HIMSS 2019
Healthcare AI Insights

Tuesday, February 19, 2019

HIMSS 2019 Recap_ Healthcare AI Insights

HIMSS is part Healthcare IT (HCIT) conference, part endurance test (because of all the walking!), and the 2019 edition that just Image from iOS (5)concluded in Orlando was no exception.  For those of us focused on Artificial Intelligence (AI) in healthcare, HIMSS is a great opportunity to meet with vendors, partners, users, leaders, and newcomers. Fortunately, the energy and attention on AI at the 2019 HIMSS was enough to carry one through several days of learning sessions, vendor booths, the Innovation Live pavilion, and more. 

I went to see what vendors and healthcare organizations are doing with AI, support our partners, and explore areas for collaboration—but I also wanted to ask a few deeper questions:

  • How, specifically, are provider organizations, HCIT vendors, governments, and others developing their AI roadmap and delivering on the promise of healthcare AI?
  • What are CIOs doing to incorporate AI into their technology plans—from AI projects to full-blown AI-centric strategies?
  • Who can demonstrate significant value from AI solutions use cases in healthcare?
  • What about the responsible use of AI? Is this on the roadmap of healthcare organizations and HCIT vendors?
Jeff at our partner Cognizant's booth at HIMSS 2019

Broad Adoption of Healthcare AI...and Plenty of Buzz
The conference confirmed that there are many healthcare organizations focused on AI. There are numerous early stage healthcare AI vendors, as well as legacy HCIT vendors, adding AI to their solution set; there are many healthcare provider and payer organizations leveraging AI; and, the broader healthcare IT ecosystem—including government, consumer electronics vendors, investors, incubators, and consultants—are all incorporating AI into their solutions and services. Not surprising!  

Large Number of Use Cases, Good Discussion of Value
HIMSS 2019 demonstrated that “Healthcare AI” is a very broad topic. One, there are countless healthcare AI use cases_ clinical, financial, administrative, operational, and more. Two, there are a number of AI technologies that can be leveraged_ data science, machine learning, natural language processing, robotic process automation, etc. And, three, even the term “AI solution” can mean models, algorithms, chatbots, and much more. The net result is the need for a lot of clarification about who is doing what with specific technology for whom—before getting into results and value, and the broader plan for transformative AI in healthcare.

Strategic Considerations for Healthcare AI
At CognitiveScale, we are seeing CIOs across numerous industries starting to adopt AI as a source of competitive advantage and differentiation, in a transformative capacity for their businesses. HIMSS 2019 showed that many more CIOs—and their HCIT vendors—are starting to elevate AI from “useful technology” (e.g. “use machine learning to convert my paper EOB (Explanation of Benefit) into an electronic remittance advice”) to a strategic enabler.  As more of these trials start to pay off, CIOs will start realizing that they need more than one-off solutions. However, much more needs to be done when it comes to deployment of healthcare AI platforms at scale. Another key strategic imperative going forward will be Responsible AI. Data ownership issues in healthcare are topical, e.g. high-level government officials, and others point to the need for patients to own their own data; but transparency, explainability, accountability, and fairness need to be thought about, as well.

Miles to Go...Some Challenges Highlighted
It can be daunting to understand which part of “Healthcare AI” is most applicable or valuable, and consequently, it is challenging to know where to focus, let alone how to develop a healthcare AI roadmap.  (Stay tuned to this space for a series on “Healthcare AI Roadmaps”). While there was a lot of discussion on various solutions and technologies, there were not enough conversations on comprehensive AI plans at an organizational level, or healthcare AI platforms that would enable these plans. In a number of cases, AI projects were being explored by innovation teams or internal consultants vs. being managed by IT—either of which is fine, but often ‘special AI projects’ are not yet core components of IT roadmaps.

In a Nutshell
HIMSS 2019 established that AI is definitely embedded across healthcare and healthcare IT.  It’s an exciting time in this market—and we look forward to helping the industry continue to harness the AI momentum in healthcare. At CognitiveScale we are working with a number of largest payer and provider organizations on everything from healthcare AI roadmaps and priorities to the development and deployment of valuable, practical, scalable, and responsible AI healthcare solutions. We look forward to elaborating on these topics—on this forum—and especially in discussion with you!

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