With a mix of social engineering and Web-based dashboard management, the radiology department at the University of Maryland Medical System has reduced overall report verification times for its radiologists.
With a mix of social engineering and Web-based dashboard management, the radiology department at the University of Maryland Medical System has reduced overall report verification times for its radiologists.
Even before a report sign-off management system had been implemented, turnaround times decreased as news spread through the department that performance would be monitored, said Paul G. Nagy, Ph.D., an assistant professor of radiology at Maryland.
After two weeks of implementation, the system had reduced report verification times from 32.9 hours to 11.8 hours.
Speech recognition has been touted as a way to improve report turnaround, but it's not for everybody, Nagy said.
Rather than wait for speech recognition to improve, the department chose to optimize its current report workflow, he said during a scientific session at the RSNA meeting. To reduce both verification time for report sign-off and fatigue levels in radiologists, the department developed an in-house system for workflow data management.
The program was developed in the Python programming language. It logs on to the department's RIS four times daily and twice during the weekends to pull all unsigned summary reports. The appropriate radiologists are then paged and e-mailed to notify them that a report is awaiting their sign-off.
When the system was first announced, some radiologists expressed concern that it would represent Big Brother watching over their every move, according to Nagy. But the group developed a metric that, when represented as a cumulative Pareto, would focus on the few laggards responsible for the bulk of the delays.
"It's the law of Pareto - 80% of the problem comes from 20% of people," Nagy said.
After a few weeks, the physicians became reliant on the tool to alert them to reports that needed their attention. They admitted to liking the tool and noted that it was far less intrusive than speech recognition, according to Nagy.
The system has now been in place for over nine months. While there has been some drift in the verification time reduction, turnaround still averages about 16.4 hours, half of what it had been.
For more online information, visit Diagnostic Imaging's RSNA Webcast.
What New Research Reveals About Novice Use of AI-Guided Cardiac Ultrasound
April 4th 2025In a study recently presented at the American College of Cardiology (ACC) conference, researchers found that novice use of AI-guided cardiac ultrasound after an AI-enabled electrocardiogram increased the positive predictive value for reduced left ventricular ejection fraction (LVEF) or aortic valve stenosis by 33 percent.
The Reading Room Podcast: Current Perspectives on the Updated Appropriate Use Criteria for Brain PET
March 18th 2025In a new podcast, Satoshi Minoshima, M.D., Ph.D., and James Williams, Ph.D., share their insights on the recently updated appropriate use criteria for amyloid PET and tau PET in patients with mild cognitive impairment.
Study with CT Data Suggests Women with PE Have More Than Triple the One-Year Mortality Rate than Men
April 3rd 2025After a multivariable assessment including age and comorbidities, women with pulmonary embolism (PE) had a 48 percent higher risk of one-year mortality than men with PE, according to a new study involving over 33,000 patients.
GE HealthCare Debuts AI-Powered Cardiac CT Device at ACC Conference
April 1st 2025Featuring enhanced low-dose image quality with motion-free images, the Revolution Vibe CT system reportedly facilitates improved diagnostic clarity for patients with conditions ranging from in-stent restenosis to atrial fibrillation.