Utility of an Automated Radiology-Pathology Feedback Tool.
Purpose: To determine the utility of an automated radiology-pathology feedback tool.Methods: We previously developed a tool that automatically provides radiologists with pathology results related to imaging examinations they interpreted. The tool also allows radiologists to mark the results as conco...
| Publicado en: | Journal of the American College of Radiology Vol. 16; no. 9; pp. 1211 - 1218 |
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| Autores principales: | , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Sep2019:Part A
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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=138228716&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 138228716 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15461440 EAO jtl: Journal of the American College of Radiology issn: 15461440 maglogo: N pubinfo: dt: Sep2019:Part A vid: 16 iid: 9 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 138228716 138228716 NLM31072775 138228716 10.1016/j.jacr.2019.03.001 NLM31072775 138228716 ppf: 1211 ppct: 7 formats: tig: atl: Utility of an Automated Radiology-Pathology Feedback Tool. aug: au: Doshi, Ankur M. Huang, Chenchan Melamud, Kira Shanbhogue, Krishna Slywotsky, Chrystia Taffel, Myles Moore, William Recht, Michael Kim, Danny affil: Department of Radiology, NYU Langone Medical Center, New York, New York sug: subj: Diagnostic Imaging Specialties, Medical Methods Pathology Methods Peer Group Prospective Studies Clinical Competence Human ab: Purpose: To determine the utility of an automated radiology-pathology feedback tool.Methods: We previously developed a tool that automatically provides radiologists with pathology results related to imaging examinations they interpreted. The tool also allows radiologists to mark the results as concordant or discordant. Five abdominal radiologists prospectively scored their own discordant results related to their previously interpreted abdominal ultrasound, CT, and MR interpretations between August 2017 and June 2018. Radiologists recorded whether they would have followed up on the case if there was no automated alert, reason for the discordance, whether the result required further action, prompted imaging rereview, influenced future interpretations, enhanced teaching files, or inspired a research idea.Results: There were 234 total discordances (range 30-66 per radiologist), and 70.5% (165 of 234) of discordances would not have been manually followed up in the absence of the automated tool. Reasons for discordances included missed findings (10.7%; 25 of 234), misinterpreted findings (29.1%; 68 of 234), possible biopsy sampling error (13.3%; 31 of 234), and limitations of imaging techniques (32.1%; 75/234). In addition, 4.7% (11 of 234) required further radiologist action, including report addenda or discussion with referrer or pathologist, and 93.2% (218 of 234) prompted radiologists to rereview the images. Radiologists reported that they learned from 88% (206 of 234) of discordances, 38.6% (90 of 233) of discordances probably or definitely influenced future interpretations, 55.6% (130 of 234) of discordances prompted the radiologist to add the case to his or her teaching files, and 13.7% (32 of 233) inspired a research idea.Conclusion: Automated pathology feedback provides a valuable opportunity for radiologists across experience levels to learn, increase their skill, and improve patient care. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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