HealthCare Business News recently spoke with Dr. Gregory N. Nicola FACR, executive leadership, Hackensack Radiology Group, and ACR MACRA chair about quality metrics and value-based care, and how radiology plays a part.

According to Nicola, radiology’s quality metrics are moving toward diagnostic accuracy measures. “In other words, did our interpretation match the downstream pathology or surgical findings?” he explained.

One of the barriers for radiology-specific measures is that they are unfamiliar to many other providers outside of the specialty including clinicians and hospitals, but also payors. “Comparing us to a gold standard like pathology is exactly where we think one focus of quality measurement should be. However, we have had payors state our proposed diagnostic accuracy measurements are really disease prevalence measurements, and therefore difficult to compare across disparate populations” he said.

“So there’s a disconnect in accepting some of our measures, but I think we have a lot to offer in other quality measure development areas, not only in the diagnostic accuracy, but also in efficiency type measures. What I mean by that is ‘are the radiologist’s recommendations incorporating cost-effective, appropriate, standardized recommendations that decrease variability of downstream medical events including repeat imaging?’”

Nicola plays an active role with the ACR and sits on a technical expert panel for quality measurement development in radiology, so his questions hold weight. His input also plays a part in helping societies develop measures to standardize follow-up recommendations in radiology, helping to reduce variability and decrease cost. “I think that’s really worth looking into,” he said. “We can add a lot of value to the health care system, particularly by decreasing variability of follow-up imaging.”

While the development of quality metrics is moving along, there are other challenges tied to value-based care. For example, radiologists still have to contend with redundant imaging procedures. “It’s probably the greatest barrier for radiologists in attempting to play an active role in being cost effective,” Nicola acknowledged. “Those of us trying to practice value-based care have little access to what the patient had done in the past if they were at a disparate institution.”

Nicola feels that the challenge shouldn’t even exist, “It’s ridiculous, because technologically, it’s seamless to share images. It just doesn’t happen in the practical sense.”

The current state of health information exchange generally excludes imaging, and when it does include it, it is flawed, in that it doesn’t integrate with a radiologist’s work flow.

There are three broad ways to exchange health information, according to Nicola. The first is patient-driven, meaning patients have full access to whom they deliver their health information to, including prior imaging. The second is physician-directed, where the referring physician has the option to share images with radiologists. The third is the query-based exchange, which utilizes database queries to find anything done on a patient. The first two are essentially non-starters for radiologists. “The reason why those two types of exchanges don’t work particularly well in radiology is because very few people understand what could prevent the next study in radiology, except for the radiologist,” Nicola said.

He offered an example; “There are times that I might see an abnormal kidney mass on a CT abdomen/pelvis, but an MR lumbar-spine from 10 years ago could prevent a follow-up imaging and I don’t think patients or doctors connect, ‘oh this lumbar MR might help on a CT with kidneys.’ They don’t connect that, but it turns out that occasionally, the MR picks up a little bit of the kidney and if you see the mass from 10 years ago, you know it’s probably nothing to worry about. So really, the radiologist needs to have access to all of the patient’s prior imaging, and they need to be able to acquire it themselves, with the patient’s permission, but it has to be us who are really searching for that prior imaging.”

Ideally, Nicola said, that search would be done automatically with matching paradigms and protocols in place, so it can be incorporated into the radiologist’s workflow, as opposed to having to sit at a separate workstation and actively pull it. “I think artificial intelligence could play a big role facilitating the query of databases, initiating the process of acquiring prior imaging from a broader database, and delivering those images to PACS prior to our interpreting the case. That would be huge leap for the specialty toward practicing high quality cost-effective care, but it doesn’t exist right now. So we’re stuck with the physician-based or patient-based exchanges that are really not helping our workflow or cutting redundant imaging.”

Even with those challenges, Nicola feels that radiology will be a big factor in value-based care, specifically because of the work being done in standardization of how radiology reports are structured, and how recommendations are made. “I think radiology is at the forefront of the standardization movement,” he said. “Because mainly, it’s a technology-driven specialty. People that go into it rely on technology and understand standardization is vital for data mining. Once you’ve done this, using the full-power of machine learning algorithms will be at our fingertips; we’ll really be able to use data to drive care, the foundation of change management. We will eventually have robust data sets allowing us to recommend the correct treatment or cost-effective standardized follow-up recommendations without the large amount of variability inherent in the current practice of the specialty.“