Collaboration Is Key – and Will One Day Be the Law

Dr.McGinty(updated)_andcroppedThis post is contributed by Geraldine McGinty, MD, MBA, FACR, vice chair of the American College of Radiology Board of Chancellors.

A recent Imaging 3.0 case study demonstrates the opportunities that present when radiologists and referring providers work together to ensure patients get the best imaging care.

Baylor College of Medicine radiologists Christie Lincoln, MD, and Melissa Chen, MD, worked with referring physicians to reduce unnecessary imaging for low back pain through the Radiology Support, Communication and Alignment Network (R-SCAN™).


Christie Lincoln, MD

Including educational interventions in an existing CME track in the health system encouraged referring providers, nurse practitioners and physician assistants to take part.

As a result, providers ordered nearly 38 percent fewer imaging exams for low back pain. They also increased their appropriateness rating for such orders by roughly 23 percent.

Beginning January of 2020, providers must consult appropriate use criteria (AUC) prior to ordering advanced imaging exams for Medicare patients. Imaging providers will not be reimbursed for the study if referring providers don’t demonstrate compliance.


Melissa Chen, MD

The R-SCAN program allows referring providers and radiologists to get a jump on this process, earn CME and improve the appropriateness of imaging care now. The R-SCAN program is also free to all involved.

2020 is not that far away. If your department or practice is not already taking steps to get ready, check into R-SCAN now and get ahead of the curve.

What steps are your department or practice taking to get ready for the Medicare AUC requirement?

Please share your thoughts in the comments section below and join the discussion on Engage (login required).

Finding the Best People For Our Profession

This posAm. College of Radiology-AMCLCt is contributed by Katarzyna J. Macura, MD, PhD, FACR, chair of the American College of Radiology Commission for Women and Diversity and Johnson B. Lightfoote, MD, FACR, chair of the ACR Committee for Diversity and Inclusion.  

To attract the best and brightest young doctors into radiology, we want to find the best people to serve in and to advance our profession and our practices. What defines those “best people” is multifaceted and evolving.Am. College of Radiology-AMCLC

It may require a demonstrated grasp on math and science, keen interest in applying imaging to all aspects of health care (including diagnostic and therapeutic interventions), and the ability to help make radiology more patient- and family-centered.

In increasingly multicultural communities (and elsewhere), a primary way to do that is to attract would-be radiologists from diverse cultural and ethnic backgrounds — to better mirror the populations we serve.

The ACR effort to attract more female and diverse candidates is taking concrete steps forward through the Medical Education & Student Outreach effort.

The ACR Commission for Women and Diversity has partnered with Nth Dimensions and other outside stakeholders to introduce medical students to our field early — particularly those from backgrounds underrepresented in our specialty.

The Pipeline Initiative for Enrichment of Radiology (PIER) program is in the second year of offering internships for first-year medical students with radiology and radiation oncology departments and practices. We urge practice leaders to volunteer to host an intern. We also ask radiologists to invite medical students they may know to apply for 2019 Radiology Summer Internships when the application process opens Dec. 1, 2018.

A number of ACR members — in collaboration with the AMA Medical Student Section (AMA MSS), American Medical Student Association (AMSA), Student National Medical Association (SNMA) and various institutions — are speaking directly to medical students at mentoring events and workshops around the country.

ACR members are also volunteering to serve as mentors to medical students through a match program featured on the AMSA website.  If you are interested in becoming a radiology mentor or hosting a summer internship in 2018 (or beyond), I encourage you to contact the ACR.

These efforts do not mean the College values the contributions of any current or prospective members less. It is a challenge that has to be met to stay ahead of the changing needs of our patients and society.

These efforts will strengthen our specialty and enhance the care we provide in every corner of America. 

Please share your thoughts in the comment section below or on Engage (login required).

The Taming of the AI Wild West Has Begun

Am. College of Radiology-AMCLCThis post is contributed by ACR Data Science Institute™ (DSI) Chief Medical Officer Bibb Allen Jr., MD, FACR.  

The FDA-funded NESTcc program has chosen the ACR Data Science Institute™ (DSI) “Lung-RADS Assist” use case among its first demonstration projects. This is a step to move artificial intelligence (AI) into medical imaging work flow and a leap toward taming what has been a technological “wild west.”

Use cases are clinical scenarios in which AI use may improve care. Until now, there has been no national body to identify or develop such cases to ensure safe and effective implementation in clinical practice.

No other national organizations are yet involved in determining if algorithms developed by vendors actually answer a relevant clinical question to improve care. This process is an initial focus of the ACR DSI.

The Lung-RADS Assist use case will determine the end-to-end workflow from development and deployment of an AI algorithm in a radiology reporting system and capture of performance metrics in a national registry.

With this process, the dark corners of the imaging AI map will start to be filled in. Just as the iron horse of the nation’s railroads helped settle the west, the ACR DSI is laying the track to move imaging AI into radiology’s future.

  • What are some use cases where you see that imaging AI can help radiologists do their jobs better (more efficiently)?
  • Where do you think imaging AI will be in 5-10 years?

Please share your thoughts in the comment section below or share them on Engage (login required).