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."
Dec. 17th Event: The Latest on Omicron, Boosters, and Immunity
This virtual event will convene leading scientific and medical experts to discuss the most pressing questions around the new Omicron variant, including what we know so far about its ability to evade COVID-19 vaccines, the role of boosters in eliciting heightened immunity, and the science behind variants and vaccines. A public Q&A will follow the expert discussion.
EVENT INFORMATION:
Date: Friday Dec 17, 2021
2:00pm - 3:30pm EST
Dr. Céline Gounder, MD, ScM, is the CEO/President/Founder of Just Human Productions, a non-profit multimedia organization. She is also the host and producer of American Diagnosis, a podcast on health and social justice, and Epidemic, a podcast about infectious disease epidemics and pandemics. She served on the Biden-Harris Transition COVID-19 Advisory Board.
Dr. Theodora Hatziioannou, Ph.D., is a Research Associate Professor in the Laboratory of Retrovirology at The Rockefeller University. Her research includes identifying plasma samples from recovered COVID-19 patients that contain antibodies capable of neutralizing the SARS-CoV-2 coronavirus.
Dr. Onyema Ogbuagu, MBBCh, is an Associate Professor at Yale School of Medicine and an infectious disease specialist who treats COVID-19 patients and leads Yale’s clinical studies around COVID-19. He ran Yale’s trial of the Pfizer/BioNTech vaccine.
Dr. Eric Topol, M.D., is a cardiologist, scientist, professor of molecular medicine, and the director and founder of Scripps Research Translational Institute. He has led clinical trials in over 40 countries with over 200,000 patients and pioneered the development of many routinely used medications.
This event is the fourth of a four-part series co-hosted by Leaps.org, the Aspen Institute Science & Society Program, and the Sabin–Aspen Vaccine Science & Policy Group, with generous support from the Gordon and Betty Moore Foundation and the Howard Hughes Medical Institute.
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.
7 Things to Know about the U.S.’s Capability to Detect Omicron
If the new variant Omicron isn’t here already – which many experts suspect that it is – it will be soon. While we wait for scientists to conduct the necessary research to characterize its transmissibility, potential fitness at immune evasion, and disease severity, we wanted to give Leaps.org readers a window into how the U.S. is positioned to detect the variant. So we spoke to Kelly Wroblewski, director of infectious diseases at the Association of Public Health Laboratories, a membership organization that represents state and local government health labs in the United States. Here are seven insights she shared.
1) If you test positive for COVID-19 with a standard PCR test, the diagnostic report will not tell you which variant you have. There are no diagnostic tests available for your doctor to order to identify variants. To find out the variant, the specimen must be sent to a commercial, clinical, academic, or public health laboratory for genetic sequencing.
2) Today, the U.S. sequences about 5 to 10 percent of all diagnostic specimens that test positive for SARS-CoV-2 in order to determine which variants are circulating and where. Last week nationally, for example, labs sequenced about 80,000 samples. This represents a massive increase from last year at this time, when labs were only sequencing about 8,000 specimens per week. Currently, 99.5 percent of circulating SARS-CoV-2 virus in the U.S. is the Delta variant.
3) The U.S. is “very well prepared” to detect Omicron, Wroblewski says, “particularly compared to where we were when the Alpha variant, or B117 first emerged.” Of the hunt for Omicron, she adds, “it’s very reminiscent of that time, except we are doing so much more sequencing and we have so much better coverage with our sequencing geographically, and we're doing it in a much more timely way. We have the ability to find emerging variants that are circulating in 0.01 percent of the population.”
4) Deciding which specimens to sample is not totally random. Samples that have more virus are likely to lead to better sequencing results. Labs also look to have a diverse set of representative samples, meaning across geographic regions and across gender, race, ethnicity, and age groups. Clinical diversity is also important, such as including pregnant women, severe in-patient cases, mild cases, etc.
5) Sequencing more is not necessarily better to find Omicron faster. “We will increase the number of sequences to a certain extent,” Wroblewski says. “Where we exhibit some caution is doing that indiscriminately isn’t the most effective use of time and resources. The important thing is to try to find Omicron, and if you increase your testing capacity too much, right now, it's still predominantly Delta in the U.S. by a long shot. So you’re mostly going to sequence Delta and you run the risk of delaying your discovery of Omicron, if you focus solely on increasing sequencing.”
So besides just ramping up the sheer numbers of sequencing, diagnostic labs across the country are now advised to preferentially use a certain PCR test made by Thermo Fisher that can help hasten the detection of Omicron. It turns out that Omicron’s specific mutations in the Spike protein mean that the Spike is not picked up on this PCR test, which yields a type of result called an S-gene target failure. Yet the test will still accurately pick up a COVID-19 diagnosis, because it detects two other gene targets on Omicron that are not mutated. “That S-gene target failure gives you a good indication that you may have Omicron. It’s a good early screen.”
Labs will then still need to sequence the whole genome to confirm it matches the Omicron sequence. “So right now, the new recommendation is to use [the Thermo Fisher test] as much as possible to give us a better chance of detecting Omicron more quickly.”
6) This Thermo Fisher test is “fairly widely used” in the U.S. already, so many labs are already well positioned to make the shift. “In early to mid 2020,” Wroblewski explains, “when the supply chain issue for testing was acute, many public health labs implemented five, six, seven, eight different tests, just so they could get enough supplies to do all the testing. Now that we're in a much better place supply-chain wise, it's very difficult and time consuming and cumbersome to maintain all those different test methods all the time, and many, many labs scaled back to only one or two. And so this [new recommendation] would just be shifting to two for some labs that will be shifting to them.”
7) Once Omicron is found here, labs will be focused on finding as many cases as possible, and the CDC will be conducting a variety of studies to determine the impact of the variant on diagnostics, therapeutics, and vaccines. Epidemiologists at the local, state, and federal level will analyze which populations it is spreading in, as well as the severity of the disease it causes. They will work to sort out different impacts on vaccinated vs. unvaccinated populations. The ultimate goal, Wroblewski concludes, is to “use all of that information to make better public health decisions and inform the public about what’s going on.”
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.