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Date: November 20th, 2020

Time: 12pm ET

Attendees (62)

Non-MITRE (47) 

First NameLast NameOrganization
StevenPiantadosiAlliance
CassandraO'ConnellAlliance Data Innovation Lab
keriReardonAlliance foundation
LelaDurakovicASCO
YvetteApuraASCO
SachaArnoldASCO CancerLinQ
VenuPerlaASCO TAPUR
RobinetteRennerBe The Match
TarunKumarCancer Insights
AnilNairCancerLinQ
RobertMillerCancerLinQ, American Society of Clinical Oncology
WendyBlumenthalCDC
SusanStilesCerner
BrianGardnerCerner Corporation
SorenaNadafCity Of Hope / Ci4CC
GUILHERMESAKAJIRIComsentimento
MattRiceDana-Farber Cancer Institute
John Methot (he/him)
Dana-Farber Cancer Institute
JakeRichardsDepartment of Health
LauraEldonFlatiron Health
DonellaBatemanFoundation Medicine
IanMaurerGenomOncology
MarieSugaKaiser Permanente
RogerMuellerMayo Clinic
DavidSchlossmanMedInfoDoc LLC
RobinPizziMEDITECH
OlegPenzinMiraMedix, LLC
MichaelBlakeNational Comprehensive Cancer Network
SusanDarlowNational Comprehensive Cancer Network
EvelynHandelNCCN
MarianBirkelandNCCN
PiyumindriFernandoPalantir
JoannaCohenPalantir
KimBallPOCP
BenSmithPrincipia Health Sciences
AnantBoroleQOMPLX
KaushalParekhRoche Diagnostics Information Solutions
BrettJohnsonstoneface ventures
RobertStillmanThe Ohio State University, Comprehensive Cancer Center
MelanieHullingsUT Southwestern
ShaalanBegUT Southwestern Medical Center
SimeonHearringVUMC
NikolaCihoricWemedoo
XXX-XXX-3786

XXX-XXX-4177

XXX-XXX-9757

MITRE (14) 

First NameLast NameOrganization
AndreQuinaMITRE
AnthonyDiDonatoMITRE
CarolinePotteigerMITRE
GregoryShemancikMITRE
JennHolmesMITRE
MaxMasnickMITRE
MayTerryMITRE
MichelleCasagniMITRE
MirandaChanMITRE
NicoleNgMITRE
ROBERTDINGWELLMITRE
SharonSebastianMITRE
SteveBrattMITRE
ZeshanRajputMITRE
JamesO'ConnorMITRE
MickO'HanlonMITRE

Action items

Planned Agenda Topics

Community Welcome – Anthony DiDonato (CodeX)

CodeX Use Case Updates – Steve Bratt (CodeX)

mCODE Knowledge Base and Educational Materials - Caroline Potteiger (MITRE)

CIBMTR Contributions and Future Work on the CodeX Registry Reporting Use Case - Robinette Renner (CIBMTR)

Community Discussion


Meeting Minutes

Anthony DiDonato, mCODE CodeX Community Lead, kicked off the meeting with an overview of the CoP, mCODE, CodeX and with announcements.

Steve Bratt, the HL7 FHIR CodeX Project Lead, welcomed attendees and provided an update on CodeX, in particular its use cases.

  • ICAREdata participation/clinical trials involvement continues to grow.
  • Integrated Trial Matching has gained an official HL7 sponsor, and Phase 0 work has officially been documented (available to community)
  • Registry Reporting is now active and continues to grow/establish itself
  • Radiation Therapy is gaining interest, scoping work still in progress
  • Pathways and Prior Authorization, we continue to work with sister FHIR Accelerator Da Vinci on cancer specific work  


mCODE Knowledge Base and Educational Materials  – Caroline Potteiger (MITRE):

