September 15, 2017

RLI 2017: Preparing Radiologists for Constant Change

Adaptive workplaces, the eminence of artificial intelligence (AI) in health care, lean operations, and meeting customer (patient) expectations dominated conversations at this year’s RLI Leadership Summit. Led by faculty from the Babson College MBA program – and facilitated by the ACR’s leadership – the annual meeting of radiology’s best and brightest served up business-minded training challenges to the future of the field.

This year’s theme, Change is Constant, was epitomized by keynote speaker Ann LeGrand, general manager of imaging for IBM Watson Health. “We’re at a crossroads,” she told the audience. “AI is here, and we’re all going to be using it.” The tech giant has been working on health care solutions for the past decade using AI, deep learning, and machine-learning algorithms — and Watson Health now counts some 10,000 employees.

“When you look at health care today,” LeGrand said, “it’s fragmented and complex and ever-changing. Every day radiologists are asked to impact patients’ lives. The people in this room are going to help shape the future, and we want to empower radiologists with diagnostic services, quality management, and workflow optimization.”
The Watson Health medical imaging collaborative includes academic medical centers, radiology providers, and imaging technology companies. A resounding message throughout three days of training was that no one could tackle AI alone. Still, there must be strong leadership in prominent roles to represent radiologists.

Traditional approaches to leadership in the medical workplace aren’t working. That was the message of Scott Taylor, MBA, PhD, associate professor of organizational behavior at Babson. “Toxic supervisors are costing business billions, not millions, each year,” Taylor said. In his session, Coaching for Sustainable Change, he told attendees that radiology leaders must be diligent in recognizing and dealing with individuals who discourage creativity and force out the best and brightest employees (physicians). These supervisors will foster a workplace environment in which doing the bare minimum is everyone’s goal.

There were sessions by Paul Mulligan, associate professor of technology and operations management, on developing and sustaining lean operations, or the practice of creating maximum value for a practice by reducing waste and patient wait times. Mark Carr, MBA adjunct lecturer in Babson’s management division, talked to attendees about developing customer insight to find out how much radiologists really understand about their patients, their referring physicians, and other key contributors in their health network.

Matt Hawkins, radiologist and assistant professor at Emory University School of Medicine, stressed building teamwork skills and resisting the urge to approach challenging situations alone. “Radiologists have to work as part of a team even though that seems to go against all of our training,” he told the audience. And your team includes more people than you think, he added. “Invest time with the nurses, the techs, subspecialists, and other radiologists,” Hawkins said.

Time spent getting to know your team and your patients can be critical to avoiding burnout and addressing alarming rates of physician suicide. Alexander Norbash, MD, MS, FACR, summit co-director and professor and chair of radiology at UC San Diego, explained how burnout is tied to the culture of a workplace and talked about the dangers of increased repetition and high work volume. It was suggested by many leaders at the summit that AI could be an invaluable tool in thwarting burnout by reducing or eliminating mundane and tiresome radiology tasks.

Following immense interest at last year’s summit in what artificial intelligence (AI) will mean to the future of radiology, David Louis, MD, pathologist-in-chief at Massachusetts Hospital, explained how pathologists were approaching the application of artificial intelligence (AI) and related technologies. Insisting that AI would play a key role in the future of radiology as well, Louis said that ACR’s new Data Science Institute would be critical to the success of radiologists who need to learn more about adopting AI practices.

James Brink, MD, FACR, mentioned some tools ACR already provides – like ACR Assist and ACR Select – to help radiologists with the type of structured data AI relies on. He noted that when developing AI algorithms, “We, as radiologists, need to be a part of this. Letting anyone else develop it would be a bad idea.”