Technological advancements have the potential to greatly improve patient outcomes and reduce costs in healthcare. Artificial intelligence, or AI, has been getting a lot of attention in the past few years as something with the potential to improve many aspects of diagnosis, treatment, and administration. Some may think we’re at the peak of what Gartner calls a hype cycle which must be navigated before we can realize any true benefits from AI.
The hype cycle is a model representing the typical progression of a technology from inception to maturity. The cycle consists of five stages: the technology trigger, the peak of inflated expectations, the trough of disillusionment, the slope of enlightenment, and the plateau of productivity. The healthcare industry has seen numerous examples of technologies that have followed the hype cycle from electronic health records to telemedicine to connected consumer health devices.
We agree that AI in healthcare is at or near the peak of inflated expectations. There is a great deal of excitement about the potential of AI to transform healthcare and many companies are investing heavily in the technology. However, there are also significant challenges associated with AI in healthcare that must be addressed for these efforts to be successful. The trough of disillusionment is certain and will occur as the enthusiasm for the technology encounters the very real limitations around its safe and effective use.
Our Data Governance Collaborative regularly looks at some of the issues around AI use in healthcare, particularly as it pertains to regulatory activity and industry discourse. Transparency issues, biases at various stages of development and use, lack of deep knowledge among both patients and healthcare professionals, and more are waiting to drag us down into the trough of disillusionment Hopefully we can wade through these issues and come out on the other side, work our way up the slope of enlightenment, and find our way toward a useful steady state grounded in realistic understanding rather than irrational exuberance. Let’s work together to reach Gartner’s plateau of productivity.
Interested in more on AI? Check out our monthly feature discussing our little experimentation with ChatGPT, and let us know how you have used it.
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Updates
We finalized our comment on the CMS Attachments NPRM and submitted it to CMS prior to the April 21 deadline. It focused on two major areas: coordination of rules and adding support for FHIR as both a data format and exchange mechanism. You can find a copy HERE.
ONC released a proposed rule covering new health IT certification requirements, changes to information blocking, and more on April 18.
We recently received a stark reminder that no one is immune from cyberattacks with the news about a successful attack on our largest NEHEN payer, Point32Health (Point32Health combines Tufts Health Plan (THP) and Harvard Pilgrim Health Care (HPHC) into a single entity). At the time of this writing, NEHEN is working closely with Point32Health and our technical services provider, Cognizant/TriZetto, to bring services back online for members.
Join us for our next Spotlight demo featuring health outcomes from the Lown Institute data. We will introduce Spotlight to those who aren’t familiar with it and then dive into the rankings such as clinical outcomes, satisfaction, and safety. Register HERE to join us on May 25 at 2pm to learn more.
AI and machine learning are all over healthcare (and everywhere else) these days. ONC discusses its use in clinical decision support in their latest proposed rule. The FTC devoted large sections of its RFI on data surveillance and privacy to it. To some, it seems like a magic solution to a lack of time, resources, and expertise. To others, it's still mired in the traditional science fictional evil overlord taking over stereotypes. In truth, it's both and neither, a promising technology that isn't quite ready for prime time but that can be useful when used cautiously, judiciously, READ MORE...
The regulatory timeline chart has a new home. Click HERE
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