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    Ty Vachon

    Ty Vachon, MD, Discusses AI's Potential to Transform Radiology

    Global Impact: Rebecca Rock, RN and SABM CFO talks with HPI about two roles across two countries

    From Lab Trend Visionary to Dark Group CEO: HPI connects with the Founder and Editor of the Dark Report, Robert Michel

    Two Imaging Leaders, Two Systems, One Outcome: Communication

    From Communication Strength to Just in Time Reopening at MGH A conversation with Dr. James Brink, Chief of Radiology at Massachusetts General Hospital

    From Time Magazine to PBM Influencer: Sherri Ozawa's Mission to Define the Value of Blood

    Buried Blessings: Pandemic perspective from Tom Strauss, CEO at Sisters of Charity Health System

    Katie Castree, Career Healthcare Process Improvement Connoisseur

    Solving Lab Challenges through Recruiting Innovation: HPI connects with Lighthouse Lab Services President, Jon Harol

    Providing Value-Based Care in a Pandemic through Telehealth and Data Resources: An HPI exclusive with Dr. Darrel Weaver

    From Supply Chain Crisis to Innovation in a Pandemic

    From Navy Medic to running a Clinical Laboratory . . . during a pandemic

    Planning for Blood Shortages in a Pandemic with Dr. Claudia Cohn

    Blood Banking is more complex today than ever before. Rob Van Tuyle, President of Vitalant's Blood Division, tells us why.

    Profoundly Impacting Healthcare with Breakthrough Anemia Management

    Supporting Imaging Precisely Where You Need It

    Working Together Makes End of Life Conversations Easier to Have

    The Future of Imaging: Assessing the early impacts of COVID-19 and the path to innovation through Artificial Intelligence (AI) A conversation with Dr. Geoff Rubin

    Pivoting in a Pandemic: How a U.S. 3D printing manufacturer is helping healthcare in its time of need

    Mara G. Aspinall: Diagnostic evangelist educating the world on the power of diagnostics today

    How The Joint Commission is addressing the COVID-19 Pandemic

    CHI Nebraska’s Laboratory Director Connie Wilkins, describes How To Manage a Clinical Laboratory During the pandemic

    Former Commercial Lab Leader Highlights the Hospital Lab as the Solution to Community Sustainability in a Healthcare Crisis

    Three Phases Essential to Crisis Preparedness in Patient Blood Management with Anne Burkey of St. Luke's Health in Boise, ID

    The Importance of Agility in Your Lab

    Dr. Paul Biddinger Shares Three Ways to Prepare for COVID-19

    Bringing Clinical Skills to Operational Leadership During a Time of Crisis; Dr. Blanton, Chief Medical Officer at Peterson Health

    7 Team Attributes to Teams that Work in Challenging Times & Through Rapid Innovation

    From Finding Problems to Saving Lives: The Evolution of Interventional Radiology

    Identifying the Potential with AI in Radiology with Dr. Chung

    Communication in the C-Suite with Cliff Robertson of Catholic Health Initiatives

    Reviewing Your Patient Financial Journey with Melody W. Mulaik, President of Revenue Cycle Coding Strategies

    Ask An Accumen Expert: Carolyn Burns, MD, a Patient Blood Management Advocate

    Linda DeVee, Leads Radiology Services at Edward-Elmhurst Health

    Theresa Mouton, Market Chief Financial Officer with Steward Health

    PELITAS President and CEO Steven Huddleston Wants Patients to Have a Great Experience – Both Clinically and Financially

    How Do You Deal with 2 Billion Forms a Year? Ask Randy Campbell

    Medical Director of Telehealth for UAB Knocks Barriers Down to Treat Patients on Their Terms

    C-Suite Spotlight: Wayne Bohenek Chief Ancillary Services Officer, Bon Secours Mercy Health

    A Leader in the Laboratory Service Line : Pierre Mouawad

    Healthcare Partner: Autumn Farmer, Chief Laboratory Officer, Bon Secours Mercy Health

    How Imbio is using AI to close the gap of missed diagnosis with Mike Hostetler

    Spit Matters with Bill Phillips from Spectrum Solutions

    How COVID-19 inspired TeraRecon to accelerate their imaging solutions to the point of care with Jeff Sorensen

    Ty Vachon, MD, is a practicing radiologist and speaker and author on machine learning in medical imaging and healthcare. He is determined to provide clinically useful tools for his healthcare colleagues to best leverage the vast amounts of data generated daily. He is a 16-year U.S. Navy veteran and lives in San Diego, California.

