A Study of Emergency Department AI Prediction Impact | NCT05683899

Studies
A Study of Emergency Department AI Prediction Impact

NCT05683899

Sponsor

Mayo Clinic

Status

Completed

Last Update Posted

Apr 5, 2024Actual

Enrollment

80Actual

Phase

Not provided

Conditions

Hospital Admission
Length of Stay

Interventions

Not provided

Countries

United States

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Apr 2024

Overall Recruitment Status or Expanded Access Status

Completed

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Jan 3, 2023Actual

Primary Completion Date

Dec 4, 2023Actual

Completion Date

Dec 4, 2023Actual

First Submitted Date

Jan 5, 2023

First Submission Date that Met QC Criteria

Jan 5, 2023

First Posted Date

Jan 13, 2023Actual

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Apr 3, 2024

Last Update Posted Date

Apr 5, 2024Actual

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

Brief Summary

The purpose of this study is to evaluate the impact of an AI admission prediction tool on the number of preventable hospital admissions, emergency department (ED) length of stay, when the predictions are displayed only to a dedicated ED triage team. Also, to evaluate user perceptions of the AI tool among the triage team users and medical officer of the day users. Additionally, to evaluate any impact of the AI tool on the number of interventions performed by the triage team, and to evaluate the impact of the tool on time-to-admission after an admission order is placed.

Detailed Description

Not provided

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

80Actual

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
Group A		141 days with AI scores displayed
Group B		141 days with AI scores not displayed

Interventions

Not provided

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
Hospital Admissions	Number of avoidable admissions prevented as a fraction of all ED patients in a day, specifically, the number of patients who were seen by the SAPPHIRE triage team and discharged home	282 days

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

For the survey component, any HIM clinician that works a shift in the triage area, ED physicians, and the medical officer of the day will be included.
For length of stay data, adult patients registered in the Mayo Clinic-Rochester St. Mary's Emergency Department will be included.

Exclusion Criteria:

For the survey, clinicians not working a triage shift during the study period will be excluded.
For the length of stay analysis, only adult ED patients will be included, who do not triaged to the behavioral health/psychiatry pathway, nor patients who are triaged to the Emergency Department observation pathway.

Accepts Healthy Volunteers

Yes

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

Not provided

Standard Ages

AdultOlder Adult

Study Population

The group being surveyed will consist of Hospital Internal Medicine (HIM) clinicians, (physicians, nurse practioners, and physician assistants) at the Mayo Clinic- Rochester site, who are all adults. The patients which are triaged by this group are only adults, and accordingly, the AI score will never be shown for pediatric patients, or patients undergoing psychiatric evaluation.

Sampling Method

Non-Probability Sample

Name	Affiliation	Role
Alexander Ryu, MD	Mayo Clinic	Principal Investigator

Facility	Status	City	State	ZIP	Country	Contacts
Mayo Clinic Minnesota		Rochester	Minnesota	55905	United States

References Module

Citations

PubMed Identifier	Type	Citation	Retractions
42120428	Derived	Ryu AJ, Ayanian S, Qian R, Parikh RS, Dugani SB, Fischer KM, Heaton HA, Boyum JP, Hinton BJ, Lawson DK, Burton MC. Artificial intelligence for predicting hospital admissions from the emergency department: a prospective, quasi-experimental study. Nat Commun. 2026 May 12. doi: 10.1038/s41467-026-72960-1. Online ahead of print.

ID	Term
D020969	Disease Attributes
D010335	Pathologic Processes
D013568	Pathological Conditions, Signs and Symptoms