OR WAIT null SECS
Radiologists can use data to demonstrate value, from RSNA 2016.
It’s no secret in radiology that there’s a continuously growing push for radiologists to demonstrate the value they bring to both health care as a whole and to patients.
According to industry experts, one of the best ways you can highlight your contributions is through leveraging the data already at your fingertips.
Radiology leaders at RSNA 2016 provided insight into the challenges you currently face in meeting this goal and ways you can improve your performance going forward.
Current mandates ranging from Meaningful Use to the Physician Quality Reporting System make your job complex, but it’s not impossible, they said. While your professional judgment remains critical to ultimately making the best decision for your patients, your greatest tool in the future will be machines and their increasing ability to learn how you use data and the language you employ.
To date, said Michael Zalis, MD, an interventional radiologist at Massachusetts General Hospital, available software systems don’t always offer the level of access to patient data you need to make the best decisions for individual patients.
Two main challenges, he said, are a lack of data needed to make informed decisions for individual patients and hurdles surrounding pre-authorization approvals for diagnostic studies.
Making the correct decision without enough knowledge of a patient’s medical history, lab results, previous studies, or ontologies is difficult. Although some version of an EMR is in use in almost all hospitals and clinics, that doesn’t mean the information trickles down to radiologists.
In addition, referring physicians frequently leave the responsibility of gaining approval for diagnostic studies to their office staff. Many of these individuals often lack the clinical knowledge needed to garner approval for a CT or MRI.
To address these roadblocks, Zalis said, future machine tools will use data in a more active way.
“There are many components to demonstrating the value of radiology as our practice evolves,” he said. “Current tools are evolving from structured and static to dynamic and patient-centered. Assistant clinical reasoning tools are these types of systems. Expect to see rapid evolution in them soon.”
As an example, he said, Massachusetts General Hospital developed its own surgical appropriateness system, Procedure Order Entry (PrOE), to help providers and staff identify whether a procedure is necessary. Although it’s not designed for radiology, the premise is translatable – the software is programmed with appropriateness guidelines published by specialty societies, and, based on the query posed, the tool searches through available information to suggest the best course of action.
Adding Patient Data to Add Value
Even as the growing digitization of health care pushes you away from the patients you care for, said Arun Krishnaraj, MD, a radiologist with the University of Virginia (UVA) Health System, you must – and can – make your value more prominently visible.
“If we’re not careful, our role will be commoditized,” he said. “There’s greater pressure on us as a profession to demonstrate how we add value. Does this portend a dystopian future for us or are we destined for Sky Lab?”
Solidifying your value, he said, means pulling more patient data into your decision-making. According to a recent UVA analysis study, there’s room for growth here. The report revealed, on review, 12% of 400 radiology reports required changes – 22% of which were emergency cases.
The best way to access more patient data is to find software with a clean, simply-designed user interface that lets you dig deeply into the patient’s EMR. Such a system should be designed to constantly learn what a radiologist searches for and to provide that information more rapidly over time. For example, Massachusetts General developed QPID (Queriable Patient Interface Dossier) to integrate the facility’s EMR and streamline providers’ abilities to access details in a patient’s medical history.
These tools are becoming more common, he said, and radiologists must tap into them.
“We have the opportunity to do some really important work by incorporating these tools that come around,” Krishnaraj said. “It’s not the machine that’s important, it’s our ability to leverage that deep learning and artificial intelligence to get more out of the information already available to us.”
Why It’s Critical
Making the greatest use out of information already available is paramount for two reasons, said Giles Boland, MD, chair of radiology at Brigham and Women’s Health Care. First, it improves your ability to provide precision medicine, and second, it can help you learn to improve and augment your reports in the future.
Using tools capable of deep machine learning will give you the detailed patient data needed to make the most informed decisions in light of a patient’s individual challenges. This knowledge allows you to create the most actionable report, he said, and positively impact patient outcomes.
On the flip side, the tools also open you up to feedback. Based on the information you put into your report, your colleagues can offer their perspectives on how you can best serve patients in the future. They can suggest changes to the language you use or point out places where you could more strictly adhere to appropriateness guidelines.
Ultimately, Boland said, the tools are growing in importance, but they are still only part of the equation for improved patient care. Your involvement, as the radiologist, is still required.
“These are just tools. Judgement is necessary,” he said. “Adopt the tools, and let’s deliver better practice performance in accordance with the guidelines. We’ll better protect patient needs if we embrace the tools – they’re here to help.”