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Virtual

Feb 08, 2024 10:00 AM - Feb 08, 2024 2:00 PM

Short Course: Mapping Common Regulatory Data Standards to FHIR

This is a Virtual Pre-Conference Short Course in conjunction with the Regulatory Submissions, Information, and Document Management Forum

Overview

This Short Course will be offered virtuallyJoin from anywhere! *This Course requires an additional registration fee. You do not need to be registered for the Forum to attend*

*Please note: Short Courses are stand-alone events. Registration for the main conference, forum, etc. are not mandatory.

 

As our data exchange moves toward full digitization, HL7 Fast Healthcare Interoperability Resources (FHIR) is emerging as the standard by which the Life Sciences industry will communicate data electronically. In this course we will discuss, from a regulatory perspective, the similarities and differences among multiple data standards that are targeted for use in FHIR for data exchange, including:

  • Identification of Medicinal Products (IDMP)
  • Chemistry, Manufacturing & Controls (CMC)
  • Structured Product Labeling (SPL)
  • Electronic Medicinal Product Information (ePI)

 

Registered attendees for this virtual Short Course will receive access to the course recording for 2 full months post-course! This allows you to remain flexible with your schedule and not worry if you need to step out momentarily. Have a conflict with the dates of the course, but are interested in the content? Register anyway and you will receive access to the recording!

 

Receive $150 off your forum registration by registering for any combination of at least two short courses and/or primers as well as the main forum. Purchases must be made at the same time to receive the discount. Discounts will be reflected on the last page of the cart.

Learning objectives

At the conclusion of this session, participants should be able to:
  • Define the key components of various common data standards (IDMP, CMC, SPL and ePI) with regard to FHIR
  • Identify common data definitions across the standards
  • Identify data definitions that are misaligned to one or more standards
  • Recognize strategies to mitigate those misalignments

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