Clever Firm Predicts Patients Most at Risk, Then Tries to Intervene Before They Get Sicker

Clever Firm Predicts Patients Most at Risk, Then Tries to Intervene Before They Get Sicker

Health firm Populytics tracks and analyzes patient data, and makes care suggestions based on that data.

(Photo by National Cancer Institute (left) and Andrew Leu on Unsplash)



The diabetic patient hit the danger zone.

Ideally, blood sugar, measured by an A1C test, rests at 5.9 or less. A 7 is elevated, according to the Diabetes Council. Over 10, and you're into the extreme danger zone, at risk of every diabetic crisis from kidney failure to blindness.

In three months of working with a case manager, Jen's blood sugar had dropped to 7.2, a much safer range.

This patient's A1C was 10. Let's call her Jen for the sake of this story. (Although the facts of her case are real, the patient's actual name wasn't released due to privacy laws.).

Jen happens to live in Pennsylvania's Lehigh Valley, home of the nonprofit Lehigh Valley Health Network, which has eight hospital campuses and various clinics and other services. This network has invested more than $1 billion in IT infrastructure and founded Populytics, a spin-off firm that tracks and analyzes patient data, and makes care suggestions based on that data.

When Jen left the doctor's office, the Populytics data machine started churning, analyzing her data compared to a wealth of information about future likely hospital visits if she did not comply with recommendations, as well as the potential positive impacts of outreach and early intervention.

About a month after Jen received the dangerous blood test results, a community outreach specialist with psychological training called her. She was on a list generated by Populytics of follow-up patients to contact.

"It's a very gentle conversation," says Cathryn Kelly, who manages a care coordination team at Populytics. "The case manager provides them understanding and support and coaching." The goal, in this case, was small behavioral changes that would actually stick, like dietary ones.

In three months of working with a case manager, Jen's blood sugar had dropped to 7.2, a much safer range. The odds of her cycling back to the hospital ER or veering into kidney failure, or worse, had dropped significantly.

While the health network is extremely localized to one area of one state, using data to inform precise medical decision-making appears to be the wave of the future, says Ann Mongovern, the associate director of Health Care Ethics at the Markkula Center for Applied Ethics at Santa Clara University in California.

"Many hospitals and hospital systems don't yet try to do this at all, which is striking given where we're at in terms of our general technical ability in this society," Mongovern says.

How It Happened

While many hospitals make money by filling beds, the Lehigh Valley Health Network, as a nonprofit, accepts many patients on Medicaid and other government insurances that don't cover some of the costs of a hospitalization. The area's population is both poorer and older than national averages, according to the U.S. Census data, meaning more people with higher medical needs that may not have the support to care for themselves. They end up in the ER, or worse, again and again.

In the early 2000s, LVHN CEO Dr. Brian Nester started wondering if his health network could develop a way to predict who is most likely to land themselves a pricey ICU stay -- and offer support before those people end up needing serious care.

Embracing data use in such specific ways also brings up issues of data security and patient safety.

"There was an early understanding, even if you go back to the (federal) balanced budget act of 1997, that we were just kicking the can down the road to having a functional financial model to deliver healthcare to everyone with a reasonable price," Nester says. "We've got a lot of people living longer without more of an investment in the healthcare trust."

Popultyics, founded in 2013, was the result of years of planning and agonizing over those population numbers and cost concerns.

"We looked at our own health plan," Nester says. Out of all the employees and dependants on the LVHN's own insurance network, "roughly 1.5 percent of our 25,000 people — under 400 people — drove $30 million of our $130 million on insurance costs -- about 25 percent."

"You don't have to boil the ocean to take cost out of the system," he says. "You just have to focus on that 1.5%."

Take Jen, the diabetic patient. High blood sugar can lead to kidney failure, which can mean weekly expensive dialysis for 20 years. Investing in the data and staff to reach patients, he says, is "pennies compared to $100 bills."

For most doctors, "there's no awareness for providers to know who they should be seeing vs. who they are seeing. There's no incentive, because the incentive is to see as many patients as you can," he says.

To change that, first the LVHN invested in the popular medical management system, Epic. Then, they negotiated with the top 18 insurance companies that cover patients in the region to allow access to their patient care data, which means they have reams of patient history to feed the analytics machine in order to make predictions about outcomes. Nester admits not every hospital could do that -- with 52 percent of the market share, LVHN had a very strong negotiating position.

Third party services take that data and churn out analytics that feeds models and care management plans. All identifying information is stripped from the data.

"We can do predictive modeling in patients," says Populytics President and CEO Gregory Kile. "We can identify care gaps. Those care gaps are noted as alerts when the patient presents at the office."

Kile uses himself as a hypothetical patient.

"I pull up Gregory Kile, and boom, I see a flag or an alert. I see he hasn't been in for his last blood test. There is a care gap there we need to complete."

