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AMIA details policy framework for AI/ML-driven decision support

Press releases may be edited for formatting or style | February 15, 2021 Artificial Intelligence Business Affairs

The position paper identifies two categories of Adaptive CDS that warrant distinction for purposes of establishing public policy. First, Adaptive CDS that is sold to customers for use in a healthcare setting is referred to as Marketed ACDS. Second, Adaptive CDS that is developed in-house by healthcare systems and not marketed or sold to others is referred to as Self-Developed ACDS. Marketed ACDS is subject to FDA oversight per the 21st Century Cures Act and related FDA interpretation. Self-Developed ACDS is likely unregulated by any federal entity and is already used routinely without oversight by any authoritative body – public, private, or non-profit.

"The current policy and oversight landscape for Adaptive CDS is inadequate," said Joseph Kannry, MD, AMIA Policy Committee Chair and paper author. "Gaps in federal jurisdiction of Adaptive CDS have left patients subject to algorithmic bias and potentially exposed to patient safety issues. In this paper we present a policy framework that spans the design and development, implementation, evaluation, and on-going maintenance of Adaptive CDS."

First, transparency in how Adaptive CDS is trained is paramount. Without transparency, there can be no accountability. Specifically, the framework requires transparency standards for how algorithms are trained, including the semantics and provenance of training datasets are necessary for validation prior to deployment. Additionally, transparency into the data acquisition process, selection criteria of cohorts, and descriptions and prevalence of attributes likely to influence how a model may perform on new data are needed. "These choices mark the venues where bias can be introduced," the paper notes.

Second, communications standards to convey specific attributes of how the model was trained, how it is designed, and how it should operate in situ are needed to objectively compare, evaluate, and guide ongoing maintenance of the algorithm. A range of questions regarding the intended use and expected users of Adaptive CDS must be addressed in a consistent manner, and product labeling regulations, such as those used by the FDA to explain prescription drugs, provide relevant correlates. For instance, FDA labeling requirements include concepts such as: indications and usage; contraindications; warnings & precautions; interactions; adverse reactions; and use in specific populations. Adaptive CDS may not be useful in specific clinical settings or for specific clinical purposes, so such standards for communicating how a clinician should apply Adaptive CDS are needed.

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