Eric Lefkofsky, CEO of health care technology company Tempus, discussed health care’s data dilemma on Wednesday during Fortune’s Brainstorm Health online conference. 

Researchers are hopeful about using machine learning techniques to analyze medical data like patient records, which could help doctors better treat patients by knowing how they’ll likely respond to certain therapies. However, health care data can be disorganized, making it difficult for data-crunching technologies to analyze it.

“There are so many brilliant minds surrounding health care, but they have, for whatever reason, chosen to not clean out their data warehouse,” Lefkofsky said about the problem of “dirty” data.

He equated cleaning health care data to “mowing lawns,” in that it’s “not necessarily difficult, you just have to get out there and do the work.” 

Lefkofsky also said that many firms working to find treatments for COVID-19 are still reluctant to share data with others for reasons including data privacy rules. He didn’t mention it, but competition between researchers also likely plays a role.

“The first thing that’s really super troubling is even in the midst of a global pandemic, it is hard to get people to truly break down these data silos and contribute data,” Lefkofsky said.

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• The enduring history of health care inequality for Black Americans
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