Register Now: Image-Based Risk: The Next Frontier in Breast Cancer Screening
|Videos|July 6, 2016

PQRS for Radiology

Author(s)Liza Haar

[VIDEO] What radiology practices need to know about PQRS, explained by Michael Bohl at RBMA 2016.

With some exceptions, if you didn’t reach nine PQRS measures in 2015, you will see a 2% reduction in your Medicare payments in 2017, Michael Bohl, CEO at Radiology Group PC, SC, told Diagnostic Imaging at RBMA 2016.

PQRS, the physician quality reporting system, is a CMS mandate that requires physicians report specific quality measures. Historically, physicians were responsible for reporting three measures, but in 2015, practices had to start submitting nine measures per physician, Bohl said.

PQRS has specific measures and then also includes quality registries that CMS has approved as alternatives to the basic PQRS measures, he said.

In order to avoid a cut in Medicare payments, physicians and practices need to decide which avenue they need to use to get to a total of nine measures, Bohl said. Bohl’s practice used the ACR Clinical Data registry to help them meet their PQRS measures.

“I was not going to get to nine for any of our doctors using basic PQRS measures,” he said. “It would have been very challenging.”

Exceptions are made for radiologists that have a very narrow practice, but most diagnostic radiologists have a broad enough practice that would make it difficult for them to qualify for exceptions, Bohl said.


Related to this article

Key Sessions of Interest for Radiologists at the Upcoming HLTH USA Conference
How will generative AI software be evaluated by the FDA in the future? What’s next for point-of-care ultrasound? What steps have been successful in facilitating adoption of AI applications across enterprise systems? Leaders in radiology and health care will be discussing these topics and more at the upcoming HLTH USA conference.
Current Perspectives on Integrating AI into Radiology
In a recent interview with Diagnostic Imaging, Joseph Cavallo, MD, MBA, offered insights on post-deployment monitoring with AI, the potential for improved workflow efficiency and the ongoing challenge of balancing essential clinical skills and AI literacy in the training of radiology residents and fellows.