On Demand: Digital Health and AI in 2026: Coding, Compliance and Revenue Opportunities-Webinar Recording

Video Transcription

Video Summary

In this session of the boot camp on digital health and AI, Nicole Knight, leader of revenue cycle and care transformation, explores the rapid integration of AI technologies and digital health services within cardiovascular care revenue cycles. The discussion begins with definitions of AI-related terms—machine learning, deep learning, and generative AI—and highlights AI's transformative impact on coding, documentation, and reimbursement processes. The session addresses potential risks including bias, hallucinations (incorrect AI outputs), overreliance, distrust, liability, unintended use, data drift, and data sharing concerns.<br /><br />Knight emphasizes the importance of human oversight in AI-assisted coding and documentation, warning of common "danger zones" like misinterpretation of codes, anatomy, or medical necessity narratives. AMA’s CPT coding guidelines for AI categorize applications as assistive (machine detects data), augmentative (machine analyzes data), and autonomous (machine independently interprets/generates conclusions), with ongoing challenges for valuation and reimbursement under CMS guidelines. The rapid growth of AI technologies challenges the sustainability of current Medicare fee schedules due to budget neutrality constraints.<br /><br />The session then shifts to telehealth updates for 2026, including the permanent adoption of virtual direct supervision via real-time audiovisual communication but the expiration of many pandemic-era flexibilities (e.g., at-home telehealth for beneficiaries after January 30, 2026). Legal considerations about medical licensure across state lines and best practices related to place of service and documentation are covered.<br /><br />Finally, Knight reviews expanded digital health services including remote patient monitoring (RPM), virtual check-ins, interprofessional consults, and chronic care management codes, emphasizing operational considerations like patient consent, out-of-pocket costs, thorough documentation, and clinical staff roles. She underscores the need for coding professionals to stay informed, start small with AI implementations, involve operational experts, and maintain compliance with regulatory standards. The session concludes by encouraging peer-to-peer sharing of AI integration experiences and anticipation of future discussions on PCI coding.

Keywords

digital health

artificial intelligence

cardiovascular care

revenue cycle management

AI coding

machine learning

telehealth 2026

remote patient monitoring

CPT coding guidelines

Medicare reimbursement