Commercial Products Using Generative Artificial Intelligence Include Ambient Scribes, Automated Documentation and Scheduling, Revenue Cycle Management, Patient Engagement and Education, and Prior Authorization Platforms.

Abstract

The integration of artificial intelligence into clinical practice is rapidly transforming health care workflows. At the forefront are large language models (LLMs), embedded within commercial and enterprise platforms to optimize documentation, streamline administration, and personalize patient engagement. The evolution of LLMs in health care has been driven by rapid advancements in natural language processing and deep learning. Emerging commercial products include ambient scribes, automated documentation and scheduling, revenue cycle management, patient engagement and education assistants, and prior authorization platforms. Ambient scribes remain the leading commercial generative artificial intelligence product, with approximately 90 platforms in existence to date. Emerging applications may improve provider efficiency and payer-provider alignment by automating the prior authorization process to reduce the manual labor burden placed on clinicians and staff. Current limitations include (1) lack of regulatory oversight, (2) existing biases, (3) inconsistent interoperability with electronic health records, and (4) lack of physician and stakeholder buy-in due to lack of confidence in LLM outputs. Looking forward requires discussion of ethical, clinical, and operational considerations.