Introduction
Effective May 1, 2025 [1] [2], healthcare providers are required to implement measures to identify and mitigate discrimination risks associated with the use of artificial intelligence (AI) and other technologies in patient care [1] [2]. These technologies often incorporate sensitive input variables such as race, color [1] [2], national origin [1] [2], sex [1] [2], age [1] [2], or disability [1] [2], which necessitates careful evaluation to prevent potential biases.
Description
Effective May 1, 2025 [1] [2], covered healthcare providers are mandated to implement reasonable measures to identify and mitigate discrimination risks associated with the use of AI and other technologies in patient care that incorporate race [1] [2], color [1] [2], national origin [1] [2], sex [1] [2], age [1] [2], or disability as input variables [1] [2]. The assessment of whether a provider has taken adequate steps to address these risks will be influenced by factors such as the provider’s size and resources [1] [2], the specific application of the AI tool [1] [2], any customization performed [1] [2], and the evaluation processes established for detecting potential discrimination [1] [2].
Providers are required to establish a systematic approach for evaluating AI tools used in patient care [2], both prior to acquisition and on an ongoing basis [1] [2]. This evaluation must determine if the AI tool utilizes sensitive input variables and assess the availability of information regarding potential biases or discrimination [1] [2]. Engaging with the tool’s developer or vendor for further insights is also recommended [2].
In cases where an AI tool is identified as having potential bias or discrimination risks [1] [2], providers should implement strategies to mitigate these issues [1] [2], including educating staff about the risks and establishing best practices for tool usage [2]. Additionally, provider policies must outline procedures for patients and staff to report concerns related to bias and discrimination in AI tool usage [1] [2], along with the processes for addressing such complaints [1] [2].
Conclusion
The implementation of these measures is crucial for ensuring equitable patient care and maintaining trust in healthcare systems. By proactively addressing potential biases in AI tools, healthcare providers can enhance the quality of care and safeguard against discrimination, ultimately fostering a more inclusive and fair healthcare environment.
References
[1] https://www.jdsupra.com/legalnews/ep-58-addressing-potential-6875069/
[2] https://www.dentonshealthlaw.com/addressing-potential-discrimination-in-patient-care-decision-support-tools-episode-58/
