Radiology is Data-Rich, Information-Poor

At SIIM 2015, Rasu Shrestha, MD, MBA of the University of Pittsburgh Medical Center thought this quote by Einstein was fitting for radiology: “We cannot solve our problems with the same thinking we used when we created them.”

Shrestha was referring to radiology’s problem with defining value. The word “value” basically echoed through the halls of the Gaylord National Resort and Convention Center, but Shrestha had an interesting perspective.

“I don’t think we could have been talking about value-based health care or value-based imaging 10 years ago,” Shrestha said. He explained that it’s a problem we have now because of the innovative technology adapted over the last decade.

In 2015, radiologists might have fancy diagnostic workstations, RIS, PACS, 3D, voice recognition, but not much else has really changed in terms of what a radiologist does.

“We’re still looking at a series of imaging at a time,” he said. “So have we really progressed?”

The problem with radiology, perhaps not just today, but always, is that it is image-centric and not patient-centric, Shrestha said.

“It’s the study that ends up in your worklist and you’re inundated with studies,” he said. “Your core objective is to get to a zero worklist, and that’s how [radiologists] are wired.”

Shrestha echoed the sentiment that radiology created its own silos, perhaps unintentionally, with PACS and RIS. He asked, “If we were to start all over again, would we really create the silos that we ended up with today?”

Radiology is data-rich and information-poor, he said. Or radiologists have too much information and not enough intelligence. The divide is in the lack of patient context, he said. It requires radiologists to be detectives.[[{"type":"media","view_mode":"media_crop","fid":"38476","attributes":{"alt":"","class":"media-image media-image-right","id":"media_crop_467649300057","media_crop_h":"0","media_crop_image_style":"-1","media_crop_instance":"3821","media_crop_rotate":"0","media_crop_scale_h":"0","media_crop_scale_w":"0","media_crop_w":"0","media_crop_x":"0","media_crop_y":"0","style":"float: right;","title":"Rasu Shrestha, MD, MBA ","typeof":"foaf:Image"}}]]

“We’re more detectives than we are clinicians, which is a sorry state to be in 2015,” Shrestha said.

Data and context is king, he said.

“How do we free the data so we are able to get to clinical insights at the point-of-care and liberate the data such that we’re able to connect across all of these silos so that we have more of a patient-centric view and not an image-centric view?” he asked.

Context, largely missing in radiology today, is fundamental to quality because if quality is measured by a diagnosis, it’s important for radiologists to have the entire context. The enterprise imaging concerns need to be addressed in scalable ways that allow radiologists to have this patient-centric vision, he said.

Health care reform and consolidation are two of the trends leading the future of radiology. But with these challenges come opportunities, Shrestha said. Consolidation brings challenges of interoperability, efficiency, and the need to do more with less, he said. Health care reform forces radiology to move from a volume-based practice to one of value.

Both challenges present opportunities for data. “Data is gold,” Shrestha said.

Data liquidity is about freeing up data from the silos of information systems and liquidating those assets, he said. “The reason we continue to do the things we’ve been doing is we have not been able to liquidate those assets and connect the dots across the board and bring out the true context,” he said.

This will allow radiologists to stop playing the role of detective.

Innovation and technology can be leveraged to push for data liquidity, Shrestha said. “So we can spend less time with our information systems and more time with our patients, and our peers; more time collaborating and communicating.”

The goal is to simplify, he said. Innovation isn’t just about adding things, it’s about removing as much as possible so that the bare minimum of what is required to function as optimally as possible is achieved, Shrestha said.

Phase one was analog, radiology then invented PACS and RIS, which brought radiology to phase 2: digital. Shrestha said we are in phase 3 now, in which radiology needs to strive for interoperability, analytics, personalized medicine, and managing risk in an intelligent way.

“The next generation of solutions is more patient-centric, not film-centric, with predictive protocols and automated processes,” he said. “We are able to leverage newer technologies such as cloud and enterprise content management and intelligence of the back end to connect the dots across the information silos.”

The evolution of the imaging workspace is what Shrestha calls a system that sits on top of image-related clinical context. The system would pull all of the relevant data from the silos of information systems that exist outside of the radiology department, because the crux of the information about the patient isn’t in the silo radiology uses today, it’s everywhere else, he said.

The data is aggregated and harmonized with a core level of focus on human-centered design and user-experience, which Shrestha said is sorely missing in today’s systems.

This will provide for more opportunities for measurement, as well, he said. “You can only improve what you measure.”

Oftentimes, radiologists are helpless with measuring value-based imaging because by the time the radiologist sees the study in their worklist, the crime has already been committed. “Radiologists need to get to the scene of the crime, and that’s at the time the study gets ordered,” Shrestha said.

There are multiple facets to measure in the value chain of imaging, Shrestha said: Reading exams, reporting results, communication, collaboration, how the report gets interpreted and dispersed to the patient, and the tracking of outcomes.

“If you recommend a follow-up in your report, was it done? Shrestha asked. “Do we care? Should we care?”

By leveraging technology, the right solutions can be created to push these metrics forward, he argued. It’s about making the systems transparent and visible so that the data is able to flow and drive an intelligent workflow.

Shrestha argued that radiology needs to show health care how getting value is done. Patient-centric collaborative intelligence is where value lies for radiology and that’s all in the data.