Development of an Automated Bone Mineral Density Software Application: Facilitation Radiologic Reporting and Improvement of Accuracy.
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 generati...
| Publicado en: | Journal of Digital Imaging Vol. 29; no. 3; pp. 380 - 388 |
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| Autores principales: | , , , |
| Formato: | diagnostic images research tables/charts Journal Article |
| Publicado: |
Springer Nature
Jun2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=115610160&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 115610160 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Jun2016 vid: 29 iid: 3 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 115610160 115610160 115610160 10.1007/s10278-015-9848-7 115610160 ppf: 380 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Development of an Automated Bone Mineral Density Software Application: Facilitation Radiologic Reporting and Improvement of Accuracy. aug: au: Tsai, I-Ta Tsai, Meng-Yuan Wu, Ming-Ting Chen, Clement affil: Department of Radiology, Kaohsiung Veterans General Hospital, Kaohsiung Taiwan sug: subj: Absorptiometry, Photon Bone Density Software Reports Human P-Value Human Error Automation 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. pubtype: Academic Journal doctype: diagnostic images research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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