Cyft | Blog

Where Will AI Increase & Decrease Costs in Healthcare?

I asked LinkedIn friends to submit their questions related to AI in healthcare in preparation for an upcoming keynote at this year's HIMSS in Vegas. I promised to try to answer the questions they submitted. This one is courtesy of my friend, the great Aman Bhandari and it garnered the most "likes." Here's his question: "I have asked for this several times and haven't

By | November 27th, 2017|Categories: Analytics, Machine Learning, Real World Applications, Value-Based Care|

Thoughts on JAMA’s “Adapting to Artificial Intelligence” by Jha and Topol

When journalists write about the disruptive power of artificial intelligence in healthcare they tend to zero in on radiology and pathology and for good reason. Both trades involve the interpretation of patterns from quantifiable image data - a thing that AI has proven highly capable of in several studies and commercial applications from facial recognition to the classification of hotdogs.

By | November 22nd, 2017|Categories: Analytics, Machine Learning|

7 Ways We’re Screwing Up AI in Healthcare

The healthcare AI space is frothy.  Billions in venture capital are flowing, nearly every writer on the healthcare beat has at least an article or two on the topic, and there isn’t a medical conference that doesn’t at least have a panel if not a dedicated day to discuss. The promise and potential is very real.And yet, we seem to

By | September 14th, 2017|Categories: Analytics, Machine Learning, Real World Applications, Value-Based Care|

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 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. This has traditionally been done by applying risk scores that are based on

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|
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