IBM Watson Health and MAP Health Management, a population health software maker, have teamed up to create new software that uses cognitive computing to treat long-term addiction and substance abuse.
The new version of the MAP Recovery Network platform is driven by IBM's Watson technology, which adds cognitive computing and machine learning to the population health software, allowing it to process unstructured data and to learn as it goes, thereby becoming more and more accurate.
The software identifies patients who are most at risk of relapse so they can be treated before that happens. This kind of approach is especially relevant as healthcare systems move from fee-for-service to value-based models, as it allows them to target those most in need of treatment when they most need it and keep track of long-term outcomes—something that's sorely missing from current treatment models, according to MAP.
"There's far more unstructured data in the addiction treatment space than structured data," said Jacob Levenson, CEO of MAP Health Management. "This enhanced version taps a new dimension of data and allows us to assess risk much more efficiently and accurately."
That's a boon for users of the platform—addiction treatment providers, care managers and insurers, including Aetna Behavioral Health.
This is not IBM's first foray into population health. In October 2016, for instance, IBM and Siemens announced a population health partnership that will, the companies say, help hospital systems transition to value-based care, and in December 2016, IBM announced it would work with Cleveland Clinic for clinical decision support.
