KevinMD June 4, 2025
Physician executive Jay Anders discusses his article, “Health care’s data problem: the real obstacle to AI success.” Jay asserts that the transformative potential of artificial intelligence in health care is fundamentally dependent on the quality of the underlying clinical data. He explains that while tools like large language models and conversational AI show promise in synthesizing information and easing documentation, their reliability is compromised when fed with data from repositories often filled with inconsistencies, errors, and gaps. This can lead to an “increased workload paradox,” where clinicians spend more time verifying and correcting AI-generated outputs, and a failure to produce the structured data vital for regulatory compliance, quality metrics, and analytics. Jay emphasizes that the “garbage in, garbage out” principle...
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