Pediatric ALLNCT06771830
Evaluation of Pediatric eCART Implementation
A study testing Pediatric eCART in people with Pediatric ALL and Sepsis, run by University of Wisconsin, Madison at 1 site in United States.
Trial summary
This is a study comparing 3 years of retrospective data (pre-implementation) to 2 years of prospective data after the implementation of a pediatric version of Electronic Cardiac Arrest Risk Triage (pediatric eCART), a clinical decision support (CDS) tool that uses electronic health records (EHR) to identify patients… Read more about this study
- Who is it for?
- Ages Up to 17 years
- Conditions the study is for
- Pediatric ALL, Sepsis
- What is being tested?
- Pediatric eCART
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 30,000 participants
- Where
- 1 siteUnited States
- Study dates
- 1 Dec 2025to Dec 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
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 Up to 17 years
- All sexes
- No healthy volunteers
- Child
Who may be able to join
- All pediatric patients scored on pediatric eCART (or eligible for scoring on either algorithm in the pre-implementation period) will be screened for study eligibility.
- Patients eligible for pediatric eCART scoring include pediatric (<18 years of age) patients
- Inpatient locations
- UW Health nurses who interact with eCART during patient care
Who cannot join
- Patients who are ineligible for pediatric eCART scoring
- Neonates and birth encounters will be excluded from the pediatric eCART study
- UW Health nurses no longer employed at UW Health
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
American Family Children's Hospital
Madison, Wisconsin, 53792
About this study
Official title: A Rapid Diagnostic of Risk in Hospitalized Pediatric Patients to Improve Outcomes Using Machine Learning
This is a study comparing 3 years of retrospective data (pre-implementation) to 2 years of prospective data after the implementation of a pediatric version of Electronic Cardiac Arrest Risk Triage (pediatric eCART), a clinical decision support (CDS) tool that uses electronic health records (EHR) to identify patients with high risk for life threatening outcomes. Up to 30,000 encounters with pediatric patients will be assessed. Acceptability of the pediatric eCART intervention will also be measured from pediatric nurse clinicians.
Read the detailed description
Pediatric eCART draws upon readily available EHR data and rapidly quantifies disease severity, predicting the likelihood of critical illness onset. Currently, no consistently available system continuously tracks the risk of critical illness in children admitted to UW Health. While AFCH has an implementation of Pediatric Early Warning Scores (PEWS) available for risk monitoring, internal reports indicate limited usage. Therefore, AFCH/UW Health clinicians or care providers do not have a reliable mechanism to risk-stratify patients for effective clinical decision-making.
This proposal leverages the AgileMD clinical decision support engine and a machine learning analytic developed in a dataset of over 30,000 patients. Pediatric eCART was explicitly designed to draw attention to patients at increased risk of deterioration and optimize patient management, including the timing of and need for ICU-level care.
Preliminary studies indicate that pediatric eCART implementation at the University of Chicago has led to improved outcomes. Similar improvements among children admitted to UW Health will lead to decreased morbidity and mortality among the pediatric population.
Further, a significant gap in understanding of nurse acceptance of data-driven CDS tools remains. Nurses are the largest workforce of clinicians in the health system and play a primary role in the detection of clinical deterioration as the clinicians that spend the most time observing and assessing patients; however, AI-driven CDS acceptability has not been measured to assess nurse acceptance of these emerging tools. Acceptability is essential to increase sustained use and to decrease suboptimal outcomes such as alert fatigue or increased cognitive load so that these tools ultimately mediate nurse well-being. One study assessed nurse perceptions of the usefulness of a sepsis early warning system and found that less than half of nurses perceived the alerts to be helpful and only a third of nurses reported that the alerts impacted patient care. Understanding nurse acceptance will inform AgileMD's design strategies to foster uptake and use so that predictive tools may be leveraged to improve the cognitive burden of nurse clinicians. In the end, the study will evaluate pediatric eCART on two pediatric groups: (1) screened pediatric patients; (2) pediatric nurse clinician end-users.
Study Design: This is a pre- and post- interventional study of a machine learning algorithm integrated into the electronic health record as a clinical decision support tool. The "pre" participants are hospitalized children (less than 18 years old) who were admitted to UW Health between January 1, 2022, and the date of pediatric eCART implementation in 2025. Pediatric eCART scores will be retrospectively calculated for the "pre" participants by feeding a patient's labs and vital sign observation into the pediatric eCART tool. The "post" participants are hospitalized children (less than18 years old) who will be admitted to UW Health within the two years following pediatric eCART implementation (expected 2025-2027). Pediatric eCART scores will be calculated in real-time for these patients.
