Making health care more personal

The health care system today largely focuses on helping people after they have problems. When they do receive treatment, it’s based on what has worked best on average across a huge, diverse group of patients.

Now the company Health at Scale is making health care more proactive and personalized — and, true to its name, it’s doing so for millions of people.

Health at Scale uses a new approach for making care recommendations based on new classes of machine-learning models that work even when only small amounts of data on individual patients, providers, and treatments are available.

The company is already working with health plans, insurers, and employers to match patients with doctors. It’s also helping to identify people at rising risk of visiting the emergency department or being hospitalized in the future, and to predict the progression of chronic diseases. Recently, Health at Scale showed its models can identify people at risk of severe respiratory infections like influenza or pneumonia, or, potentially, Covid-19.

“From the beginning, we decided all of our predictions would be related to achieving better outcomes for patients,” says John Guttag, chief technology officer of Health at Scale and the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT. “We’re trying to predict what treatment or physician or intervention would lead to better outcomes for people.”

A new approach to improving health

Health at Scale co-founder and CEO Zeeshan Syed met Guttag while studying electrical engineering and computer science at MIT. Guttag served as Syed’s advisor for his bachelor’s and master’s degrees. When Syed decided to pursue his PhD, he only applied to one school, and his advisor was easy to choose.

Syed did his PhD through the Harvard-MIT Program in Health Sciences and Technology (HST). During that time, he looked at how patients who’d had heart attacks could be better managed. The work was personal for Syed: His father had recently suffered a serious heart attack.

Through the work, Syed met Mohammed Saeed SM ’97, PhD ’07, who was also in the HST program. Syed, Guttag, and Saeed founded Health at Scale in 2015 along with  David Guttag ’05, focusing on using core advances in machine learning to solve some of health care’s hardest problems.

“It started with the burning itch to address real challenges in health care about personalization and prediction,” Syed says.

From the beginning, the founders knew their solutions needed to work with widely available data like health care claims, which include information on diagnoses, tests, prescriptions, and more. They also sought to build tools for cleaning up and processing raw data sets, so that their models would be part of what Guttag refers to as a “full machine-learning stack for health care.”

Finally, to deliver effective, personalized solutions, the founders knew their models needed to work with small numbers of encounters for individual physicians, clinics, and patients, which posed severe challenges for conventional AI and machine learning.

“The large companies getting into [the health care AI] space had it wrong in that they viewed it as a big data problem,” Guttag says. “They thought, ‘We’re the experts. No one’s better at crunching large amounts of data than us.’ We thought if you want to make the right decision for individuals, the problem was a small data problem: Each patient is different, and we didn’t want to recommend to patients what was best on average. We wanted what was best for each individual.”

The company’s first models helped recommend skilled nursing facilities for post-acute care patients. Many such patients experience further health problems and return to the hospital. Health at Scale’s models showed that some facilities were better at helping specific kinds of people with specific health problems. For example, a 64-year-old man with a history of cardiovascular disease may fare better at one facility compared to another.

Today the company’s recommendations help guide patients to the primary care physicians, surgeons, and specialists that are best suited for them. Guttag even used the service when he got his hip replaced last year.

Health at Scale also helps organizations identify people at rising risk of specific adverse health events, like heart attacks, in the future.

“We’ve gone beyond the notion of identifying people who have frequently visited emergency departments or hospitals in the past, to get to the much more actionable problem of finding those people at an inflection point, where they are likely to experience worse outcomes and higher costs,” Syed says.

The company’s other solutions help determine the best treatment options for patients and help reduce health care fraud, waste, and abuse. Each use case is designed to improve patient health outcomes by giving health care organizations decision-support for action.

“Broadly speaking, we are interested in building models that can be used to help avoid problems, rather than simply predict them,” says Guttag. “For example, identifying those individuals at highest risk for serious complications of a respiratory infection [enables care providers] to target them for interventions that reduce their chance of developing such an infection.”

Impact at scale

Earlier this year, as the scope of the Covid-19 pandemic was becoming clear, Health at Scale began considering ways its models could help.

“The lack of data in the beginning of the pandemic motivated us to look at the experiences we have gained from combatting other respiratory infections like influenza and pneumonia,” says Saeed, who serves as Health at Scale’s chief medical officer.

The idea led to a peer-reviewed paper where researchers affiliated with the company, the University of Michigan, and MIT showed Health at Scale’s models could accurately predict hospitalizations and visits to the emergency department related to respiratory infections.

“We did the work on the paper using the tech we’d already built,” Guttag says. “We had interception products deployed for predicting patients at-risk of emergent hospitalizations for a variety of causes, and we saw that we could extend that approach. We had customers that we gave the solution to for free.”

The paper proved out another use case for a technology that is already being used by some of the largest health plans in the U.S. That’s an impressive customer base for a five-year-old company of only 20 people — about half of which have MIT affiliations.

“The culture MIT creates to solve problems that are worth solving, to go after impact, I think that’s been reflected in the way the company got together and has operated,” Syed says. “I’m deeply proud that we’ve maintained that MIT spirit.”

And, Syed believes, there’s much more to come.

“We set out with the goal of driving impact,” Syed says. “We currently run some of the largest production deployments of machine learning at scale, affecting millions, if not tens of millions, of patients, and we  are only just getting started.”

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Real-time data for a better response to disease outbreaks

Kinsa was founded by MIT alumnus Inder Singh MBA ’06, SM ’07 in 2012, with the mission of collecting information about when and where infectious diseases are spreading in real-time. Today the company is fulfilling that mission along several fronts.

