AI that identifies undiagnosed cognitive impairment could improve VBC

A statistical analysis evaluated a refit of the Dementia AlgoRithm, which helps determine patients at risk for cognitive decline, using administrative claims data. It found the new models could be a game-changer for value-based care providers.

A new report by Milliman concluded that, after it tested the impact of various modifications to Together Senior Health’s Dementia AlgoRithm, new claims-sourced models demonstrated positive predictive value to support quality care.

WHY IT MATTERS

Together, part of Linus Health, developed its proprietary cognitive-impairment identification and stratification algorithm – validated using electronic health record data – to help find patients with elevated risks for undiagnosed Alzheimer's disease, dementia and cognitive decline.

“RADAR offers payers and providers a quick, highly efficient method for identifying their patients with the highest risk of having undiagnosed dementia,” Deborah Barnes, cofounder of Together, said in the report announcement. “Most importantly, RADAR is highly accurate, according to the results of this thorough analysis from Milliman.”

With new RADAR models that use claims data, overall predictive performance might be twice as high as predictive mammography algorithms and three times that of predictive colonoscopy algorithms, according to Dr. John Showalter, an internal medicine physician specializing in dementia and chief strategy officer at Linus Health.

“The evidence clearly demonstrates that the gold standard for breast and colorectal cancer screenings yield predictive results on par with the refit RADAR model,” he said in a statement Tuesday. 

“RADAR, however, is far superior in that it does not require any patient time, discomfort or involvement at all, nor is it anywhere near as costly as these common, guideline-directed procedures.”

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