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Project Overview


  • Digital oncology measure development/authoring has been constrained by an ecosystem of disparate and unstructured data, as well as a lack of digitalized collections and oncology models to support interoperability.
  • Consequently, the majority of oncology quality measures data collection has required manual abstraction resulting in significant burden, and an overall lack of opportunity to share this unstandardized information across systems or organizations.
  • Notably, this has also resulted in the authoring and availability of digitalized clinical quality measures for oncology lagging behind other clinical domains.


Target Outcome: 

  • Create a solution that demonstrates the ability to author and evaluate digital measures using FHIR data model with mCODE profile extensions and data elements for value-based programs and clinical quality improvement in the Oncology domain.
  • This use case will focus on the beginning of a measure’s life cycle and start with quality measure authoring.
  • Initial project scope will focus efforts to:
    • Author and develop a process for setting up necessary data elements in discrete data fields, to be used for data collection and aggregation. 
    • Prove that measures can be authored and executed using mCODE, and FHIR, and the correct measure result can be obtained
  • This use case will start with the authoring and development of test case bundles using a single measure initially for phase 0


  • The clinical oncology subject matter expertise of the CodeX community, paired with the mCODE profiles and FHIR IGs, should allow for the authoring of these quality metrics and provide a proof of concept for measure developers
    • Specifically, there is significant value in demonstrating that quality measure authoring of oncology measures will be easier and more feasible using a FHIR- (and mCODE)-based solution.
  • With the expansion of programs focusing on collection of meaningful oncology quality measure data, such as the VA initiatives, the Advancing Cancer Care MVP (MIPS), in support of the Federal Cancer Moonshot Initiative, and the Enhancing Oncology Model (EOM), this CodeX use case team wishes to provide solutions using HL7 FHIR and mCODE to provide a path to data collection with reduced burden. 

Project Plan 
rttd public project plan
rttd public project plan




DiscoveryUse case identification 

Complete = in 2 months?


Plan out high level project plan, deliverables, success measures, high level timeline, key stakeholders, etc

Complete = in 6 months?

Phase 0

Test the Telligen Quality Measures Engine (QME) Tooling, as a proof of concept, to determine if QME is successful in authoring and evaluating:

  1. the digitally available 2022 MIPS Measure #143: Oncology: Oncology: Medical and Radiation – Pain Intensity Quantified
  2. ASCO proposed eCQM #1: Antiemetic Therapy for Low and Minimal Emetic Risk Antineoplastic Agents in the Infusion Center
  3. ASCO proposed eCQM #2: Antiemetic Therapy for High and Moderate Emetic Risk Antieneoplastic Agents in the Infusion Center


  • Map MIPS measure to mCODE
  • Create FHIR transaction test case bundles and load to FHIR Clinical Data Repository (CDR)
  • Author Measure and supporting libraries (translate and create FHIR measure resources)
  • Stratifying denominator by SDOH characteristics
  • Execute measure and measure report with QME tool

Complete = in 6-8 months?

Phase 1 

Expand portfolio of VA quality measures and repeat measure mapping, authoring, test bundle creation and testing steps

Current Measures include:

  1. ASTRO measure: Oncology: Treatment Summary Communication - Radiation Oncology
    1. This is the ASTRO eCQM treatment summary measure – linked here
  2. VA measure: Performance Status
    1. This is one of the VA measures - linked here


Phase 2

Expand portfolio by aligning to oncology quality measures in federal models and among oncology steward programs

  • Proposed measure(s) for the Advancing Cancer Care MVP (MIPS) and Enhanced Oncology Model (once measures are identified)
    • Prepare to incorporate this subset into the QME through mapping to mCODE, authoring and support libraries and execution of measures using QME tool for testing

In addition to aligning to federal models, longer-term VA measures include:

  1. 28 Days from Diagnosis to Any Treatment (#All-B-1) ASPIRATIONAL
    1. This will require modeling “systemic therapy” as a FHIR concept
  2. 14 Days from Simulation to First Radiation Treatment
    1. This will require modeling of “simulation” as a FHIR concept (RT-specific)


Phase 3

Source real world Clinical Data Repository endpoints for measure data source



Quick Links

Please refer to Quality Measures - Proposal for additional use case details

mCODE Implementation Guide (STU 2)

Measures Status

Conference Call Information

Public Call Meeting Details – TBA (date, time, Zoom link, password, etc.)

Use Case Team

RoleName Organization
CodeX-specific role?

Stephanie Jones

American Society of Clinical Oncology

Yvette Apura

American Society of Clinical Oncology

Caitlin Drumheller

American Society of Clinical Oncology

Karen Hagerty

American Society of Clinical Oncology

Randi KudnerAmerican Society for Radiation Oncology

Sam DawesAmerican Society for Radiation Oncology

Anne HubbardAmerican Society for Radiation Oncology

Rick EmeryCigna/Evernorth

Dr. Vik ShahCigna/Evernorth

Dr. Mary Kay BartonCigna/Evernorth

Sondra BergerCigna/Evernorth

Dennis BlairCigna/Evernorth
Use Case CoordinatorAnthony DiDonatoMITRE
Use Case Assistant CoordinatorBrittany NguyenMITRE

Becky MetzgerTelligen

Gail WintersTelligen

Sharon LabbateTelligen

If you'd like to learn more about this use case, please contact Anthony DiDonato - 

Current Collaborators

  • American Society of Clinical Oncology
  • American Society for Radiation Oncology
  • Cigna/Evernorth
  • Telligen