Hospital AdmissionNCT05683899
A Study of Emergency Department AI Prediction Impact
An observational study of Hospital Admission and Length of Stay, run by Mayo Clinic at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Hospital Admission, Length of Stay
- How many people
- 80 participants
- Where
- 1 siteUnited States
- Study dates
- 3 Jan 2023to 4 Dec 2023
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- Healthy volunteers accepted
- Adult, Older 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.
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Evaluation of Emergency Department AI Prediction Algorithm
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.
- Conditions
- Hospital Admission, Length of Stay
- Keywords
- AI Prediction Algorithm, Emergency Department
- Medical subject headings
- Emergencies
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Group A | 141 days with AI scores displayed | |
| Group B | 141 days with AI scores not displayed |
What is being measured
The primary outcome is the main question the study is designed to answer.
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
Measured: 282 days
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Jan 2023
- Study start3 Jan 2023
- Primary completion4 Dec 2023
- Study completion4 Dec 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Hospital AdmissionStudies of the same condition, open and under way.
- More trials run by Mayo ClinicThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 80 participants (actual)
Sponsor and investigators
- Lead sponsor
- Mayo Clinic
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Alexander J. Ryu, Mayo Clinic
- Investigators
- Alexander Ryu, MD, Principal investigator, Mayo Clinic
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05683899
- Sponsor's protocol ID
- 22-011319
- Status last verified
- Apr 2024
- First submitted
- 5 Jan 2023
- Last updated
- 5 Apr 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
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;17(1):6337. doi: 10.1038/s41467-026-72960-1.
PubMed 42120428
Study at a glance
From the registry record, last updated by the sponsor on 5 Apr 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation of Emergency Department AI Prediction Algorithm
- ClinicalTrials.gov ID
- NCT05683899
- Acronym / sponsor ID
- 22-011319
- Conditions
- Hospital Admission, Length of Stay
- Keywords
- AI Prediction Algorithm, Emergency Department
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 80 participants (actual)
- Lead sponsor
- Mayo ClinicUniversity, hospital or other
- Study start
- 3 Jan 2023 (actual)
- Primary completion
- 4 Dec 2023 (actual)
- Study completion
- 4 Dec 2023 (actual)
- First posted
- 13 Jan 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Group A | – | –141 days with AI scores displayed |
| Group B | – | –141 days with AI scores not displayed |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older 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.
Key inclusion criteria (2 listed)
- 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.
Key exclusion criteria (2 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Hospital Admissions
Time frame: 282 days
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
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 5 Apr 2024.
- Derived from this study: PubMed 42120428Ryu 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;17(1):6337. doi: 10.1038/s41467-026-72960-1.
- Mayo Clinic Clinical TrialsLink provided by the sponsor.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Alexander Ryu, MD principal investigator
Mayo Clinic
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Hospital Admission and Length of Stay, run by Mayo Clinic at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 5 Apr 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Hospital Admissions (time frame: 282 days). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05683899, which also lists 1 linked publication.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 5 Apr 2024.