Health systems are using machine learning to predict high-cost care. Will it help patients?

Ideally, machine learning can help health systems, payers, and social workers understand which patients have the highest need and bolster resources for those populations.

Health systems and payers eager to trim costs think the answer lies in a small group of patients who account for more spending than anyone else.

If they can catch these patients — typically termed “high utilizers” or “high cost, high need” —  before their conditions worsen, providers and insurers can refer them to primary care or social programs like food services that could keep them out of the emergency department. A growing number also want to identify the patients at highest risk of being readmitted to the hospital, which can rack up more big bills. To find them, they’re whipping up their own algorithms that draw on previous claims information, prescription drug history, and demographic factors like age and gender.

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