Computer-Aided Reporting of Chest Radiographs: Efficient and Effective Screening in the Value-Based Imaging Era.
In the post-PACS era, mammography is unique in adopting specialized ergonomic interfaces to improve efficiency in a high volume setting. Chest radiography is also a high volume area of radiology. The authors hypothesize that applying a novel interface for chest radiography interpretation and reporting could create high productivity while maintaining quality. A custom version of the ClearCanvas open source software, EzRad, was created with a workflow re-designed specifically for tuberculosis screening chest radiographs, which utilized standardized computer generated reports. The preliminary reports from 881,792 studies evaluated by radiology residents over a nine-year period were analyzed for productivity as RVU/FTE and compared to the finalized reports from a subspecialty attending chest radiologist for accuracy. Radiology residents were able to produce 7480 RVU/FTE per year in screening chest radiography productivity when using a custom interface at a large academic medical center with a miss rate of 0.1%. Sensitivity was 77% and specificity was 99.9%. An ergonomic user interface allowed high productivity in interpretation of chest radiography for tuberculosis screening while maintaining quality.
Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, Baltimore, MD, 21201, USA. mmorris@jhu.edu.|Baltimore Veteran's Affairs Medical Center, Baltimore, MD, USA. mmorris@jhu.edu.|Mercy Medical Center, Baltimore, MD, USA. mmorris@jhu.edu.|University of Maryland Medical System, Baltimore, MD, USA. mmorris@jhu.edu.
Michael
M
Morris
Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, Baltimore, MD, 21201, USA.|Baltimore Veteran's Affairs Medical Center, Baltimore, MD, USA.|University of Maryland Medical System, Baltimore, MD, USA.
Babak
B
Saboury
Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, Baltimore, MD, 21201, USA.
Niketh
N
Bandla
Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, Baltimore, MD, 21201, USA.|Analytical Informatics, Baltimore, MD, USA.|University of Maryland Medical System, Baltimore, MD, USA.
Christopher
C
Toland
Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, Baltimore, MD, 21201, USA.|Analytical Informatics, Baltimore, MD, USA.|University of Maryland Medical System, Baltimore, MD, USA.
Christopher
C
Meenan
Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, Baltimore, MD, 21201, USA.|Baltimore Veteran's Affairs Medical Center, Baltimore, MD, USA.|University of Maryland Medical System, Baltimore, MD, USA.
Eliot
E
Siegel
Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland Medical Center, 22 S Greene Street, Baltimore, MD, 21201, USA.|Baltimore Veteran's Affairs Medical Center, Baltimore, MD, USA.|University of Maryland Medical System, Baltimore, MD, USA.
Jean
J
Jeudy
D017598:Efficiency, Organizational; D006804:Ergonomics; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007091:Image Processing, Computer-Assisted; D013902:Radiography, Thoracic / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software; D014376:Tuberculosis / Q000000981:diagnostic imaging*; D057188:Workflow
Big data; Computer aided reporting; Productivity; Screening chest radiograph; Tuberculosis; Value based care