It starts with families. More than 1.5 million of Kinsa’s “smart” thermometers have been sold or given away across the country, including hundreds of thousands to families from low-income school districts. The thermometers link to an app that helps users decide if they should seek medical attention based on age, fever, and symptoms.

At the community level, the data generated by the thermometers are anonymized and aggregated, and can be shared with parents and school officials, helping them understand what illnesses are going around and prevent the spread of disease in classrooms.

By working with over 2,000 schools to date in addition to many businesses, Kinsa has also developed predictive models that can forecast flu seasons each year. In the spring of this year, the company showed it could predict flu spread 12-20 weeks in advance at the city level.

The milestone prepared Kinsa for its most profound scale-up yet. When Covid-19 came to the U.S., the company was able to estimate its spread in real-time by tracking fever levels above what would normally be expected. Now Kinsa is working with health officials in five states and three cities to help contain and control the virus.

“By the time the CDC [U.S. Centers for Disease Control] gets the data, it has been processed, deidentified, and people have entered the health system to see a doctor,” say Singh, who is Kinsa’s CEO as well as its founder. “There’s a huge delay from when someone contracts an illness and when they see a doctor. The current health care system only sees the latter; we see the former.”

Today Kinsa finds itself playing a central role in America’s Covid-19 response. In addition to its local partnerships, the company has become a central information hub for the public, media, and researchers with its Healthweather tool, which maps unusual rates of fevers — among the most common symptom of Covid-19 — to help visualize the prevalence of illness in communities.

Singh says Kinsa’s data complement other methods of containing the virus like testing, contact tracing, and the use of face masks.

Better data for better responses

Singh’s first exposure to MIT came while he was attending the Harvard University Kennedy School of Government as a graduate student.

“I remember I interacted with some MIT undergrads, we brainstormed some social-impact ideas,” Singh recalls. “A week later I got an email from them saying they’d prototyped what we were talking about. I was like, ‘You prototyped what we talked about in a week!?’ I was blown away, and it was an insight into how MIT is such a do-er campus. It was so entrepreneurial. I was like, ‘I want to do that.’”

Soon Singh enrolled in the Harvard-MIT Program in Health Sciences and Technology, an interdisciplinary program where Singh earned his master’s and MBA degrees while working with leading research hospitals in the area. The program also set him on a course to improve the way we respond to infectious disease.

Following his graduation, he joined the Clinton Health Access Initiative (CHAI), where he brokered deals between pharmaceutical companies and low-resource countries to lower the cost of medicines for HIV, malaria, and tuberculosis. Singh described CHAI as a dream job, but it opened his eyes to several shortcomings in the global health system.

“The world tries to curb the spread of infectious illness with almost zero real-time information about when and where disease is spreading,” Singh says. “The question I posed to start Kinsa was ‘how do you stop the next outbreak before it becomes an epidemic if you don’t know where and when it’s starting and how fast it’s spreading’?”

Kinsa was started in 2012 with the insight that better data were needed to control infectious diseases. In order to get that data, the company needed a new way of providing value to sick people and families.

“The behavior in the home when someone gets sick is to grab the thermometer,” Singh says. “We piggy-backed off of that to create a communication channel to the sick, to help them get better faster.”

Kinsa started by selling its thermometers and creating a sponsorship program for corporate donors to fund thermometer donations to Title 1 schools, which serve high numbers of economically disadvantaged students. Singh says 40 percent of families that receive a Kinsa thermometer through that program did not previously have any thermometer in their house.

The company says its program has been shown to help schools improve attendance, and has yielded years of real-time data on fever rates to help compare to official estimates and develop its models.

“We had been forecasting flu incidence accurately several weeks out for years, and right around early 2020, we had a massive breakthrough,” Singh recalls. “We showed we could predict flu 12 to 20 weeks out — then March hit. We said, let’s try to remove the fever levels associated with cold and flu from our observed real time signal. What’s left over is unusual fevers, and we saw hotspots across the country. We observed six years of data and there’d been hot spots, but nothing like we were seeing in early March.”

The company quickly made their real-time data available to the public, and on March 14, Singh got on a call with the former New York State health commissioner, the former head of the U.S. Food and Drug Administration, and the man responsible for Taiwan’s successful Covid-19 response.

“I said, ‘There’s hotspots everywhere,” Singh recalls. “They’re in New York, around the Northeast, Texas, Michigan. They said, ‘This is interesting, but it doesn’t look credible because we’re not seeing case reports of Covid-19.’ Low and behold, days and weeks later, we saw the Covid cases start building up.”

A tool against Covid-19

Singh says Kinsa’s data provide an unprecedented look into the way a disease is spreading through a community.

“We can predict the entire incidence curve [of flu season] on a city-by-city basis,” Singh says. “The next best model is [about] three weeks out, at a multistate level. It’s not because we’re smarter than others; it’s because we have better data. We found a way to communicate with someone consistently when they’ve just fallen ill.”

Kinsa has been working with health departments and research groups around the country to help them interpret the company’s data and react to early warnings of Covid-19’s spread. It’s also helping companies around the country as they begin bringing employees back to offices.

Now Kinsa is working on expanding its international presence to help curb infectious diseases on multiple fronts around the world, just like it’s doing in the U.S. The company’s progress promises to help authorities monitor diseases long after Covid-19.

“I started Kinsa to create a global, real-time outbreak monitoring and detection system, and now we have predictive power beyond that,” Singh says. “When you know where and when symptoms are starting and how fast their spreading, you can empower local individuals, families, communities, and governments.”

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