Informatics in radiology: Efficiency metrics for imaging device productivity.
Acute awareness of the costs associated with medical imaging equipment is an ever-present aspect of the current healthcare debate. However, the monitoring of productivity associated with expensive imaging devices is likely to be labor intensive, relies on summary statistics, and lacks accepted and standardized benchmarks of efficiency. In the context of the general Six Sigma DMAIC (design, measure, analyze, improve, and control) process, a World Wide Web-based productivity tool called the Imaging Exam Time Monitor was developed to accurately and remotely monitor imaging efficiency with use of Digital Imaging and Communications in Medicine (DICOM) combined with a picture archiving and communication system. Five device efficiency metrics-examination duration, table utilization, interpatient time, appointment interval time, and interseries time-were derived from DICOM values. These metrics allow the standardized measurement of productivity, to facilitate the comparative evaluation of imaging equipment use and ongoing efforts to improve efficiency. A relational database was constructed to store patient imaging data, along with device- and examination-related data. The database provides full access to ad hoc queries and can automatically generate detailed reports for administrative and business use, thereby allowing staff to monitor data for trends and to better identify possible changes that could lead to improved productivity and reduced costs in association with imaging services. © RSNA, 2011.
School of Computing, Informatics and Decision Systems Engineering, Arizona State University, Tempe, Arizona, USA.
Mengqi
M
Hu
William
W
Pavlicek
Patrick T
PT
Liu
Muhong
M
Zhang
Steve G
SG
Langer
Shanshan
S
Wang
Vicki
V
Place
Rafael
R
Miranda
Teresa Tong
TT
Wu
D000465:Algorithms; D003952:Diagnostic Imaging / Q000295:instrumentation*; D004526:Efficiency; D019544:Equipment Failure Analysis / Q000379:methods*; D008490:Medical Informatics / Q000379:methods*; D013673:Technology Assessment, Biomedical / Q000379:methods*; D014481:United States