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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 …
Why fixing health care’s data quality is crucial for AI success [PODCAST]
As health care embraces digital transformation, one truth is clear: AI’s success depends on data quality. No matter how advanced the algorithms, poor clinical data limits their effectiveness.
AI in health care: Promise meets reality
The health care technology landscape is abuzz with large language models (LLMs) and conversational AI applications that show remarkable capabilities in synthesizing patient information and streamlining clinical workflows. Clinicians …
Health care’s data problem: the real obstacle to AI success
As a physician who grew up in a small town in central Illinois, I’ve witnessed firsthand the decline of rural health care in America. The hospital where I first became interested in medicine is now half its original size, merged with a larger health system, and struggling to stay afloat. This story is all too common across rural America, where health care access is becoming increasingly scarce, and the challenges …
Revitalizing rural health care with technology and policy
Risk adjustment is a statistical method used by health plans to predict an individual’s use of health care services and the associated cost of care. Unlike traditional fee-for-service Medicare, Medicare Advantage (MA) plans receive a flat monthly payment for the individual beneficiary’s cost of care, with payments partially based on risk score.
Higher risk scores mean higher payments, and plans have financial incentives linked to more thorough documentation (coding) of their …
Let’s focus more on caring, rather than coding
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