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.
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AI-rewrites the medical criteria so a patient or caregiver can understand them. Always confirm with the trial site.
Compliance with the model workflow as measured by a pop-up questionnaire after each model alert aggregated as a proportion -clinicians
Timeframe: within 30 minutes after each alert during a patient's admission