Literature DB >> 19027682

Automating radiologist workflow, part 3: education and training.

Bruce Reiner1.   

Abstract

The current model for radiologist education consists largely of mentorship during residency, followed by peer-to-peer training thereafter. The traditional focus of this radiologist education has historically been restricted to anatomy, pathology, and imaging modality. This "human" mentoring model becomes a limiting factor in the current practice environment because of rapid and dramatic changes in imaging and information technologies, along with the increased time demands placed on practicing radiologists. One novel way to address these burgeoning education and training challenges is to leverage technology, with the creation of user-specific and context-specific automated workflow templates. These automated templates would provide a low-stress, time-efficient, and easy-to-use equivalent of "computerized" mentoring. A radiologist could identify the workflow template of interest on the basis of the specific computer application, pathology, anatomy, or modality of interest. While the corresponding workflow template is activated, the radiologist "student" could effectively start and stop at areas of interest and use the functionality of an electronic wizard to identify additional educational resource of interest. An additional training feature of the technology is the ability to review "proven" cases for the purposes of establishing competence and credentialing.

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Year:  2008        PMID: 19027682     DOI: 10.1016/j.jacr.2008.05.013

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  2 in total

1.  Application of innovation economics to medical imaging and information systems technologies.

Authors:  Bruce I Reiner; Matthew McKinley
Journal:  J Digit Imaging       Date:  2012-06       Impact factor: 4.056

2.  Workflow Lexicons in Healthcare: Validation of the SWIM Lexicon.

Authors:  Chris Meenan; Bradley Erickson; Nancy Knight; Jewel Fossett; Elizabeth Olsen; Prerna Mohod; Joseph Chen; Steve G Langer
Journal:  J Digit Imaging       Date:  2017-06       Impact factor: 4.056

  2 in total

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