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

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

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

Medicaid State Funding: Thriving Under Value-Based Care in the Face of Upcoming Changes

By now it’s no secret that president-elect Donald Trump intends to vastly restructure our Medicaid Program, meaning that uncertainty is on the horizon for healthcare providers supplying care to over 80 million low-income Americans. Georgia Congressman Tom Price will lead the US Department of Health and Human Services (HHS) under Trump, with many estimating that Medicaid could soon change from

By | December 5th, 2016|Value-Based Care|

Dartmouth Researchers Detect Falls Without the Data Scientists

We learned that a team of health services researchers at Dartmouth College recently published a study in the Journal of Patient Safety using an early research version of Cyft to detect falls in inpatient notes.  No one on their research team is a data scientist and using a relatively small sample size they outperformed previous efforts at this task by

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