Attracting and Retaining Top Talent
The growth of artificial intelligence in healthcare is only paralleled by the fervor of its skeptics. Will AI supersede radiologists? How will this impact patient care and physician education? Is this just another dot-com-era bubble that will inevitably burst? Only a viable and sustainable technological solution withstands the rigorous obstacles to becoming mainstream, and imaging AI is most definitely up to the task. In a 3-part blog series, we will be focusing on the tangible advantages of adopting AI in your Department of Radiology. Our goal is to highlight benefits your program will reap from working side by side with Aidoc in implementing a successful AI suite. Our first post demonstrates why a stellar AI program is imperative to attracting the best radiology residents, and how programs with AI can train residents with the latest and most advanced technology medicine has to offer patients.
The advent of inculcating artificial intelligence into the arena of healthcare is moving from a nonessential amenity to an essential component of a robust radiology department. Although artificial intelligence remains an attractive buzzword that a variety of medical specialties are striving to learn how to leverage, the landscape of the field of radiology has successfully started immersing itself in forging a new future of biomedical imaging that works side by side with the most advanced technology known to mankind. Nevertheless, there are still radiology programs waiting on the sidelines, avoiding the necessary steps towards becoming an active partner in a world where AI and radiologists work together for the patient. Such programs may be wary of the proven cost-effectiveness of implementing AI, or the true value of AI on workflow, resident education, patient care, and quality of care administered. While the benefits of AI in radiology are tangible and exciting, one seemingly obvious yet commonly overlooked benefit of adopting AI is talent acquisition and retention.
Historically, radiology attracts the best and brightest residents, many of whom have strong technical backgrounds in computer science and engineering. With USMLE board scores topping the nations national average, applicants to diagnostic radiology programs are relentlessly eager to combine their passion for patient care with their savviness for healthtech. Headlines about AI replacing radiologists are ubiquitous in the popular media, and studies from the University of Chicago Medical Center and the University of British Columbia found that fears about AI are impacting how potential residents choose radiology as a career. Yet, programs with robust AI technologies already implemented into their workflow may mitigate this fear by demonstrating how AI and radiologists work synergistically. Furthermore, leading radiology programs throughout the nation (Stanford, UCSF, Duke, Yale) that have embraced AI are poised to offer their residents and attendings invaluable research opportunities in this quickly growing field. A well built AI service is a key enabler of attracting the most ambitious and talented radiology residents and attending physicians.
The robust return on investment for an AI platform is becoming tangible within radiology departments across the country. Whether it be improved prioritization or better patient outcomes, AI is ripe to revolutionize radiology for the better. Yet, the field of radiology is only as talented as the radiologists it attracts, and through being an innovative hub for research and implementation of AI, programs are better suited to attract, train, and retain only the best and brightest radiology has to offer.