Establishing concrete protocols for logging unanticipated events in MRI can help imaging practices establish internal performance benchmarks and make data-driven decisions on resource allocation, according to a study published in the Journal of the American College of Radiology.
Faculty and staff from Emory University School of Medicine found a 16.7 percent rate of unanticipated events during MRI exams, dominated by non-contrast patient-related issues. While that rate matches published literature and was relatively expected, the project served as a healthy benchmark of unanticipated events across the Emory system, according to co-author and Director of Neuroradiology Amit M. Saindane, MD.
“The goal was to see what the variability was across various sites in our system,” he said. “Acquire this information and then use it to figure out what specific problems are in particular locations. There’s no hope of trying to fix the issue unless you know where the issue is happening.”
While some institutions still use pen-and-paper logs of unanticipated events, Emory University implemented a software called REDcaps, normally used for tracking data in research projects. When a technologist is completing a study he or she can open REDcaps directly from their image management software and answer a short series of questions, including whether or not there was an unanticipated medical device, contrast reaction, or excessive patient motion. Brevity and ease of use are crucial, according to Saindane.
“We’ve focused in on some of the more important issues, we’re not bombarding them with 50 different questions,” he said. “There’s also better compliance from the technologists when they don’t have to go to a different system. For anyone thinking of doing something similar to this, that’s one of the barriers to consider.”
The study authors collected REDcap data from June 2013 through November 2014, finding patient motion was the top problem under the umbrella of patient-related issues. The rate of events was significantly higher with inpatients rather than outpatients, mostly because inpatients are generally in worse condition. According to Saindane. this prompted the researchers to consider quality improvement initiatives to enhance communication amongst faculty and staff.
For example, some inpatients need to be sedated to decrease motion during an exam. Using pre-exam checklists and schedulers to ensure the anesthesia team arrives at the right time can reduce delays, in turn improving turnaround times. The authors said this has downstream effects: Shorter turnaround times mean more patients are seen during the day, when the imaging department is fully staffed. Additionally, it may free up hospital beds if the patient’s discharge is contingent on the results of the imaging exam.
“For any practice that is looking to base decisions on where they apply resources through something like this, it’s a useful method,“ said Saindane. “If a particular practice is worried about unanticipated events, they can get an idea if their numbers are similar to other practices or if they’re excessive.”
This system simplifies tracking both quantitative and qualitative data about unanticipated events—to such a degree, they’ve already used this data in discussions with hospital administrators.
“If the rate of delays at one site is three times what they are at a different site, it gives us data to back up those claims,” said Saindane. “It lets us know there’s something we need to fix and we need to devote resources to fixing it.”
One curiosity noted by the authors was the higher rate of reported unanticipated events across all categories at university-affiliated sites, possibly indicating differences in reporting culture or procedure.
“In many institutions the number of unanticipated events may be under reported,” said co-author Gelareh Sadigh, MD, a fourth-year diagnostic radiology resident at Emory. “Two things we’ve done are improve the [reporting] culture—especially with technologists—and make the system user-friendly which can increase the amount of reporting.”
Electronic tracking of unanticipated events in an imaging practice can reveal areas of concern, especially when compared to similar locations across a health system. Harvesting actionable data will become increasingly important as outcome-based reimbursement becomes the norm and reporting systems like this represent the future of clinical data mining.
“Not only does this study provide a window