Today I’m enjoying the New England HIMSS Spring Conference including an amazing keynote session by Dale Sanders from Health Catalyst. Next week I’ll be following up this blog post with some other insights that Dale shared at the New England HIMSS event, but today I just wanted to highlight one powerful concept that he shared:
Healthcare AI Needs a Breadth and Depth of Data
As part of this idea, Dale shared the following image to illustrate how much data is really needed for AI to effectively assess our health:
Thanks @drsanders Amazing Speaker “digitize assets.. #nomoreclicks roadmap of the future AI @HealthCatalyst @NewEnglandHIMSS @MattCBornstein @mramaloney @pat_rioux @dirkstanley @techguy @CoherenceMed @janicemccallum @sgschade @timothywong007 pic.twitter.com/2DX43moPeK
— Malissa Miot (@malissa_miot) May 17, 2018
Dale pointed out that in healthcare today we really only have access to the data in the bottom right corner. That’s not enough data for AI to be able to properly assess someone’s health. Dale also suggested the following about EHR data:
— John Lynn (@techguy) May 17, 2018
Long story short, the EHR data is not going to be enough to truly assess someone’s health. As Google recently proved, a simple algorithm with more data is much more powerful than a sophisticated algorithm with less data. While we think we have a lot of data in healthcare, we really don’t have that much data. Dale Sanders made a great case for why we need more data if we want AI to be effective in healthcare.
What are you doing in your organization to collect data? What are you doing to get access to this data? Does collection of all of this data scare anyone? How far away are we from this data driven, AI future? Let us know your thoughts in the comments.