By Matthew J. Miller, Associate Residency Program Director, Allegheny Health Network
Continued demand for telemedicine and remote learning.
When medical historians look back on this time, the easy connection between the COVID-19 pandemic and the rise of telemedicine and remote learning will surely be made. While it is true that the pandemic necessitated an increased role for remote operations, the establishment of telemedicine and specifically teleradiology began in the years prior to 2020 with the ubiquitous rise of hospital networks and cloud storage. Successful telemedicine/teleradiology companies arose and found a niche in the market following the turn of the century, however, a stigma existed within some large health systems and especially academia that teleradiology provided suboptimal care and found the nontraditional fact that some physicians worked from home to be unacceptable. As a result, most teleradiology job openings were for less desirable overnight shifts. It wasn’t until the pandemic, however, many health systems were pushed to discover that telemedicine/teleradiology is not only acceptable, but in some instances, becoming the standard.
The ability to provide adequate care to patients at different and oftentimes remote locations all within the comfort of their home office affords radiologists the ability to spread their expertise around while streamlining their workday. The stigma of teleradiology providing suboptimal care is now gone and many accomplished imaging specialists are choosing to transition to remote positions. The elimination of the work commute and common hospital tasks has resulted in improved work-life balance for these individuals.
Radiologists are leading the charge in welcoming and establishing the role of AI in improving healthcare.
Prominent healthcare systems can now see the undeniable benefits of remote coverage which includes faster turnaround time and greater access to subspecialized care. This culture shift has led to most radiology practices employing teleradiologists in some capacity or, at a minimum, providing home reading stations for current employees so that some degree of work can be performed remotely. Employing teleradiologists allows these systems to recruit more broadly and in fact, healthcare systems that serve more undesirable locations can recruit fantastic radiologists who otherwise would have no interest to cover their facilities remotely which ultimately results in better patient care.
Medical trainees have taken note of this change in practice, as the competitiveness of matching into radiology has increased greatly. Additionally, training programs have evolved and adapted in their methods. High quality recorded lectures are now commonplace and afford residents the flexibility to learn and relearn material at their own acceptable pace. Residency programs are also able to more easily invite remote guest lecturers or subscribe to a dedicated teaching curriculum to improve their own educational or training weaknesses. Remote read-out sessions, once frowned upon, are now enhanced with videoconferencing. Even the ABR board exams are now given remotely, eliminating unnecessary spending on travel and lodging.
My specific field of breast imaging has been slow to accept remote imaging services due to the known benefits of real-time physician scanning and physical examinations. Additionally, there are stricter quality assurance checks for remote workstations that are used to read mammography. However, remote breast imaging (telemammography) services are starting to become more common due to the benefits mentioned above. The stricter QA checks have been solved with specialized software and updated self-evaluating screens. It will be essential that performance data of remote breast imagers and patient outcome data is compared to the more traditional established metrics. If early results are indicative of future performance, telemammography is here to stay.
Enhanced role of Artificial Intelligence
Artificial Intelligence has been a hot topic in medical imaging for several years now. The two main areas where the AI is establishing a role are assisting in the interpretation and optimization of efficiency. There is seemingly endless research being performed and published on the utilization of medical imaging AI.
There are some people outside the medical imaging community who erroneously believe that “radiologists will be replaced by robots” due to continued improvements with AI. While it is true that AI’s role will continue to grow and evolve, the need for human physician imagers to perform quality and accuracy checks will never approach zero. Rather, human physicians and AI will grow synergistically together and the role each plays in the care of patients must be embraced.
In breast imaging, we’ve been using a form of AI for some time called “Computer Aided Detection,” aka CAD. CAD affords breast imagers to take a second look at mammograms aiming to help limit errors in cancer detection. CAD is far from perfect, however, it has become an established useful tool that breast imagers use on nearly every mammogram that is read. As we continue to improve our mammogram machine and technique, CAD should theoretically improve as well.
Radiologists are leading the charge in welcoming and establishing the role of AI in improving healthcare. Physicians and healthcare systems should be wise to embrace the advancements and provide the necessary funding to adopt and adapt when appropriate so that they do not fall behind.