- Conditions
- Pediatric ALL, Sepsis
- Being tested
- Pediatric eCART
- Keywords
- machine learning, artificial intelligence, clinical decision support, triage, electronic medical records
- Medical subject headings
- Precursor Cell Lymphoblastic Leukemia-Lymphoma, Sepsis
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Pediatric eCARTDevice
Also called electronic Cardiac Arrest Risk Triage
Integration of the pediatric version of electronic Cardiac Arrest Risk Triage as a clinical decision support tool within Epic for use by clinicians
| Study group | Role | What they receive |
|---|---|---|
| Pediatric eCART | Experimental | Not described Receives: Device: Pediatric eCART |
What is being measured
The primary outcome is the main question the study is designed to answer.
In Hospital Mortality
Measured: assessed through hospital stay (typically up to 5 days on average, but may be over 60 days)
Intensive Care Unit (ICU) free days
Defined as the number of days patients were both alive and discharged from the ICU out of the first 28 days of hospitalization. Because death is biased toward fewer ICU days and is a competing outcome, patients who die prior to day 28 are assigned with 0 ICU-free days.
Measured: up to 28 days
Secondary outcomes (6)
Median 30-day Ventilator-Free Days
Measured: assessed through hospital stay (typically up to 5 days on average, but may be over 60 days)
Summary of Critical Events
Summary of critical events, including mechanical ventilation, vasoactive administration, or death, reported by participant count.
Measured: assessed through hospital stay (typically up to 5 days on average, but may be over 60 days)
Total Hospital Length of Stay (LOS)
Reported in days
Measured: assessed through hospital stay (typically up to 5 days on average, but may be over 60 days)
Number of ICU transfers
Measured: assessed through hospital stay (typically up to 5 days on average, but may be over 60 days)
Usability of Pediatric eCART: System Usability Scale (SUS) score
SUS is a 10-item survey scored on a 5 point response scale from strongly disagree to strongly agree. Scores are transformed to a scale from 0-100 where higher scores are indicative of better system usability.
Measured: Surveys automatically sent to nurses within a week of eCART interface, responses collected up to 1 month
Acceptability of Pediatric eCART: Perceived Usefulness Scale
The Perceived Usefulness scale uses a 7-point response scale from 0 (extremely unlikely) to 6 (extremely likely) for a total possible range of scores from 0 to 36, higher scores indicate higher perceived usefulness.
Measured: Surveys automatically sent to nurses within a week of eCART interface, responses collected up to 1 month
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Jan 2025
- Study start1 Dec 2025
- Primary completionDec 2027 (estimated)
- Study completionDec 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pediatric ALLStudies of the same condition, open and under way.
- 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
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- interrupted time series approach
- Masking
- None (open label)
- Enrolment
- 30,000 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Wisconsin, Madison
- Sponsor type
- University, hospital or other
- Collaborators
- AgileMD, Inc.
- Responsible party
- Sponsor
- Investigators
- Anoop Mayampurath, PhD, Principal investigator, UW School of Medicine and Public Health
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06771830
- Sponsor's protocol ID
- 2024-1835
- Other IDs
- A531200, Protocol Version 8/3/26
- Status last verified
- Jul 2026
- First submitted
- 7 Jan 2025
- Last updated
- 13 Aug 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
- Individual data sharing
- Yes
Study at a glance
From the registry record, last updated by the sponsor on 13 Aug 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- A Rapid Diagnostic of Risk in Hospitalized Pediatric Patients to Improve Outcomes Using Machine Learning
- ClinicalTrials.gov ID
- NCT06771830
- Acronym / sponsor ID
- 2024-1835
- Conditions
- Pediatric ALL, Sepsis
- Keywords
- machine learning, artificial intelligence, clinical decision support, triage, electronic medical records
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 30,000 participants (estimated)
- Lead sponsor
- University of Wisconsin, MadisonUniversity, hospital or other
- Collaborators
- AgileMD, Inc.
- Study start
- 1 Dec 2025 (actual)
- Primary completion
- Dec 2027 (estimated)
- Study completion
- Dec 2027 (estimated)
- First posted
- 13 Jan 2025 (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.
This is a study comparing 3 years of retrospective data (pre-implementation) to 2 years of prospective data after the implementation of a pediatric version of Electronic Cardiac Arrest Risk Triage (pediatric eCART), a clinical decision support (CDS) tool that uses electronic health records (EHR) to identify patients with high risk for life threatening outcomes. Up to 30,000 encounters with pediatric patients will be assessed. Acceptability of the pediatric eCART intervention will also be measured from pediatric nurse clinicians.
Detailed description
Pediatric eCART draws upon readily available EHR data and rapidly quantifies disease severity, predicting the likelihood of critical illness onset. Currently, no consistently available system continuously tracks the risk of critical illness in children admitted to UW Health. While AFCH has an implementation of Pediatric Early Warning Scores (PEWS) available for risk monitoring, internal reports indicate limited usage. Therefore, AFCH/UW Health clinicians or care providers do not have a reliable mechanism to risk-stratify patients for effective clinical decision-making.
