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Final ID: Poster #: EDU-137

Comprehensive Content and Learning Management System: Focused Multifaceted Learning for Pediatric Radiology

Purpose or Case Report: Learning at point of care has become the norm. There is endless unfiltered radiology educational material available on the internet. Radiology trainees and educators need a filtered high quality engine available at point of care to enable efficient and effective learning and teaching.

Methods & Materials: This presentation will include a complete pictorial display of all of the facets of a content and learning management system complete with detailed annotation and illustration to explain the role for each component.
Results: This learning resource is built on a Microsoft platform connected to a SQL-server based learning management system. Components of the program include: links to an array of established and vetted online resources, library complete with e-texts and atlases, teaching files, recorded lectures, video-based skills tutorials, fellows' and residents' orientation materials, subspecialty "corners" (fetal, MSK etc), reference articles, required reading, imaging protocols, case of the day, educator's toolkit, virtual rounding platform for ICU, and administrative corner. An internal search engine allows easy access within the firewall to the university library and improves search efficiency in removing the reliance on unfiltered searches through the usual browsers.
Conclusions: This electronic Education platform provides efficient and effective access to high quality learning and teaching resources at point of care for trainees and radiologists in pediatric radiology.
  • Reid, Janet  ( Children's Hospital of Philadelphia , Philadelphia , Pennsylvania , United States )
  • Gandhi, Trupti  ( Children's Hospital of Philadelphia , Philadelphia , Pennsylvania , United States )
  • Kazmi, Parvez  ( Children's Hospital of Philadelphia , Philadelphia , Pennsylvania , United States )
  • Anupindi, Sudha  ( Children's Hospital of Philadelphia , Philadelphia , Pennsylvania , United States )
  • Francavilla, Michael  ( Children's Hospital of Philadelphia , Philadelphia , Pennsylvania , United States )
  • States, Lisa  ( Children's Hospital of Philadelphia , Philadelphia , Pennsylvania , United States )
Session Info:

Electronic Exhibits - Educational

Informatics, Education, QI, or Healthcare Policy

Scientific Exhibits - Educational

More abstracts on this topic:
Machine and Deep Learning Models for Identification and Classification of Pediatric Brain Tumors

Randhawa Hari, Park Brandon, Khanna Praneet, Jung Daniel, Das Ayushman, Ginn Kevin, Mitchell Grace

Pitfalls and Biases in Artificial Intelligence for Pediatric Radiology Models

Rafful Patricia, Khalkhali Vahid, Alkhulaifat Dana, Welsh Michael, Wieczkowski Sydney, Sotardi Susan

More abstracts from these authors:
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