Healthcare IT News December 3, 2019
Fundamental issues related to executive support, staff buy-in and patient risk stratification need to be understood and addressed before machine learning applications can help with population health goals.
The goal of population health is to use data to identify those who will benefit from intervention sooner, typically in an effort to prevent unnecessary hospital admissions. Machine learning introduces the potential of moving population health away from one-size-fits-all risk scores and toward matching individuals to specific interventions.
The combination of the two has enormous potential. However, many of the factors that will determine success or failure have nothing to do with technology and should be considered before investing in machine learning or population health.
Is there enough incentive?
Population health software,...
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