Leo Celi and the 'Holy Grail of Personalized Medicine'

Danny Funt
APRIL 16, 2018

Melding Medicine and Computing

The same year Leo Celi was born in the Philippines, psychologists at the Oregon Research Institute were performing groundbreaking experiments on the shortcomings of human judgment. As it happens, the first of their tests observed medical professionals. When examining stomach x-rays for cancer, radiologists “tended to describe their thought processes as subtle and complex and difficult to model,” as Michael Lewis recounts in his latest book, The Undoing Project. Yet computers using a simple algorithm did better at diagnosing cancer than did the doctors being studied. For the lead Oregon investigator, the results were “generally terrifying.”
In college and then medical school at the University of the Philippines in Manila, Celi certainly had no encounters with data science. His mother was a nurse, and his sisters and cousins also became nurses—in their country, a career in medicine was a guaranteed way out of poverty. When Celi entered medical school, he found “it was all memorization and embracing concepts that are handed to you.” His professors imparted what he later came to see as a naïve sense of confidence.

“In school examinations, there are always multiple choice and true or false, when in fact there are no correct answers,” Celi explains. “It depends on what patients value more: Do they value this probability of improvement from an intervention versus this probability of harm from a side effect? As doctors, we can’t help them navigate that because we ourselves are very uncomfortable with probabilities.”

Now Celi believes medical schools and residency programs “need to be transformed radically,” with data science incorporated into core curricula so that doctors can make better use of EMRs and feel comfortable working with investigators. (New York University School of Medicine is leading the way on this.) He and his lab partners at MIT outlined that recommendation in their 2016 paper Bridging the Health Data Divide. Clinicians are inclined to believe they know what’s best for patients, while engineers can find doctors stubbornly set in their ways. Data silos are notorious in healthcare, but expertise has been placed in silos, too.

After earning his medical degree in 1990, Celi followed the rest of his family to the United States, where he received training in internal medicine at Cleveland Clinic, in infectious diseases at Harvard, and then in critical care medicine at Stanford. In 1999, he joined a startup out of Johns Hopkins University called Visicu, where he worked with software and hardware engineers to design technology that would improve the efficiency of ICUs.

Around that time, Roger Mark, MD, PhD, was pushing a computer on a cart through the ICU at Beth Israel Deaconess Medical Center, plugging it into a monitor to record data with the permission of 1 patient at a time. In an effort to study arrhythmias, Mark recalls, “we’d ask the nurse, ‘Who had a bad night? Who’s unstable?’ Then we’d start recording, and of course the patient would be stable as a rock that day.”

Mark directs the Laboratory of Computational Physiology at MIT, and this primitive method of data collection was the origin of Medical Information Mart for Intensive Care, or MIMIC, the database with de-identified records from patients admitted to the hospital’s ICU from 2001 to 2012. (It was made possible after the institutional review board at Beth Israel approved of Mark’s gathering data without individual consent.) Mark recognized that each patient’s experience was, in essence, an experiment. Years later, people like Celi would be able to parse that data for all sorts of unanticipated findings.

In 2002, Celi accepted a faculty position at the University of Otago in New Zealand, where he developed safety protocols for the ICU while continuing to practice in the emergency department. A medical student there, Xaviour Walker, was struck by Celi’s “thirst for knowledge” and his  example as a “hugely generous and humble person. He always talked to nurses, techs, students, and administration staff to get to know them as people.” Celi encouraged Walker to continue studying in the United States. By 2007, Celi had decided that he, too, needed additional education—the art of medicine, as he’d been taught it, was failing patients. So he returned to Cambridge, Massachusetts.

As Celi began dual master’s programs at MIT and Harvard, the National Institutes of Health awarded Roger Mark’s lab a major grant to expand MIMIC. “I went back to school to try to improve the way we deliver care, and then suddenly the government granted funding to build the tools I was interested in building,” Celi says. “It was almost too good to be true.”

For his master’s thesis at MIT (with Peter Szolovits’ supervision), Celi used MIMIC to analyze 1400 patients admitted to the ICU with acute kidney injury and found that traditional models for predicting hospital mortality, which use prospective observational studies, were less effective than customized modeling would be using retrospective data. In conclusion, he noted that “the question remains whether clinicians will embrace this approach. Will we be able to convince them that information from a very large cohort of patients whose clinical course is stored in an electronic database might be more reliable than a composite of the patients they have encountered in the past whose clinical course may be imperfectly stored in their memory?”

Nearly a decade later, many clinicians remain unconvinced. Szolovits, for his part, maintains hope that the medical community will embrace data science. But, he adds, “I was optimistic in 1974, and it’s taken a while. I would take my optimism with a grain of salt.”

The Physician and the Algorithm

These days, at any given moment, Celi is involved in about 25 research projects. He continues to work as an internist in the Beth Israel Deaconess ICU for a week each month—as an investigator, he considers it crucial to remain in touch with the challenges facing clinicians. When he’s not at the hospital, Celi typically starts his day at 7 AM on conference calls with collaborators based all over the world. He works at his office on MIT’s campus from 9 AM to 6 PM and then returns home for more conference calls until 11 PM or so. Somehow he finds an hour every day for kickboxing. “Wherever we travel in the world,” explains one of his lab partners and kickboxing converts, Matthieu Komorowski, MD, “we bring the boxing gloves and kicking shields.”

On Friday mornings, Celi teaches a course in the Health Science and Technology program run jointly by MIT and Harvard Medical School. The course, Global Health Informatics, allows students to conduct research using MIMIC. The database includes, for example, progress notes from care providers; timestamped physiological measurements; continuous intravenous drip medications and fluid balances; laboratory test results; and data from the hospital’s 2 critical care information systems, Philips CareVue and iMDsoft MetaVision. All this data collection was possible without disturbing ICU workflow. Mark estimates that 6000 people around the world have completed the credentialing process to use MIMIC.

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