Short Description

The track will focus on extracting patient medication data from an EHR FHIR server and generating an SDTM dataset to submit to FDA's submission Gateway for validation. This is an evolution from the January track and new steps will cover the assessment of the confidence in the quality of the data and addition of a FHIR based algorithmic approach to consolidation of medication data for a patient. 

Long Description

Clinical Research studies currently require the redundant entry of clinical data that already typically reside in certified EHR/health IT systems.  It would be substantially better to utilize EHR source data to directly populate clinical research data capture systems wherever feasible. At this time, the data standard used for submission of tabulated clinical study data for pharmaceutical and biologicals to the FDA is SDTM (Study Data Tabulation Model), created by the Clinical Data Interchange Standards Consortium (CDISC) standards development organization, which is optimized for clinical research and regulatory uses. 

This track is the second in a series evolving an approach to collect concomitant medication data for a patient from one or more EHR systems and to aggregate this into a summary record that meets regulatory standards for accuracy and trustworthiness and which can then be converted into a format for submission.  

The January 2021 considered a series of fictional patients, and retrieved retrieve medications relevant dates from the following resources: MedicationStatment;  MedicationRequest.   

  • For May we will scan all the possible resource locations of medication information provided by FHIR (regardless of which resources a particular EHR is using) and we will use actual EHR data rather than fictional data. 
  • Algorithmically navigate the available medication information (including the resources present in the EHR and the data recorded within them) to determine a consolidated list for each patient
  • In the exported consolidated list, provide information inferring a level of confidence the patient ingested the drug:
    • for example, only a medication statement list shows the patient takes an antihypertensive drug, but a full set of records all the way to administration is shown for an IV antibiotic.
    • This is useful to a researcher to be able to assign different levels of confidence to one drug. For example: Prescription only: was it even filled? when was it taken last? Does that affect my study and is there a way to address this?  Record includes Administration: suggests confirmation the drug was given as recorded.


Test the design of a set of resources

Submitting Work Group/Project/Accelerator/Affiliate/Implementer Group  

Vulcan Accelerator

Track Lead(s)

Scott Gordon, Lauren McCabe

Track Lead Email(s)

Related Tracks

FHIR Version


Specification(s) this track uses

A draft IG

Artifacts of focus

Expected participants

Vulcan members, Regulators, EHR Vendors, EDC Vendors, Academic Medical Centers, Pharma Companies.  We averaged 10-15 participants in January - should be similar.

We particularly invite EHR vendors to provide test systems to work with and Developers to address the medication record consolidation part of the system.

Zulip stream


Track Details

System Roles:

  • FHIR EHR Server - An EHR server pre-populated with synthetic or fully anonymized records. The connectathon will not make any changes to the data on this server.
  • Consolidation engine
  • FHIR-to-SDTM Mapping Capability - This capability will be developed for the connectathon. It will convert medication-related FHIR resources for a given patient to CDISC SDTM Concomitant Medication dataset, i.e. CM domain dataset. This capability will also convert the Patient FHIR resource for the same patient to CDISC SDTM Demographics dataset, i.e. DM domain dataset. For the purposes of the January connectathon other necessary CDISC SDTM domain datasets, e.g. TS/ TE/ TA, will be created manually, especially since the EHR Server is less likely to contain clinical trials related data.
  • FDA Submission Gateway - The FDA Gateway will receive the CDISC SDTM datasets and validates it. Note: The Gateway uses Pinnacle 21 to validate CDISC SDTM datasets. 


The May connectathon will focus on the following scenario: 

  1. Search for a patient in the EHR FHIR server by a patient identifier
  2. Retrieve patient’s medication records for a given period
  3. Display medication records on the UI
  4. Indicate the confidence level associated with each record
  5. Consolidate the records into a summary record
  6. Show the FHIR XML/JSON representation of the medication records and summary record
  7. Convert the FHIR summary data CDISC SDTM datasets, CM and DM domains
  8. Validate the created SDTM datasets via the FDA Gateway

The figure below depicts the data flow.


Test Script(s):

The wireframe below shows the January reference implementation.  For May it will be similar but incorporate extra functionality.

  1. The user enters a patient number in block A and clicks [Search]
  2. The system will retrieve the patient from the FHIR EHR server and display basic patient demographics information in block B, and the patient’s medications record in block C.
  3. The user can click [Display Results (XML/JSON)] to display the XML or JSON FHIR representation of the medications record
  4. The user can click [Export SDTM Dataset] and the system creates the DM (Demographics) and CM (Concomitant Medication) CDISC SDTM domain files to store on the user’s local machine.

Note: Other CDISC SDTM files necessary for the submission will be manually created, i.e. TS (Trial Summary), TE (Trial Elements), TA (Trial Arms), and define.xml. Since the server will have EHR clinical data, and no clinical trial data, the clinical trial related variable values used in these SDTM domain files will be synthetic and constant for any patient used in the prototype.

Security and Privacy Considerations:

The data used for this connectathon will be synthetic or fully anonymised.  There may be security requirements for access tot the FDA gateway for testing.