As healthcare organizations move toward taking on greater financial risk for keeping people healthy, it is critical for organizations to match people to the interventions they’re most likely to benefit from.
These days, every care management / value-based care organization has a risk score to help target interventions. Unfortunately, these risk scores often frustrate clinicians by directing them to people who cannot benefit from an intervention – either the person is not actually headed for trouble, or the clinician already knew about that person.
Healthcare is notorious for its lack of consistent and widely adopted data formats. The one consistent exception is the billing information exchanged between payors and providers.
Today, June 12, 2017, Children’s Mercy Kansas City, Joslin Diabetes Center, Cyft Inc., and The Leona M. and Harry B. Helmsley Charitable Trust are proud to announce the creation of a new learning health system to improve the care of individuals diagnosed with type 1 diabetes (T1D).
Cyft is pleased to recognize the publication of three peer-reviewed studies by leading health services researches that used the research precursor to Cyft to address important clinical questions.
With 30 percent of Medicare payments expected to be tied to alternative payment models and bundled payments by the end of 2016, the pressure is on for healthcare leaders still struggling to align their organizations with the idea of value-based care (VBC).
Healthcare IT News wrote a great piece encapsulating Len’s thoughts and those of his fellow presenters; all who sought to explain the potential impact of machine learning on healthcare.