Introduction

CDISC defines a number of standards that support the capture and sharing of information related to research and clinical trials. FHIR is an HL7 standard for the capturing and sharing of healthcare information for a wide variety of purposes. This implementation guide, a joint effort of CDISC and HL7 defines mappings between FHIR release 4.0 and three specific CDISC standards:

• Study Data Tabulation Model Implementation Guide (SDTMIG) 3.2
• Clinical Data Acquisition Standards Harmonization Implementation Guide (CDASH) 2.1
• LAB 1.0.1

By making it easier to convert data between HL7 FHIR (commonly used in clinical systems to collect and share healthcare data) and CDISC standards (commonly used to submit clinical trial data for analysis and regulatory approval), both organizations aim to reduce the barriers to using clinical information to support research. Possible uses include:

• Capturing 'real world evidence' (RWE) where clinical data not directly captured for clinical trial purposes can be used to support regulatory applications.
• Allowing trial-driven data capture to occur directly inside clinical systems rather than separate clinical trial management solutions, leveraging technologies like SMART on FHIR. This is sometimes referred to as e-sourced data.
• Making it easier to leverage clinical data in retrospective studies.
• Supporting the creation of case report forms (CRFs) that link to data elements defined using FHIR resources and profiles.
• Enabling experts from both standards communities to understand each others terms and better align both sets of specifications as they continue to evolve.

As indicated by the use-cases, this guide will principally be used to support conversion of FHIR data into CDISC standards. The focus is on identifying which FHIR locations are most likely to have data needed to populate the in-scope CDISC specifications. However, the mapping information provided could also be used to generate FHIR instances from existing collections of CDISC data if there was a desire to do that.

Content

This implementation guide is purely a 'descriptive' guide. It does not (currently) define any FHIR profiles, value sets or other artifacts. Instead, it provides mapping tables that show the mappings between elements in portions of selected CDISC specifications map to FHIR. This content is organized as follows:

• Mapping Overview: Provides an explanation of the approach to the mappings, a description of how the mapping tables are organized, and other information relevant to reading and interpreting this specification.
• Mapping Caveats & Considerations: Additional background on aspects of CDISC standards that provide additional challenges when mapping from FHIR and guidance on how to address those challenges.
• Mapping domains: Separate pages that describe the mappings for different areas of clinical research information
  • Adverse Events
  • Concomitant Medications
  • Demographics
  • Laboratory
  • Medical History
  • Procedures
  • Vital Signs
• Downloads: Provides links to download this IG as well as to download the mappings as a custom transformable XML structure or as a single CSV or Excel file.

Credits

The following individuals were instrumental in the development of this implementation guide:

IG Authors

• Lloyd McKenzie (Gevity Consulting)
• Theresia Edgar (Gevity Consulting)

CDISC

• Mike Hamidi (CDISC)
• Rebecca Baker (CDISC)
• Rhonda Facile (CDISC)

HL7 Biomedical Research & Regulation work group

(Only co-chairs listed)

• Boris Brodsky (U.S. FDA)
• Hugh Glover (Blue Wave Informatics)
• Smita Hastak (Samvit Solutions)
• Andy Iverson (Medtronic)

Additional Acknowledgments

• Christine Denney (Eli Lilly and Co.)
• Jeff Abolafia (Pinnacle 21)
• Transcelerate eSource and E2C teams
• All those who participated in the initial review and feedback through CDISC and/or HL7's review processes

Various individuals from governmental regulatory agencies were involved in mapping discussions and in review of this document prior to publication. Their participation in no way represents policy with respect to expectations around the submission or conversion expectations for real world data or other potential uses of these mappings.