    Dr. Vachon credits his success to some great advice he received from a teacher: “be the best learner in the room and keep it simple.” It’s a maxim that he has followed diligently as a physician and healthcare leader, from his time in medical school to his career in the Navy. During his military service, he was a flight surgeon with the Marine Corps deployed to the Persian Gulf in 2009. He returned to focus on radiology, where he became fascinated with machine learning. Recently the Healthcare Performance Insider caught up with Dr. Vachon and learned more about why he describes himself as a radiologist, informaticist, medical imaging domain expert, and machine learning enthusiast.

    During my residency, I became fascinated with the data that goes from the electronic medical record to the PACS, to the radiology information system, how complex that is, and how far behind we are compared to regular business intelligence. And so, one of my biggest projects as a radiology resident was looking at how we can move data better between disparate systems. That has grown to other things that I’ve done in my post-radiology career.

    Over the past couple of years, Dr. Vachon has been working with healthcare IT companies, working alongside computer scientists and data scientists to share information about the field of radiology and how radiologists work in order to implement the clinical perspective into their workflows.

    Using data to improve healthcare
    Electronic health and medical records are perfectly designed to get a little bit of building data and not share it. From a patient’s standpoint, that’s terrible. That is not well designed for a dynamic medical environment and a world where we have all of these application interfaces where everyone connects things.

    If data were clean and accessible, Dr. Vachon argues, the healthcare industry would improve dramatically. We would be able to improve healthcare, making it infinitely better than it is now. However, that’s where the crux is. The crux is, how do we capture that data and make it usable? One example is if we were on a telemedicine encounter right now, there are all kinds of data that are not being captured. We could be turning this conversation into text. We could be seeing if I’m nervous or calm or you’re nervous or calm. All of these things can be easily done. Starting with clean data, and putting it in the right place, is going to be the key to improving healthcare.

    Helping more people
    Dr. Vachon hopes to use his experiences as a healthcare leader, a flight surgeon, and a radiologist to apply transformative ideas at greater scale. One way to do this, Dr. Vachon said, is to put useful tools in people’s hands. As one of his favorite books, The Checklist Manifesto, argues, people can use checklists to decrease variability and increase quality on any process. However, that’s not always the way things are done in healthcare, which can be to patients’ detriment.

    Dr. Vachon’s mission is to help build tools that create an augmented intelligence scenario where we have AI pulling data or AI taking clean data and finding predictive elements to work with leadership to help providers and help patients.

    To do that, he draws on his commitment to ongoing learning, researching new, FDA-approved algorithms and keeping up on innovations in the field of radiology. He shares the results of his research, so that practicing radiologists across the country can benefit from the latest knowledge at the intersection of radiology and AI. Two years ago, Dr. Vachon pulled his insights together into a book, AI and Machine Learning for Radiologists.

    Radiology in the time of COVID-19
    Things have changed for everyone during 2020’s COVID-19 pandemic. Dr. Vachon keeps busy with a few hours each week of teleradiology. He also continues to advise healthcare IT companies working to bring AI and machine learning insights into radiology. Many of the companies that I advise were able to go head down and really start working on research and development. The companies he works with are asking questions at the forefront of innovation: How do we parse data? What are some different ways to look at data integration? How does this impact the user interface?

    Looking to radiology’s future
    How will AI impact the day-to-day practice of radiology in the next five years? The FDA has approved about 80 AI algorithms for radiology. However, when a human radiologist looks at a CT, or an MRI, or even an X-ray, that radiologist is looking at around 10,000 different details. This is recently well documented in the medical literature, that there are 10,000 things that radiologists look for. And if there are only 80 FDA-approved algorithms, we have a long way to go. I think 1,000 algorithms is a great benchmark, because 1,000 algorithms would represent one-tenth of the things that I work at or look at. At the 10 percent level, radiologists would be able to use AI to improve their workflows.

    Right now, according to Dr. Vachon, there is a lot of hype around artificial intelligence and machine learning in radiology. However, he cautions, with so few algorithms, it’s just not that helpful. And despite all the hype, the vast majority of the 30,000 radiologists in United States don’t use it – me included. It’s not part of my regular workflow, we have a long way to go for it to become usable to really start helping patients at scale.

    But there are many other ways AI can help the field of radiology. Those 80 algorithms, and the 10,000 things radiologists look for, those are solely within the scan itself. That doesn’t include the protocol of the exam, the ordering of the exam, the billing of the exam, or the scheduling of the patient. All of these other things have decisions that can be augmented by an intelligence system, machine learning included.

    Dr. Vachon is optimistic, looking forward. He is hopeful that the whole radiology patient care ecosystem will rise together to include evaluation of images, the patient’s experience, and the process by which we take care of the patient.

    Ty Vachon

    Ty Vachon

    MD, Radiologist, Speaker and Author", Aryeh Shander