Leonard D’Avolio, Ph.D. is an Assistant Professor at Harvard Medical School and Brigham and Women’s Division of General Internal Medicine and Primary Care. He is the CEO and co-founder of Cyft, a company based on years of his research optimizing machine learning and natural language processing to improve healthcare. He is also an advisor to Ariadne Labs and the Helmsley Charitable Trust Foundation, board member for Youth Development Organization, a researcher, and writer.
He previously led informatics for the Department of Veterans Affairs’ precision medicine initiative (the Million Veteran Program) and the first clinical trial embedded within an electronic medical record system. He founded Ariadne Labs’ informatics team and led their partnership strategy as well as the creation of a mobile phone-based system that uses real time data feedback to improve neonatal care in Uttar Pradesh, India.
He has won awards for his efforts putting health data to work for Veterans and is an invited speaker and writer on the topic of healthcare IT innovation by venues such as TEDMED, InformationWeek, and Scientific American. His work has been funded by several agencies and organizations including the Department of Defense, the Department of Veterans Affairs, the Agency for Healthcare Research & Quality, the National Cancer Institute, Helmsley Charitable Trust Foundation, and the Bill and Melinda Gates Foundation.
After decades of lagging behind other industries in the use of data, healthcare is poised for its own data-driven transformation. Journalists describe a not-too-distant future where patients, phones, Fitbits, and physicians march hand-in-hand toward a healthier tomorrow.
But not everyone is jumping for joy.
Some healthcare organizations are so frustrated with the state of health IT that the American Medical Association’s CEO James Madara, MD, last year called digital health the “snake oil of the early 21st century.” Rather than improving care and boosting professional satisfaction, many digital tools, he wrote, don’t work that well, and actually impede care, confuse patients, and waste everyone’s time.
And then there’s machine learning. Or is it artificial intelligence? Or cognitive computing? Which is which or what is what?
In his keynote, Harvard Medical School professor Leonard D’Avolio, who previously led informatics at the VA, gets to the bottom of all this confusion and disgruntlement and examines what’s hype and what’s not. And how together, once a few very real barriers are eliminated, big data and machine learning will better serve doctors, patients and families, and contribute to improved healthcare.
The U.S health care systems broad adoption of EHRs has dramatically increased the quantity of clinical data available electronically. Simultaneously, rapid progress has been made in clinical analytics—techniques for analyzing large quantities of data and gleaning new insights from that analysis. This is all part of the big data “revolution.” As a result, there are unprecedented opportunities to use big data to reduce the costs of health care in the United States.
But what exactly are those opportunities, and how are big data and analytics changing the delivery of care as we know it?
In this opening leadership discussion, our distinguished panel of healthcare data experts discuss the insights likely to emerge from clinical analytics, the types of data needed to obtain such insights, and the infrastructure—analytics, algorithms, registries, assessment scores, monitoring devices, and so forth—that organizations will need to perform the necessary analyses and to implement changes that will improve care while reducing costs