AI-Augmented Clinical Decision Support For Behavioral Escalation Management In Autism Spectrum Disorder

Abstract

Children and adults with Autism Spectrum Disorder (ASD) are frequently subject to behavioral escalation events that can overwhelm families and clinical teams. Traditional escalation management strategies involve clinician expertise and subjective observation, and may result in delayed or inconsistent responses. This research proposes an artificial intelligence (AI) augmented clinical decision support system (CDSS) in order to predict, detect, and control escalation risks in ASD. The system uses multimodal data from wearable sensors, electronic health records and behavioral observations to produce de-escalation prompts in real-time. Pilot simulation shows 22% fewer incidents of crisis and more confident clinicians in escalating crises. These findings emphasize the potential of AI-enhanced decision support for revolutionizing behavioral care in ASD and remaining compliant with safety and privacy frameworks.