Curtis Petersen was sitting in his cancer biology lab at Oregon Health & Science University, counting cells in a Petri dish. One by one. Hour after hour.
The work was meticulous; a tedious plod toward understanding the molecular mechanisms of disease. Over time, the task nettled him. “It seemed to impact a very narrow scope of people with very specific disease states,” he says. “And I was interested in going in the opposite direction.”
So in 2013, he pivoted. He enrolled in the Master of Public Health (MPH) program at The Dartmouth Institute for Health Policy and Clinical Practice at Dartmouth’s Geisel School of Medicine, trading molecular biology of a single disease state for population-level thinking about health.
The Question That Wouldn’t Go Away
It was while he was at The Dartmouth Institute that an epidemiology course unlocked something in him. “It got me thinking about data analysis less as, ‘How can I speed up my work,’ and more about answering interesting questions through statistics,” he says. This revelation would set the tone for the following decade of discovery, learning, and, more than a fair share of pivots.
His initial ponderings on the purpose of data analysis led Petersen to push himself beyond the coursework. With Stata and R programming, he took a deep dive into biostatistics. Slowly, he began noticing a problem nobody seemed to know how to solve: What to do with “high-frequency health data”—the measurements wearables like Apple Watch and Oura Ring now ubiquitously collect.
“If a device collects 30 blood pressure readings in a day, as a user what am I meant to do with that? What does that mean for my health?” Petersen asks.
After completing his MPH in 2014, Petersen joined ImagineCare to build algorithms for spotting patterns in patient data, working alongside Dartmouth and Geisel faculty members Nancy Morden, MD; Ethan Berke, MD, MPH; and Jim Weinstein, MS, DO. This work of translating complex analytics into tools clinicians could actually use felt more practical than studying the narrow scope of a specific disease.
But that high-frequency data problem kept nagging at him. And in 2016, in true entrepreneurial spirit, he pivoted again—boomeranging back to Dartmouth for a PhD in technology & disease management, part of Geisel’s quantitative biomedical science program.
‘Your Flaming Garbage’
Back at Dartmouth, Petersen’s research focus was epigenetics—the science of how one’s environment impacts their genetics—in the lab of Brock Christensen, PhD, professor of epidemiology and molecular and systems biology at Geisel and one of the world’s leading experts in the field.
To wrangle molecular data, behavioral patterns, and clinical measurements, Petersen realized he needed to level up his statistical chops. So he tacked on a Master of Science in biomedical data science to his PhD. Another unexpected turn.
For his PhD dissertation, Petersen explored the connection between biological aging and physical activity in older adults. Tracking how bodies change over time; finding meaning in messy streams of scientific information. Finally, he had landed on the longitudinal work he cared about most.
As president of the Graduate Student Council, Petersen encountered peers struggling to find their path. Many lamented how their data refused to behave, how their research was going nowhere.
“Even if your data and research seem like a flaming pile of garbage from the start,” he’d tell them, “it’s your flaming garbage. Own it. Make it work. You can become an expert in what it means and discover some amazing answers.”
When Nobody Cares
Right as Petersen was wrapping up his PhD, fellow Dartmouth Institute alum Nick Weber, MPH ’19, approached him. How would he like to start a company?
Years earlier, Weber had suffered a heart attack. Now he wanted to build better tools for prevention and recovery. Petersen balked at first. As before, he was less keen to treat a specific disease. But Weber’s pitch hit the nerve of what had dogged him for years: How do you make high-frequency health data clinically valuable to a lot of people?
Soon after being approached by Weber, Petersen said yes, and the two Geisel alums co-founded Ucardia, a virtual cardiac rehab service with remote monitoring and personalized coaching.
Selling it to hospitals, Petersen discovered, was brutal. “It was like selling a bathroom sink to somebody whose house is on fire,” he says. Hospital administrators kept telling him, “I know you can help me, but I’m losing money everywhere else.”
So Petersen, along with Weber, made a choice to save their idea: pivot. They expanded from post-acute patients to anyone with cardiometabolic conditions. They built products. Scrapped them. Built new ones. “The researcher in me is always thinking about what’s wrong and how to improve,” Petersen says. “I’ve always liked the idea of making a thing more useful than it is.”
Context Is King
Today, Ucardia has paying customers and is running a clinical trial with UT Southwestern to evaluate their mobile health cardiac rehab program for heart failure patients with preserved ejection fraction (HFpEF), a chronic condition where the heart’s main pumping chamber is too stiff to fill with blood.
The biggest challenge, Petersen believes, is giving people insights they don’t already have. “If I tell you that your weight is going up, who cares? You probably already know that,” he says.
What matters is how signals relate to one another. A heart rate spike alone is just an event. A heart rate spike at a specific time, when you know what else is happening and how it compares to baseline—that’s meaningful, and something you can act on.
“By combining episodic data together, we can turn snapshots into almost a continuous dataset, which helps us start to understand what could really be going on,” he says.
If gathering context over time turns obvious signals into insightful stories, that same alchemy reveals something about Petersen’s own journey. His story may look tidy on LinkedIn, but it belies the truth of how switchbacks in life pass for serendipity online.
After his MPH at Geisel, all those years ago, Petersen says he had no idea what he would do. He took jobs. Went back for degrees. Started a company that was not guaranteed to succeed. It didn’t always make sense. But that was his flaming garbage, and he spent the time discovering how everything can come together.
“The only reason it’s worked,” he says, “is because I’ve tried to say yes to everything. You never know when something is going to work out. But you get out what you put in.”
