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The purpose of this study is to evaluate the effectiveness and user satisfaction of the study teams early warning system, called PICTURE, which utilizes artificial intelligence (AI) techniques and algorithms to identify patient deterioration on pediatric units within Mott Children's Hospital.
In this pilot study the patient care team will review the PICTURE information and alerts. Morning rounds will be partially informed by the PICTURE scores and the scores will be included in the hand off notes for the patients with a red score.
The primary purpose of this study is to test the hypothesis that the combination of the PICTURE-Pediatric model, the proposed workflow and the proposed interface results in at least 80% compliance.
No participants will be consented as the Institutional review board has approved a waiver of consent for THE clinicians and the patients information being reviewed.
The enrollment numbers will include only the clinicians.
Full description
PICTURE Pediatric evaluates large amounts of patient data, labs, monitored data, and vital signs (all variables that are measured as part of routine clinical care and that are stored in the electronic health record in real-time); it does this every 15-minutes and delivers a deterioration risk index score that has been shown to outperform Pediatric Early Warning Score (PEWS), and other similar scoring systems in identifying patients at risk for clinical deterioration. Clinical implementation of PICTURE Pediatric could identify patients at high risk of deterioration early enough to intervene and decrease the need for transfer to the Pediatric Intensive Care unit (PICU), and it could also reduce morbidity and hospital length of stay. This in turn could also improve bed availability for patients awaiting admission in the emergency department and improve efficient transfer out of the PICU, all of which improves care and reduces cost for the patients, their families, and the hospital system.
This protocol also does not mandate or require clinical decisions based on alerts generated (e.g. there is no mandate to transfer to the Intensive Care unit, perform an intervention, or change therapy/clinical course based on PICTURE alerts); rather, the clinical team will decide whether additional investigation, therapy, intervention, or transfer is required after alerts are generated based on staff's clinical experience, knowledge and with consultation with an attending physician when applicable. In case of device failure, there would be no deterioration risk scores generated and the clinical teams would simply continue to follow the current workflow.
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Inclusion and 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:
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
Primary purpose
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375 participants in 2 patient groups
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Central trial contact
Jay Semerad
Data sourced from clinicaltrials.gov
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