ViVE 2023: 5 takeaways on ChatGPT, data privacy and more

Digital health companies and investors flocked to Nashville, Tennessee, this week for the second annual ViVE conference. Hot topics among the crowd of 7,500 included concerns about “creepy”, the economy and whether ChatGPT is as good as it’s made out to be. Here were the five takeaways.

1. Everyone wants to talk about ChatGPT.

Potential of Generative AI Applications Like ChatGPT and GPT-4 in healthcare was the main topic of conversation. Attendees had two schools of thought on the potential of ChatGPT in healthcare, which were summed up well by Mickey Tripathi, head of the Office of the National Coordinator for Health Information Technology.

“I think we all feel tremendous excitement and you also want to feel tremendous fear,” Tripathi said.

Michael Haselberg, chief digital health officer at the University of Rochester Medical Center in New York, said he believes in the power of generative AI. ChatGPT developer OpenAI’s big language AI models are “light years ahead” of data seen in the market from various startups Automating health care administrative and revenue cycle processes.

“It’s very easy to use. I have no formal training as a computer scientist and I can program with OpenAI,” Haselberg said. “I can very quickly spin up an application that can solve a lot of the problems my employees are sitting on top of right now. Before that I was looking at all these companies to try to solve [those problems] For me.”

Hasselberg and Steve Krause, partners at venture firm Bessemer Venture Partners, both said AI models have great potential in automating processes such as pre-authorization.

but there was a fair share of skepticism And even the fear of generative AI models. Tripathi said that when used inappropriately, algorithms can perpetuate health equity and quality issues. Tom Cassells, CEO of Rock Health’s advisory and consulting arm, agreed.

what are dangerous [digital health companies] that touch clinical practice and are looking at bringing big data models using existing biased medical guidelines and information,” Casals said.

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