The subsequent piece is a guest post authored by Tejaswani Veerni, a Business Intelligence Developer at UI Health. AI is desired by all health systems. Dialogue concerning its implementation occurs at all levels, from top executives to the analytics department.
However, those who genuinely deal with healthcare data understand the barrier that hinders many discussions, and this barrier is PHI. Protected health information is not insignificant; it serves as a significant obstacle. Every choice made by a healthcare data team is influenced by it.
Many AI tools available today were not designed with the responsibility to fill that gap in mind. The existence of this compliance gap is undeniable. When attempting to implement a universal AI tool on genuine patient information, the same issue arises.
Many AI solutions used in businesses were not created to manage PHI, they were not developed in accordance with HIPAA, and they lack the necessary compliance features that healthcare demands. Involving patient data that can be identified, even unintentionally, constitutes a breach.
For numerous analytics teams, particularly in smaller establishments, the most secure course of action has been to exclude AI altogether.
