While AI offers tremendous potential to improve data management and streamline patient care, the technology also introduces a variety of risks that must be carefully addressed at every stage of the adoption process – from strategy and integration to change management and governance.
Although no single governance or security framework for clinical AI exists today, the World Health Organization’s (WHO) AI ethics framework provides a valuable roadmap. This framework highlights the importance of documented governance, risk management and compliance programs to mitigate a multitude of risks.
The WHO AI ethics framework offers a structured approach to managing AI-related risks in healthcare, focusing on several critical areas:
At more than 100 pages, the WHO AI ethics framework is robust. While it’s always a good idea to have a governance and security expert as part of your health system’s AI team, you don’t need to read the entire document to understand high-level themes that should be prioritized in the early stages of AI planning.
These risks specifically pertain to LLMs, a subset of AI used to assist clinical decisions, enhance patient engagement, automate administrative tasks and improve diagnostic accuracy by analyzing data and medical imaging:
In preparation for successful AI adoption, health systems must proactively address risk. The first step is understanding the most common risks, such as the fragmented landscape of AI developers and vendors. Each new AI developer and vendor increases complexity, introducing regulatory, data security and clinical alignment demands.
To address complexities, health systems should consider consolidating AI solutions on a platform that streamlines governance, risk management and compliance. The result: A clear view of risks like over-reliance and fragmented workflows, allowing for effective bias tracking and ensuring a more secure, compliant AI implementation.
By aligning with the WHO AI ethics framework and selecting a platform-based solution with a partner who adheres to global standards, health systems can manage AI’s complexities while focusing on what matters most: delivering high-quality patient care.
Get started by downloading our resource guide spotlighting selected information from the WHO AI ethics framework and the Open Worldwide Application Security Project (OWASP) AI security guidelines. Have additional questions? We’re here to help.
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