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To objectively and subjectively evaluate a large, academic radiology department's transition to electronic health record (EHR) centered workflow.Multiple metrics were compared from before and after the move to EHR-driven workflow. Examination ordering and reading priority data were obtained for 30 days both before and after the transition. Sixteen radiologists were observed opening a computed tomography (CT) examination, and time to open, mouse clicks, and keystrokes were recorded. Information available to the radiologist during interpretation was also compared. Additionally, a 12 question survey was sent out to the residents and faculty both before and after the transition.Implementation of an eight-level reading priority system increased worklist granularity and improved identification of more urgent studies to read. Radiologists opened CT studies in picture archiving and communications system-driven workflow in 52.4 ± 16.9 seconds using 9.5 ± 3.9 clicks and 6.3 ± 2.9 keystrokes, compared to 17.3 ± 9.5 seconds, 4.8 ± 1.5 clicks, and 0.1 ± 0.3 keystrokes in EHR-driven workflow (p0.001 for each measure). More information was available to the radiologist during examination interpretation, and 54.7% of radiologists rated the ease of use of the new system as good or very good (compared to 4.2% for the old system, p0.001).Transitioning to an EHR-driven workflow at a large academic medical center improved efficiency, was favorable to radiologists, and enhanced examination prioritization.

Rationale and Objectives The aim of this study was to assess if graphical user interface screen-capture software applied to a magnetic resonance (MR) hardware console could nonintrusively allow the analysis of discrepancies between expected and experienced MR table time. Materials and Methods Individual MR examination acquisition processes were captured in audio-video interleave streams for 10 patients who underwent comprehensive liver MR imaging. These audio-video streams were dissected into periods of true image data acquisition, scanner activity without direct image data acquisition, and scanner inactivity. Results Total expected time required for standardized liver MR image acquisition was estimated at 15 minutes. Experienced table times varied highly, ranging from 19:00 to 58:08 minutes. Image data acquisition occurred during approximately 58% (range, 43.3%–73.7%) of overall table time. Image data were obtained approximately 77% (range, 65.6%–87.0%) of the time the scanner spent active. Conclusion Graphical user interface screen-capture software installed on an MR console nonintrusively revealed significant periods of table time spent not obtaining true image data and explained discrepancies between expected and experienced MR table times. Table-time calculations using Digital Imaging and Communications in Medicine image headers and scanner-logged time stamps are underestimations of true table time because they do not take into account some scanner activities not directly leading to image formation.

The aim of this study was to assess if graphical user interface screen-capture software applied to a magnetic resonance (MR) hardware console could nonintrusively allow the analysis of discrepancies between expected and experienced MR table time.Individual MR examination acquisition processes were captured in audio-video interleave streams for 10 patients who underwent comprehensive liver MR imaging. These audio-video streams were dissected into periods of true image data acquisition, scanner activity without direct image data acquisition, and scanner inactivity.Total expected time required for standardized liver MR image acquisition was estimated at 15 minutes. Experienced table times varied highly, ranging from 19:00 to 58:08 minutes. Image data acquisition occurred during approximately 58% (range, 43.3%-73.7%) of overall table time. Image data were obtained approximately 77% (range, 65.6%-87.0%) of the time the scanner spent active.Graphical user interface screen-capture software installed on an MR console nonintrusively revealed significant periods of table time spent not obtaining true image data and explained discrepancies between expected and experienced MR table times. Table-time calculations using Digital Imaging and Communications in Medicine image headers and scanner-logged time stamps are underestimations of true table time because they do not take into account some scanner activities not directly leading to image formation.