PICTURE-Pediatric for Clinical Deterioration
What You Need to Know Before You Apply
What is the purpose of this trial?
This trial tests a new AI system called PICTURE-Pediatric, designed to help doctors at Mott Children's Hospital detect early signs of a child's health deterioration. The system sends alerts when it identifies potential issues, aiming to improve care during hospital stays. The trial compares periods when doctors use PICTURE alerts with periods when they do not. It targets patients aged 30 days to 25 years on the general care wards. Participants do not need to provide consent, as the study focuses on clinician use of the system. As an unphased trial, this study offers a unique opportunity to contribute to innovative healthcare solutions that could enhance pediatric care.
Will I have to stop taking my current medications?
The trial information does not specify whether participants need to stop taking their current medications.
What prior data suggests that the PICTURE early warning system is safe for use in pediatric units?
Research has shown that the PICTURE-Pediatric system uses computer programs to predict if a child's health might worsen in the hospital. As a computer system, not a medicine or device, it poses no physical side effects or direct risks to patients. The system analyzes electronic health records to alert doctors and nurses early if a child's condition changes, enabling healthcare teams to act quickly to address potential problems.
Safety concerns for this system focus on its accuracy and reliability. The emphasis is on how well the system identifies real issues without causing unnecessary worry. Current studies aim to ensure the system's alerts are accurate and helpful for healthcare providers, supporting rather than disrupting patient care.1234Why are researchers excited about this trial?
Researchers are excited about the PICTURE-Pediatric system because it introduces a proactive way to monitor clinical deterioration in children. Unlike other methods that might rely on periodic checks or subjective assessments, PICTURE-Pediatric offers real-time scores and alerts, potentially allowing for quicker interventions. This system could transform how healthcare providers respond to changes in a child's condition, aiming to catch and address issues before they become critical.
What evidence suggests that the PICTURE system is effective for identifying patient deterioration in pediatric units?
Research shows that the PICTURE-Pediatric system uses artificial intelligence (AI) to predict when hospitalized children might worsen. Studies have found that AI monitoring can reduce emergency calls by almost 40% in some cases. This enables doctors to detect problems early and assist children before their condition becomes serious. In this trial, one group will receive PICTURE-Pediatric scores and alerts, which draw from electronic health records to notify doctors and nurses about a child's health status. This method has improved care and outcomes in hospitals. Early results suggest that PICTURE can be a valuable tool for enhancing children's safety in the hospital.24567
Who Is on the Research Team?
Rodney Daniels
Principal Investigator
University of Michigan
Are You a Good Fit for This Trial?
This trial is for healthcare teams at Mott Children's Hospital. It focuses on clinicians who manage pediatric patients and will involve using an AI-based early warning system to detect patient deterioration without needing consent from the clinicians or patients.Inclusion Criteria
Exclusion Criteria
Timeline for a Trial Participant
Screening
Participants are screened for eligibility to participate in the trial
Control Arm
During the control arm, the PICTURE scores and alerts will not be shown.
Experimental Arm
PICTURE-Pediatric scores and alerts are shown to the clinical team.
Follow-up
Participants are monitored for compliance and acceptability of the intervention.
What Are the Treatments Tested in This Trial?
Interventions
- PICTURE-Pediatric
Trial Overview
The PICTURE-Pediatric system, which uses artificial intelligence to predict clinical deterioration in children, is being tested. Clinicians' compliance with the system's alerts during morning rounds and handoffs is measured against a control arm where these alerts are hidden.
How Is the Trial Designed?
2
Treatment groups
Experimental Treatment
This arm will happen for two four-week periods.
During the control arm, the PICTURE scores and alerts will not be shown. This arm will happen for two four-week periods.
Find a Clinic Near You
Who Is Running the Clinical Trial?
University of Michigan
Lead Sponsor
Citations
PICTURE: Pediatric General Floor Deterioration Prediction
PICTURE is a suite of machine learning algorithms that utilize electronic health record (EHR) data to predict patient deterioration in hospital ...
PICTURE-Pediatric for Clinical Deterioration
The purpose of this study is to evaluate the effectiveness and user satisfaction of the study teams early warning system, called PICTURE, ...
3.
childrenshospitals.org
childrenshospitals.org/news/childrens-hospitals-today/2024/07/using-ai-to-forecast-patient-deteriorationUsing AI to Forecast Patient Deterioration
A predictive tool to identify trends and stay ahead of deterioration reduced crisis response calls by nearly 40% in an acute care unit.
4.
journals.lww.com
journals.lww.com/ijebh/fulltext/9900/early_detection_of_clinical_deterioration_in_a.197.aspxEarly detection of clinical deterioration in a pediatric...
The results of clinical outcomes and staff outcomes are summarized in Table 4. The follow-up audit showed improved compliance with best ...
5.
publications.aap.org
publications.aap.org/pediatrics/article/152/4/e2023061625/193910/The-Need-for-a-Standard-Outcome-for-ClinicalThe Need for a Standard Outcome for Clinical Deterioration ...
In this article, we compare existing outcomes for evaluating clinical deterioration outside of the ICU, highlighting sources of variation and vulnerability.
PICTURE: Pediatric General Floor Deterioration Prediction
PICTURE is a suite of machine learning algorithms that utilizes electronic health record (EHR) data to predict patient deterioration in hospital settings.
Signal detection for pediatric patient deterioration with ...
This reflects a developmental stage in clinical reasoning where learners may focus on isolated indicators rather than synthesizing a complete clinical picture.
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