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Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
Technology Matters: Emerging technologies in clinical informatics to support child and adolescent mental healthcare
Juliet Beni Edgcomb1, Bonnie T Zima1
1Mental Health Informatics & Data Science (MINDS) Hub at the Center for Community Health, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles (UCLA), Los Angeles, CA, USA.
Abstract:
Electronic health records (EHRs) can support patient safety across medical settings but require thoughtful adaptation to serve specialty care. This article provides an overview of how EHRs intersect with safety in child and adolescent mental health care, showcasing three distinct clinical domains: psychotropic medication safety, self-harm risk mitigation, and monitoring of restrictive measures, including involuntary detainment. While innovations demonstrate promise, challenges persist, including alert fatigue, implementation variability, nascent adaptation for child and adolescent mental health, and emerging evidence of algorithmic bias in detection of high-risk youth. The rapidly evolving landscape of EHR-interfaced artificial intelligence (subsuming ambient documentation, machine learning prediction models, and large language models) advances faster than evidence accumulation. Development of effective safety technologies requires active collaboration between child mental health clinicians/practitioners and clinical informatics teams to ensure new tools are clinically valid, evidence-based, acceptable, tailored to mental health care, and developmentally appropriate. Translation of new EHR technologies to better safety outcomes necessitates purposeful involvement of young people and their families alongside mental health clinicians.
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