"There's just so much more you can do with that information," he says, envisioning a future where follow-up for, say, knee replacement surgery and outcomes could be tracked, and either validated or changed.

Ethical Issues at the Forefront

Of course, embracing data use in such specific ways also brings up issues of security and patient safety. For example, says medical ethicist Mongovern, there are many touchpoints where breaches could occur. The public has a growing awareness of how data used to personalize their experiences, such as social media analytics, can also be monetized and sold in ways that benefit a company, but not the user. That's not to say data supporting medical decisions is a bad thing, she says, just one with potential for public distrust if not handled thoughtfully.

"You're going to need to do this to stay competitive," she says. "But there's obviously big challenges, not the least of which is patient trust."

So far, a majority of the patients targeted – 62 percent -- appear to embrace the effort.

Among the ways the LVHN uses the data is monthly reports they call registries, which include patients who have just come in contact with the health network, either through the hospital or a doctor that works with them. The community outreach team members at Populytics take the names from the list, pull their records, and start calling. So far, a majority of the patients targeted – 62 percent -- appear to embrace the effort.

Says Nester: "Most of these are vulnerable people who are thrilled to have someone care about them. So they engage, and when a person engages in their care, they take their insulin shots. It's not rocket science. The rocket science is in identifying who the people are — the delivery of care is easy."

Anne Miller
Anne Miller is an editor and writer based in Brooklyn who is particularly curious about how technology impacts our daily lives. Her byline has appeared in the New York Times, the Washington Post, the Wall Street Journal and Slate, and she's a regular contributor to Dell Perspectives — when she's not managing editorial projects for Fortune 500 firms. She holds a master's degree in Human-Computer Interaction from the Rensselaer Polytechnic Institute.
Some companies claim remote work hurts wellbeing. Research shows the opposite.

Leaders at Google and other companies are trying to get workers to return to the office, saying remote and hybrid work disrupt work-life boundaries and well-being. These arguments conflict with research on remote work and wellness.

Adobe Stock

Many leaders at top companies are trying to get workers to return to the office. They say remote and hybrid work are bad for their employees’ mental well-being and lead to a sense of social isolation, meaninglessness, and lack of work-life boundaries, so we should just all go back to office-centric work.

One example is Google, where the company’s leadership is defending its requirement of mostly in-office work for all staff as necessary to protect social capital, meaning people’s connections to and trust in one another. That’s despite a survey of over 1,000 Google employees showing that two-thirds feel unhappy about being forced to work in the office three days per week. In internal meetings and public letters, many have threatened to leave, and some are already quitting to go to other companies with more flexible options.

Keep Reading Keep Reading
Gleb Tsipursky
Dr. Gleb Tsipursky is an internationally recognized thought leader on a mission to protect leaders from dangerous judgment errors known as cognitive biases by developing the most effective decision-making strategies. A best-selling author, he wrote Resilience: Adapt and Plan for the New Abnormal of the COVID-19 Coronavirus Pandemic and Pro Truth: A Practical Plan for Putting Truth Back Into Politics. His expertise comes from over 20 years of consulting, coaching, and speaking and training as the CEO of Disaster Avoidance Experts, and over 15 years in academia as a behavioral economist and cognitive neuroscientist. He co-founded the Pro-Truth Pledge project.
What will the $100 genome mean?

A company has slashed the cost of assessing a person's genome to just $100. With lower costs - and as other genetic tools mature and evolve - a wave of new therapies could be coming in the near future.

Adobe Stock

In May 2022, Californian biotech Ultima Genomics announced that its UG 100 platform was capable of sequencing an entire human genome for just $100, a landmark moment in the history of the field. The announcement was particularly remarkable because few had previously heard of the company, a relative unknown in an industry long dominated by global giant Illumina which controls about 80 percent of the world’s sequencing market.

Ultima’s secret was to completely revamp many technical aspects of the way Illumina have traditionally deciphered DNA. The process usually involves first splitting the double helix DNA structure into single strands, then breaking these strands into short fragments which are laid out on a glass surface called a flow cell. When this flow cell is loaded into the sequencing machine, color-coded tags are attached to each individual base letter. A laser scans the bases individually while a camera simultaneously records the color associated with them, a process which is repeated until every single fragment has been sequenced.

Instead, Ultima has found a series of shortcuts to slash the cost and boost efficiency. “Ultima Genomics has developed a fundamentally new sequencing architecture designed to scale beyond conventional approaches,” says Josh Lauer, Ultima’s chief commercial officer.

Keep Reading Keep Reading
David Cox
David Cox is a science and health writer based in the UK. He has a PhD in neuroscience from the University of Cambridge and has written for newspapers and broadcasters worldwide including BBC News, New York Times, and The Guardian. You can follow him on Twitter @DrDavidACox.