutes to generate a deterioration risk score that has outperformed PEWS in prior work. In this interventional pilot, clinical teams will see PICTURE scores and alerts during one workflow arm while the control arm has scores hidden, and scores for red-risk patients will be included in handoff notes and inform morning rounds. The protocol does not mandate clinical actions based on alerts; care teams make decisions using their clinical judgment. The primary hypothesis is that the combined model, workflow, and interface will reach at least 80% compliance among clinicians, and clinician usability and acceptability will be measured via questionnaires.
Why it matters
Potential benefit: If successful, the system could help teams identify deteriorating children earlier, potentially reducing PICU transfers, morbidity, and hospital length of stay while improving bed flow.
How similar studies have gone: Prior work indicates the PICTURE Pediatric algorithm outperforms PEWS and similar scores for predicting deterioration, but real-world clinical implementation and workflow usability remain relatively novel and are the focus of this pilot.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria - Patients:
* Age ≥30 days and ≤25 years
* Be on the general care wards of Mott Children's Hospital or boarding in the Emergency Department (ED), but admitted to a pediatric floor medical team. These will be enforced by these criteria:
1. Patient class: not emergency b. Patient level of care: not Intensive Care unit (ICU) c. Patient locations (per protocol)
Exclusion Criteria - Patients:
* Patients that do not meet the inclusion criteria
Where it's running
-
University of Michigan
Ann Arbor, Michigan, United States Recruiting
Study contacts
- Principal investigator: Rodney Daniels — University of Michigan
- Study coordinator: Jay Semerad
- Email: jsemerad@umich.edu
- Phone: 734-647-4751
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.