Clever Firm Predicts Patients Most at Risk, Then Tries to Intervene Before They Get Sicker
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."
Vaccines Without Vaccinations Won’t End the Pandemic
COVID-19 vaccine development has advanced at a record-setting pace, thanks to our nation's longstanding support for basic vaccine science coupled with massive public and private sector investments.
Yet, policymakers aren't according anywhere near the same level of priority to investments in the social, behavioral, and data science needed to better understand who and what influences vaccination decision-making. "If we want to be sure vaccines become vaccinations, this is exactly the kind of work that's urgently needed," says Dr. Bruce Gellin, President of Global Immunization at the Sabin Vaccine Institute.
Simply put: it's possible vaccines will remain in refrigerators and not be delivered to the arms of rolled-up sleeves if we don't quickly ramp up vaccine confidence research and broadly disseminate the findings.
According to the most recent Gallup poll, the share of U.S. adults who say they would get a COVID-19 vaccine rose to 58 percent this month from 50 percent in September, with non-white Americans and those ages 45-65 even less willing to be vaccinated. While there is still much we don't understand about COVID-19, we do know that without high levels of immunity in the population, a return to some semblance of normalcy is wishful thinking.
Research from prior vaccination campaigns such as H1N1, HPV, and the annual flu points us in the right direction. Key components of successful vaccination efforts require 1) Identifying the concerns of particular segments of the population; 2) Tailoring messages and incentives to address those concerns, and 3) Reaching out through trusted sources – health care providers, public health departments, and others in the community.
Research during the H1N1 flu found preparing people for some uncertainty actually improved trust, according to Dr. Sandra Crouse Quinn, professor and chair, Family Science, University of Maryland. Dr. Crouse Quinn's research during that period also underscored the need to address the specific vaccine concerns of racial and ethnic groups.
The stunning scientific achievement of COVID-19 vaccines anticipated to be ready in record time needs to be backed up by an equally ambitious and evidence-based effort to build the public's confidence in the vaccines.
Data science has provided crucial insight about the social media universe. Dr. Neil Johnson, a scientist at George Washington University, found that despite having fewer followers, anti-vaccination pages are more numerous and growing faster than pro-vaccination pages. They are more often linked to in discussions on other Facebook pages – such as school parent associations – where people are undecided about vaccination.
We've learned about building vaccine confidence from earlier campaigns. Now, however, we are faced with a unique and challenging set of obstacles to unpack quickly: How do we communicate the importance of eventual COVID-19 vaccines to Americans in light of the muddled-to-poor messaging from political leaders, the weaponizing of relatively simple public health recommendations, the enormous disproportionate toll on people of color, and the torrent of online misinformation? We urgently need data reflective of today's circumstances along with the policy to ensure it is quickly and effectively disseminated to the public health and clinical workforce.
Last year prompted in part by the measles outbreaks, Reps. Michael C. Burgess (R-TX) and Kim Shrier (D-WA), both physicians, introduced the bipartisan Vaccines Act to develop a national surveillance system to monitor vaccination rates and conduct a national campaign to increase awareness of the importance of vaccines. Unfortunately, that legislation wasn't passed. In response to COVID-19, Senate HELP Committee Ranking member Patty Murray (D-WA) has sought funds to strengthen vaccine confidence and combat misinformation with federally supported communication, research, and outreach efforts. Leading experts outside of Congress have called for this type of research, including the Sabin-Aspen Vaccine Science Policy Institute. Most recently, the National Academy of Sciences, in its report regarding the equitable distribution of the COVID-19 vaccine, included as one of its recommendations the need for "a rapid-response program to advance the science behind vaccine confidence."
Addressing trust in vaccination has never been as challenging nor as consequential. The stunning scientific achievement of COVID-19 vaccines anticipated to be ready in record time needs to be backed up by an equally ambitious and evidence-based effort to build the public's confidence in the vaccines. In its remaining days, the Trump Administration should invest in building vaccine confidence with current resources, targeting efforts to ensure COVID vaccines reduce rather than exacerbate racial and ethnic health disparities. Congress must also act to provide the additional research and outreach resources needed as well as pass the Vaccines Act so we are better prepared in the future.
If we don't succeed, COVID-19 will continue wreaking havoc on our health, our society, and our economy. We will also permanently jeopardize public trust in vaccines – one of the most successful medical interventions in human history.
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Kira Peikoff was the editor-in-chief of Leaps.org from 2017 to 2021. As a journalist, her work has appeared in The New York Times, Newsweek, Nautilus, Popular Mechanics, The New York Academy of Sciences, and other outlets. She is also the author of four suspense novels that explore controversial issues arising from scientific innovation: Living Proof, No Time to Die, Die Again Tomorrow, and Mother Knows Best. Peikoff holds a B.A. in Journalism from New York University and an M.S. in Bioethics from Columbia University. She lives in New Jersey with her husband and two young sons. Follow her on Twitter @KiraPeikoff.