The rise of AI in healthcare has introduced new efficiencies but also new uncertainties. As hospitals look to streamline clinical documentation, many are beginning to incorporate AI into the medical record process. While this hybrid approach offers speed and convenience, it also brings critical compliance and regulatory challenges.
A June 9 blog post by Coronis Health breaks down some of the primary concerns around AI and how organizations can prepare for the future.
Three takeaways:
1. AI use without critical guardrails
Some providers are leveraging AI tools like ambient listening to help complete patient records. While this practice is becoming more common, federal and state guidance on its legality and appropriateness is still developing. Research from Johns Hopkins Medicine also shows the regulatory frameworks to use AI in a safe, ethical and equitable way are still being developed.
2. New legislation may limit AI-generated documentation
In March, Arkansas introduced legislation (House Bill 1816) aimed at restricting the use of AI in healthcare services and medical record generation unless specific safeguards are in place. As more states evaluate the risks and benefits of AI-assisted documentation, additional regulatory action may follow.
3. HIPAA compliance concerns
Many popular AI documentation tools store inputs and outputs in the cloud. While this supports data storage and application access, it also means patient data may reside on third-party servers. Healthcare attorneys caution that any storage of protected health information (PHI) in the cloud requires a business associate agreement (BAA). However, not all AI applications offer BAAs in every pricing tier—potentially putting providers at risk. Organizations using AI for medical record creation must confirm that their vendors are HIPAA-compliant and that a BAA is in place. Without these safeguards, providers risk violating privacy laws.
The post Cloud, compliance & clinical notes: 3 takeaways on AI in documentation appeared first on Becker’s ASC.
