What’s ‘next chapter’ in HME data?

PORTLAND, Maine – A dearth of data makes it difficult for the HME industry to fully leverage AI and other developing technologies, so it may have to shift its focus, according to a panel of vendors at the HME News Business Summit in October. 

Because personal health information is protected and because HME companies are typically smaller in size – “No organization here has enough data to feed a large language model,” said Dr. Charlotte Lawson, CEO and co-founder of Darby – the industry should collectively focus on building a small language model, with AAHomecare or another organization taking the lead. 

“That’s my hot take,” said Lawson, who also still practices emergency medicine. “That way you can feed your data (into an SLM) that enhances an LLM.” 

Lawson was joined on the panel, which was moderated by Josh Marx, CEO of Medical Service Company, by Craig Thompson, general manager of Tomorrow Health; Steve Cela, founder and president of Strategic Office Support; and Justin Mortara, CEO and president of EnsoData. 

Mortara agreed this is the “next chapter,” saying HME providers are making strides in automating what they already do – document wrangling, for example – but they need to do more to leverage AI to help them do things they’re not already doing. 

“You need to allow AI to see what we don’t see,” he said. “Language models can look across dimensions.” 

But panelists agreed that before the industry can work toward even an SLM, it needs to standardize its data. That’s a big goal of Tomorrow Health’s, Thompson said, especially knowing that payers consider HME data “a black box.” 

“That would be really powerful,” he said. 

Other highlights from the panel: 

Buy or build: For many providers, building technology to improve their efficiency isn’t an option, so their focus should be on finding the right partner. But they also want to make sure they don’t buy it and forget it. “You need to maintain it and you need to customize it, so you’re not adapting to the platform, the platform is adapting to you,” Mortara said. 

Inside the box: While much of the conversation focused on thinking outside of the box, panelists said it’s also important to look inside the box. “Financials and analytics are so complicated,” Cela said. “Being able to see where you make money is huge. We even had a client recently who hired a data analyst. Think about that.”