Ambient technology in epilepsy clinical practice

Area of Science:

• Neurology
• Clinical Informatics
• Artificial Intelligence

Background:

• Large language model-based artificial intelligence (AI) is emerging as a tool in neurology for tasks like patient scheduling and preliminary result interpretation.
• Ambient AI models offer potential for automating clinical documentation in epilepsy care, addressing physician burnout and improving patient experience.

Purpose of the Study:

• To examine the challenges, risks, and practical considerations of applying ambient intelligence (AmI) documentation tools in outpatient epilepsy clinics.
• To highlight the importance of human oversight in the deployment of AI for clinical documentation.

Main Methods:

• Review of current applications of ambient AI in clinical practice for documentation.
• Analysis of potential benefits, risks, and practical considerations for epilepsy clinics.

Main Results:

• AmI models show promise in enhancing clinical documentation efficiency and potentially reducing provider burnout.
• Critical concerns include potential model biases, risk of errors in electronic health records, and unintended consequences.

Conclusions:

• Careful regulation, ongoing performance monitoring, and robust safeguards are essential for the safe deployment of AmI in epilepsy care.
• Collaborative efforts between clinicians, informatics professionals, AI developers, and regulatory bodies are needed to ensure patient safety and maximize benefits.