Cyft | Blog

Rethinking How to Measure “Risk” in Healthcare

A more technical post for those evaluating risk scores for care management, coupled with a real-world example. As healthcare moves 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. This has traditionally meant using various risk scores that are based on claims data.

By | September 5th, 2017|Categories: Analytics, Real World Applications|

Risk Scores in Clinical Care- You’re Not From Around Here Are You?

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. Why is that? It turns out most

By | August 28th, 2017|Categories: Analytics|

The Dangers of Claims Based on Claims

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. These files are often referred to as “claims.” Because of their ubiquity, many of today’s analytical approaches - from epidemiology to public health, actuarial sciences, business intelligence, and risk scores - rely heavily,

By | August 21st, 2017|Categories: Analytics, Real World Applications|

What Data Scientists Need to Learn to Work in Healthcare

Data scientists like Sid Henriksen, a Ph.D. student nearing graduation, often ask me how they can succeed in healthcare. With Sid's permission, here are a few questions and insights for aspiring healthcare data scientists. How applicable is generic data science in healthcare? The core data science skillset of machine learning, data visualization, and statistics is the foundation of working with all data, healthcare

By | June 23rd, 2017|Categories: Analytics, Machine Learning|

Leading Institutions to Focus on Improving Type 1 Diabetes Care with Machine Learning

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). Starting in mid-2017, Children's Mercy and Joslin will deploy machine learning-enabled solutions to

By | June 12th, 2017|Categories: Company News, Press, Real World Applications|

Hey Machine Learning…If That’s Even Your Real Name

Hey Machine Learning, I heard what Forbes said about your “setback” at MD Anderson. I also heard rumors going around HIMSS that maybe it’s “too soon” for you to be in healthcare. At first I thought, “serves you right.” There was so much hype that I could barely recognize you. Then I realized that, in a way, we’re all to

By | March 7th, 2017|Categories: Analytics, Machine Learning, Real World Applications, Value-Based Care|
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