This proposal leverages the AgileMD clinical decision support engine and a machine learning analytic developed in a dataset of over 30,000 patients. Pediatric eCART was explicitly designed to draw attention to patients at increased risk of deterioration and optimize patient management, including the timing of and need for ICU-level care.
Preliminary studies indicate that pediatric eCART implementation at the University of Chicago has led to improved outcomes. Similar improvements among children admitted to UW Health will lead to decreased morbidity and mortality among the pediatric population.
Further, a significant gap in understanding of nurse acceptance of data-driven CDS tools remains. Nurses are the largest workforce of clinicians in the health system and play a primary role in the detection of clinical deterioration as the clinicians that spend the most time observing and assessing patients; however, AI-driven CDS acceptability has not been measured to assess nurse acceptance of these emerging tools. Acceptability is essential to increase sustained use and to decrease suboptimal outcomes such as alert fatigue or increased cognitive load so that these tools ultimately mediate nurse well-being. One study assessed nurse perceptions of the usefulness of a sepsis early warning system and found that less than half of nurses perceived the alerts to be helpful and only a third of nurses reported that the alerts impacted patient care. Understanding nurse acceptance will inform AgileMD's design strategies to foster uptake and use so that predictive tools may be leveraged to improve the cognitive burden of nurse clinicians. In the end, the study will evaluate pediatric eCART on two pediatric groups: (1) screened pediatric patients; (2) pediatric nurse clinician end-users.
Study Design: This is a pre- and post- interventional study of a machine learning algorithm integrated into the electronic health record as a clinical decision support tool. The "pre" participants are hospitalized children (less than 18 years old) who were admitted to UW Health between January 1, 2022, and the date of pediatric eCART implementation in 2025. Pediatric eCART scores will be retrospectively calculated for the "pre" participants by feeding a patient's labs and vital sign observation into the pediatric eCART tool. The "post" participants are hospitalized children (less than18 years old) who will be admitted to UW Health within the two years following pediatric eCART implementation (expected 2025-2027). Pediatric eCART scores will be calculated in real-time for these patients.
Study design
- Primary purpose
- Health services research
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- interrupted time series approach
| Arm | Type | Receives |
|---|---|---|
| Pediatric eCART | Experimental | Device: Pediatric eCART |
Who may qualify
- Ages
- Up to 17 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child
Key inclusion criteria (4 listed)
- All pediatric patients scored on pediatric eCART (or eligible for scoring on either algorithm in the pre-implementation period) will be screened for study eligibility.
- Patients eligible for pediatric eCART scoring include pediatric (<18 years of age) patients
- Inpatient locations
- UW Health nurses who interact with eCART during patient care
Key exclusion criteria (3 listed)
- Patients who are ineligible for pediatric eCART scoring
- Neonates and birth encounters will be excluded from the pediatric eCART study
- UW Health nurses no longer employed at UW Health
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Pediatric eCARTAlso: electronic Cardiac Arrest Risk TriageIntegration of the pediatric version of electronic Cardiac Arrest Risk Triage as a clinical decision support tool within Epic for use by clinicians | Device | Pediatric eCART |
Primary outcome
In Hospital Mortality
Time frame: assessed through hospital stay (typically up to 5 days on average, but may be over 60 days)
Intensive Care Unit (ICU) free days
Time frame: up to 28 days
Defined as the number of days patients were both alive and discharged from the ICU out of the first 28 days of hospitalization. Because death is biased toward fewer ICU days and is a competing outcome, patients who die prior to day 28 are assigned with 0 ICU-free days.
6 secondary outcomes
Median 30-day Ventilator-Free Days
Time frame: assessed through hospital stay (typically up to 5 days on average, but may be over 60 days)
Summary of Critical Events
Time frame: assessed through hospital stay (typically up to 5 days on average, but may be over 60 days)
Total Hospital Length of Stay (LOS)
Time frame: assessed through hospital stay (typically up to 5 days on average, but may be over 60 days)
Number of ICU transfers
Time frame: assessed through hospital stay (typically up to 5 days on average, but may be over 60 days)
Usability of Pediatric eCART: System Usability Scale (SUS) score
Time frame: Surveys automatically sent to nurses within a week of eCART interface, responses collected up to 1 month
Acceptability of Pediatric eCART: Perceived Usefulness Scale
Time frame: Surveys automatically sent to nurses within a week of eCART interface, responses collected up to 1 month
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Aug 2026.
- Individual participant dataSharing planned: Yes
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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.
Anoop Mayampurath, PhD principal investigator
UW School of Medicine and Public Health
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Pediatric eCART in people with Pediatric ALL and Sepsis, run by University of Wisconsin, Madison 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 4 inclusion and 3 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: looking for participants now, as of the sponsor's last update on 13 Aug 2026. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Anoop Mayampurath, PhD (608-261-1028, mayampurath@wisc.edu), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
In Hospital Mortality (time frame: assessed through hospital stay (typically up to 5 days on average, but may be over 60 days)). The study lists 2 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 13 Aug 2026.