  • Can be found on confluence page under mCODE
    • Includes brief review of mCODE standard
      • Deeper level of detail including mCODE organized by category (outcomes, labs, genomics, etc)
      • Further detail on data dictionary and profiles
    • Includes mCODE detail that will be easier to digest than mCODE Implementation Guide for this that want higher level 
  • Profile Tours - pages specific to each mCODE profile
    • Provides greater detail for each profile 
    • For example - Cancer Patient Profile
      • Info on base FHIR resource, description, constraints, etc
      • Other Notes of Interest section as well
        • Can be seen as "fun facts" of why this profile is specified as it is
  • mCODE Generic Playbook
    • Target audience - technical staff at health system
    • Split into 2 sections
      • Elements that do not impact clinical workflow
      • Elements that may impact clinical workflow
        • Further organized by data element domain (patient, genomic, etc.)
  • mCODE and Research Standards
    • Background on a couple of research standards, and how compares to mCODE
      • BRIDG, OMOP, CDASH
        • Overview, uses, implementation detail, etc. 
  • Knowledge Base - mCODE
    • Search feature for questions
    • Useful links available/quick links
      • HL7 detail, mCODE detail, etc. 
    • Browse by topic of interest
    • Links to Jira for community involvement there 
      • Comments and solutions also available here
    • Qs and How Tos
      • Think of as FAQs from the community, good starting place if you have a question
      • Can submit a new question if not covered - email address listed
        • If you click on linked Qs, goes into greater detail
          • Great mCODE and troubleshooting descriptions with screenshots
  • For other outreach
    • Chat.FHIR.org
  • Slide deck available on mCODE STU2 Potential Changes
    • Summary and greater detail throughout
    • Changes not set in stone but wanted the community to understand current thinking 


CIBMTR Contributions and Future Work on the CodeX Registry Reporting Use Case – Robinette Renner (CIBMTR):

  • Covering background, preliminary work, and next steps in use case
  • CIBMTR
    • Research collaboration between Medical College of Wisconsin and National Marrow Donor Program/Be the Match
    • Collects outcomes data form all US hematopoietic cell transplants
    • Maintains registry of over 550,000 patients since 1970
      • Focus on CAR-T treatment 
  • Within Registry Reporting use case
    • Collaborating with the CDC
    • Collaborating with state cancer registries
      • Some differences between CIBMTR and state registry data collections
        • Focus of CIBMTR
          • treatment data
          • data standard is caDSR
          • data sources international and domestic
        • Share the same pain-points of burden and time to report patient information
    • Use case work
      • Organized around two arms of work
        • Terminology 
        • Technical Architecture
  • Preliminary work
    • Stared with key data elements between mCODE, CIBMTR, and State Registries
      • Started with shared demographic data
    • CIBMTR has published a reporting app in Epic App Orchard
      • Allows for electronic submitting of select set of data
    • Also developed synthetic data that is CAR-T specific for use case
  • Collaborators - onboarded and prospective
    • MITRE, CIBMTR, CDC, UCSF, CA State Registry, Stanford
  • Successes and Challenges
    • Strong interest from the beginning
    • Both CIBMTR and CDC already use data standards
    • Existing technical frameworks that can be leveraged
      • CIBMTR SMART-on-FHIR app in Epic App Orchard
      • CDC's MedMorph reference architecture 
    • Challenges include data element agreement across systems, but no surprise there
  • Scope of effort
    • Currently focusing on California for proof of concept, but will grow into other states
  • Cadence established
    • Kickoff already occurred, now holding regular workgroup calls
  • Multi-Phased approach to work
    • Phase 0 proof of concept
    • Phase 1 full mCODE + extensions
    • Phase 2 standardize and scale
      • Reference slides for full detail 


Q&A

Q: What is the ideal end stage for reporting to CIBMTR in the future

A: Moving the data using the standards through the tool that we develop


Q: If you can move the data in a standardized way, like using mCODE, would you rethink the current question and answer approach

A: Forms based approach was initially effective when using paper, but doesn't translate well to electronic data capture - will be moving to domain based approach, though over time


Q: Transition period for CIBMTR, in moving to domain based approach - could you elaborate?

A: With the CIBMTR reporting app can only collect small subset of data, so working with initial sites who are willing to be patient in testing and leading to fully developed solution. We anticipate the need for a web based manual entry approach for unstructured data, smaller sites without good systems or international sites for example. 


Q: Were you (CIBMTR) able to use FHIR backend authentication to get data from UCSF?

A: Can get back to you on that as that's a very technical questions - UCSF is not currently using our app and moving the data


Q: Rationale for using synthetic data?

A: Mitigates run-up time to onboarding health systems and enabling their data, also allows for us to demo our solutions without constraints


Q: Are you going to scale registry reporting to other states besides California?

A: We are starting by leveraging partner site engagement in the CIBMTR network, but yes planning to scale into additional states up to national level

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