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.
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."
Her Incredible Sense of Smell Led Scientists to Develop the First Parkinson's Test
Joy Milne's unusual sense of smell led Dr. Tilo Kunath, a neurobiologist at the Centre for Regenerative Medicine at the University of Edinburgh, and a host of other scientists, to develop a new diagnostic test for Parkinson's.
Thirty-seven years ago, Joy Milne, a nurse from Perth, Scotland, noticed a musky odor coming from her husband, Les.
To her surprise, at a local support group meeting, she caught the familiar scent once again, hanging over the group like a cloud.
At first, Milne thought the smell was a result of bad hygiene and badgered her husband to take longer showers. But when the smell persisted, Milne learned to live with it, not wanting to hurt her husband's feelings.
Twelve years after she first noticed the "woodsy" smell, Les was diagnosed at the age of 44 with Parkinson's Disease, a neurodegenerative condition characterized by lack of dopamine production and loss of movement. Parkinson's Disease currently affects more than 10 million people worldwide.
Milne spent the next several years believing the strange smell was exclusive to her husband. But to her surprise, at a local support group meeting in 2012, she caught the familiar scent once again, hanging over the group like a cloud. Stunned, Milne started to wonder if the smell was the result of Parkinson's Disease itself.
Milne's discovery led her to Dr. Tilo Kunath, a neurobiologist at the Centre for Regenerative Medicine at the University of Edinburgh. Together, Milne, Kunath, and a host of other scientists would use Milne's unusual sense of smell to develop a new diagnostic test, now in development and poised to revolutionize the treatment of Parkinson's Disease.
"Joy was in the audience during a talk I was giving on my work, which has to do with Parkinson's and stem cell biology," Kunath says. "During the patient engagement portion of the talk, she asked me if Parkinson's had a smell to it." Confused, Kunath said he had never heard of this – but for months after his talk he continued to turn the question over in his mind.
Kunath knew from his research that the skin's microbiome changes during different disease processes, releasing metabolites that can give off odors. In the medical literature, diseases like melanoma and Type 2 diabetes have been known to carry a specific scent – but no such connection had been made with Parkinson's. If people could smell Parkinson's, he thought, then it stood to reason that those metabolites could be isolated, identified, and used to potentially diagnose Parkinson's by their presence alone.
First, Kunath and his colleagues decided to test Milne's sense of smell. "I got in touch with Joy again and we designed a protocol to test her sense of smell without her having to be around patients," says Kunath, which could have affected the validity of the test. In his spare time, Kunath collected t-shirt samples from people diagnosed with Parkinson's and from others without the diagnosis and gave them to Milne to smell. In 100 percent of the samples, Milne was able to detect whether a person had Parkinson's based on smell alone. Amazingly, Milne was even able to detect the "Parkinson's scent" in a shirt from the control group – someone who did not have a Parkinson's diagnosis, but would go on to be diagnosed nine months later.
From the initial study, the team discovered that Parkinson's did have a smell, that Milne – inexplicably – could detect it, and that she could detect it long before diagnosis like she had with her husband, Les. But the experiments revealed other things that the team hadn't been expecting.
"One surprising thing we learned from that experiment was that the odor was always located in the back of the shirt – never in the armpit, where we expected the smell to be," Kunath says. "I had a chance meeting with a dermatologist and he said the smell was due to the patient's sebum, which are greasy secretions that are really dense on your upper back. We have sweat glands, instead of sebum, in our armpits." Patients with Parkinson's are also known to have increased sebum production.
With the knowledge that a patient's sebum was the source of the unusual smell, researchers could go on to investigate exactly what metabolites were in the sebum and in what amounts. Kunath, along with his associate, Dr. Perdita Barran, collected and analyzed sebum samples from 64 participants across the United Kingdom. Once the samples were collected, Barran and others analyzed it using a method called gas chromatography mass spectrometry, or GS-MC, which separated, weighed and helped identify the individual compounds present in each sebum sample.
Barran's team can now correctly identify Parkinson's in nine out of 10 patients – a much quicker and more accurate way to diagnose than what clinicians do now.
"The compounds we've identified in the sebum are not unique to people with Parkinson's, but they are differently expressed," says Barran, a professor of mass spectrometry at the University of Manchester. "So this test we're developing now is not a black-and-white, do-you-have-something kind of test, but rather how much of these compounds do you have compared to other people and other compounds." The team identified over a dozen compounds that were present in the sebum of Parkinson's patients in much larger amounts than the control group.
Using only the GC-MS and a sebum swab test, Barran's team can now correctly identify Parkinson's in nine out of 10 patients – a much quicker and more accurate way to diagnose than what clinicians do now.
"At the moment, a clinical diagnosis is based on the patient's physical symptoms," Barran says, and determining whether a patient has Parkinson's is often a long and drawn-out process of elimination. "Doctors might say that a group of symptoms looks like Parkinson's, but there are other reasons people might have those symptoms, and it might take another year before they're certain," Barran says. "Some of those symptoms are just signs of aging, and other symptoms like tremor are present in recovering alcoholics or people with other kinds of dementia." People under the age of 40 with Parkinson's symptoms, who present with stiff arms, are often misdiagnosed with carpal tunnel syndrome, she adds.
