TY - JOUR
T1 - Development of an Automated Bone Mineral Density Software Application
T2 - Facilitation Radiologic Reporting and Improvement of Accuracy
AU - Tsai, I. Ta
AU - Tsai, Meng Yuan
AU - Wu, Ming Ting
AU - Chen, Clement Kuen Huang
N1 - Publisher Copyright:
© 2015, Society for Imaging Informatics in Medicine.
PY - 2016/6/1
Y1 - 2016/6/1
N2 - The conventional method of bone mineral density (BMD) report production by dictation and transcription is time consuming and prone to error. We developed an automated BMD reporting system based on the raw data from a dual energy X-ray absorptiometry (DXA) scanner for facilitating the report generation. The automated BMD reporting system, a web application, digests the DXA’s raw data and automatically generates preliminary reports. In Jan. 2014, 500 examinations were randomized into an automatic group (AG) and a manual group (MG), and the speed of report generation was compared. For evaluation of the accuracy and analysis of errors, 5120 examinations during Jan. 2013 and Dec. 2013 were enrolled retrospectively, and the context of automatically generated reports (AR) was compared with the formal manual reports (MR). The average time spent for report generation in AG and in MG was 264 and 1452 s, respectively (p < 0.001). The accuracy of calculation of T and Z scores in AR is 100 %. The overall accuracy of AR and MR is 98.8 and 93.7 %, respectively (p < 0.001). The mis-categorization rate in AR and MR is 0.039 and 0.273 %, respectively (p = 0.0013). Errors occurred in AR and can be grouped into key-in errors by technicians and need for additional judgements. We constructed an efficient and reliable automated BMD reporting system. It facilitates current clinical service and potentially prevents human errors from technicians, transcriptionists, and radiologists.
AB - The conventional method of bone mineral density (BMD) report production by dictation and transcription is time consuming and prone to error. We developed an automated BMD reporting system based on the raw data from a dual energy X-ray absorptiometry (DXA) scanner for facilitating the report generation. The automated BMD reporting system, a web application, digests the DXA’s raw data and automatically generates preliminary reports. In Jan. 2014, 500 examinations were randomized into an automatic group (AG) and a manual group (MG), and the speed of report generation was compared. For evaluation of the accuracy and analysis of errors, 5120 examinations during Jan. 2013 and Dec. 2013 were enrolled retrospectively, and the context of automatically generated reports (AR) was compared with the formal manual reports (MR). The average time spent for report generation in AG and in MG was 264 and 1452 s, respectively (p < 0.001). The accuracy of calculation of T and Z scores in AR is 100 %. The overall accuracy of AR and MR is 98.8 and 93.7 %, respectively (p < 0.001). The mis-categorization rate in AR and MR is 0.039 and 0.273 %, respectively (p = 0.0013). Errors occurred in AR and can be grouped into key-in errors by technicians and need for additional judgements. We constructed an efficient and reliable automated BMD reporting system. It facilitates current clinical service and potentially prevents human errors from technicians, transcriptionists, and radiologists.
KW - Bone mineral density
KW - DXA
KW - Open source
KW - Radiology reporting
KW - Workflow
UR - http://www.scopus.com/inward/record.url?scp=84949501160&partnerID=8YFLogxK
U2 - 10.1007/s10278-015-9848-7
DO - 10.1007/s10278-015-9848-7
M3 - Article
C2 - 26644156
AN - SCOPUS:84949501160
SN - 0897-1889
VL - 29
SP - 380
EP - 387
JO - Journal of Digital Imaging
JF - Journal of Digital Imaging
IS - 3
ER -