“Before the conference, I’d seen a press release announcing that the largest health actuarial firm in the world, Milliman, was now using the LexisNexis scores. I tracked down Marcos Dachary, who works in business development for Milliman. Actuaries calculate health care risks and help set the price of premiums for insurers. I asked Dachary if Milliman was using the LexisNexis scores to price health plans and he said: “There could be an opportunity.”
The scores could allow an insurance company to assess the risks posed by individual patients and make adjustments to protect themselves from losses, he said. For example, he said, the company could raise premiums, or revise contracts with providers. It’s too early to tell whether the LexisNexis scores will actually be useful for pricing, he said. But he was excited about the possibilities. “One thing about social determinants data — it piques your mind,” he said. Dachary acknowledged the scores could also be used to discriminate. Others, he said, have raised that concern. As much as there could be positive potential, he said, “there could also be negative potential.” It’s that negative potential that still bothers data analyst Erin Kaufman, who left the health insurance industry in January. The 35-year-old from Atlanta had earned her doctorate in public health because she wanted to help people, but one day at Aetna, her boss told her to work with a new data set.
To her surprise, the company had obtained personal information from a data broker on millions of Americans. The data contained each person’s habits and hobbies, like whether they owned a gun, and if so, what type, she said. It included whether they had magazine subscriptions, liked to ride bikes or run marathons. It had hundreds of personal details about each person. The Aetna data team merged the data with the information it had on patients it insured. The goal was to see how people’s personal interests and hobbies might relate to their health care costs. But Kaufman said it felt wrong: The information about the people who knitted or crocheted made her think of her grandmother. And the details about individuals who liked camping made her think of herself. What business did the insurance company have looking at this information? “It was a dataset that really dug into our clients’ lives,” she said. “No one gave anyone permission to do this.”