Additionally, by the time physical symptoms are present, Parkinson's patients have already lost a substantial amount of dopamine receptors – about sixty percent -- in the brain's basal ganglia. Getting a diagnosis before physical symptoms appear would mean earlier interventions that could prevent dopamine loss and preserve regular movement, Barran says.
"Early diagnosis is good if it means there's a chance of early intervention," says Barran. "It stops the process of dopamine loss, which means that motor symptoms potentially will not happen, or the onset of symptoms will be substantially delayed." Barran's team is in the processing of streamlining the sebum test so that definitive results will be ready in just two minutes.
"What we're doing right now will be a very inexpensive test, a rapid-screen test, and that will encourage people to self-sample and test at home," says Barran. In addition to diagnosing Parkinson's, she says, this test could also be potentially useful to determine if medications were at a therapeutic dose in people who have the disease, since the odor is strongest in people whose symptoms are least controlled by medication.
"When symptoms are under control, the odor is lower," Barran says. "Potentially this would allow patients and clinicians to see whether their symptoms are being managed properly with medication, or perhaps if they're being overmedicated." Hypothetically, patients could also use the test to determine if interventions like diet and exercise are effective at keeping Parkinson's controlled.
"We hope within the next two to five years we will have a test available."
Barran is now running another clinical trial – one that determines whether they can diagnose at an earlier stage and whether they can identify a difference in sebum samples between different forms of Parkinson's or diseases that have Parkinson's-like symptoms, such as Lewy Body Dementia.
"Within the next one to two years, we hope to be running a trial in the Manchester area for those people who do not have motor symptoms but are at risk for developing dementia due to symptoms like loss of smell and sleep difficulty," Barran says. "If we can establish that, we can roll out a test that determines if you have Parkinson's or not with those first pre-motor symptoms, and then at what stage. We hope within the next two to five years we will have a test available."
But a definitive Parkinson's test, however revolutionary, would likely not be made available to the general population – at least, not for a while.
"We would likely first give this test to people who are at risk due to a genetic predisposition, or who are at risk based on prodomal symptoms, like people who suffer from a REM sleep disorder who have a 50 to 70 percent chance of developing Parkinson's within a ten year period," Barran says. "Those would be people who would benefit from early therapeutic intervention. For the normal population, it isn't beneficial at the moment to know until we have therapeutic interventions that can be useful."
Milne's husband, Les, passed away from complications of Parkinson's Disease in 2015. But thanks to him and the dedication of his wife, Joy, science may have found a way to someday prolong the lives of others with this devastating disease.
[Ed. Note: This hit article from our archives originally ran on September 3, 2019.]
A Team of Israeli Students Just Created Honey Without Bees
The bee-free honey on the left, and the Israeli team that won the iGEM competition.
Can you make honey without honeybees? According to 12 Israeli students who took home a gold medal in the iGEM (International Genetically Engineered Machine) competition with their synthetic honey project, the answer is yes, you can.
The honey industry faces serious environmental challenges, like the mysterious Colony Collapse Disorder.
For the past year, the team from Technion-Israel Institute of Technology has been working on creating sustainable, artificial honey—no bees required. Why? As the team explains in a video on the project's website, "Studies have shown the amazing nutritional values of honey. However, the honey industry harms the environment, and particularly the bees. That's why vegans don't use honey and why our honey will be a great replacement."
Indeed, honey has long been a controversial product in the vegan community. Some say it's stealing an animal's food source (though bees make more honey than they can possibly use). Some avoid eating honey because it is an animal product and bees' natural habitats are disturbed by humans harvesting it. Others feel that because bees aren't directly killed or harmed in the production of honey, it's not actually unethical to eat.
However, there's no doubt that the honey industry faces some serious environmental challenges. Colony Collapse Disorder, a mysterious phenomenon in which worker bees in colonies disappear in large numbers without any real explanation, came to international attention in 2006. Several explanations from poisonous pesticides to immune-suppressing stress to new or emerging diseases have been posited, but no definitive cause has been found.
There's also the problem of human-managed honey farms having a negative impact on the natural honeybee population.
So how can honey be made without honeybees? It's all about bacteria and enzymes.
The way bees make honey is by collecting nectar from flowers, transporting it in their "honey stomach" (which is separate from their food stomach), and bringing it back to the hive, where it gets transferred from bee mouth to bee mouth. That transferal process reduces the moisture content from about 70 percent to 20 percent, and honey is formed.
The product is still currently under development.
The Technion students created a model of a synthetic honey stomach metabolic pathway, in which the bacterium Bacillus subtilis "learns" to produce honey. "The bacteria can independently control the production of enzymes, eventually achieving a product with the same sugar profile as real honey, and the same health benefits," the team explains. Bacillus subtilis, which is found in soil, vegetation, and our own gastrointestinal tracts, has a natural ability to produce catalase, one of the enzymes needed for honey production. The product is still currently under development.
Whether this project results in a real-world jar of honey we'll be able to buy at the grocery store remains to be seen, but imagine how happy the bees—and vegans—would be if it did.