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  1. Project Scope Statements/Proposals
  2. PSS-1981

Bidirectional OMOP phenotype and FHIR CQL Data Requests

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    • Icon: Project Scope Statement Project Scope Statement
    • Resolution: Unresolved
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      1) Research organizations and communities establish well-defined cohorts, yet require significant curation to capture and analyze data; researchers also validate their datasets and address reliability and feasibility issues with respect to the data requested and retrieved. The ability to convert phenotype definitions and retrieve data directly from information captured as part of the care delivery process will significantly reduce the effort and time required to curate the data.
      2) Collaborating with research phenotype definitions provides validated and reliable data to evaluate clinical outcomes with respect to effectiveness, timeliness, efficiency, and safety.
      3) Identification of process data requirements to evaluate quality care delivery and clinical decision support may inform potential updates to the OMOP data model.
      4) Potential domains for using queries developed in FHIR CQL for OMOP, or OMOP Atlas to FHIR CQL include research, clinical / financial registries, quality improvement, public health surveillance, and other potential domains.

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      1) Research organizations and communities establish well-defined cohorts, yet require significant curation to capture and analyze data; researchers also validate their datasets and address reliability and feasibility issues with respect to the data requested and retrieved. The ability to convert phenotype definitions and retrieve data directly from information captured as part of the care delivery process will significantly reduce the effort and time required to curate the data. 2) Collaborating with research phenotype definitions provides validated and reliable data to evaluate clinical outcomes with respect to effectiveness, timeliness, efficiency, and safety. 3) Identification of process data requirements to evaluate quality care delivery and clinical decision support may inform potential updates to the OMOP data model. 4) Potential domains for using queries developed in FHIR CQL for OMOP, or OMOP Atlas to FHIR CQL include research, clinical / financial registries, quality improvement, public health surveillance, and other potential domains.
    • Clinical Quality Information
    • Biomedical Research & Regulation
      Clinical Decision Support
    • Clinical Interoperability Council; Vocabulary; Learning Health Systems
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      Johns Hopkins University
      Possible: Georgia Tech, NCATS, CDMHC
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      Johns Hopkins University Possible: Georgia Tech, NCATS, CDMHC
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      Multiple stakeholders require the ability to query and retrieve real world clinical and financial data to meet specific use cases that include specifically defined cohorts (or phenotypes) for research, quality improvement activities, public health surveillance, professional society registries for credentialing, and population research. Most of the use cases require considerable time and effort to develop cohort definitions which include aspects of terminology and varying context and metadata complexity (e.g., event timing, age characteristics). Each stakeholder group establishes its own method for evaluating cohort definition validity and reliability and all require data curation by one or more of the requesting entity, the responding entity, or an intermediary. Such data curation is highly time and resource intensive. Establishing a methodology for developing and validating such queries and requesting data retrieval based on standard a interoperability model (FHIR) used by entities capturing data for sharing should significantly reduce the curation effort and expense. Moreover, various stakeholders will gain significant value by the ability to share cohort (phenotype) definitions with a consistent method for validity and reliability determination.
      Show
      Multiple stakeholders require the ability to query and retrieve real world clinical and financial data to meet specific use cases that include specifically defined cohorts (or phenotypes) for research, quality improvement activities, public health surveillance, professional society registries for credentialing, and population research. Most of the use cases require considerable time and effort to develop cohort definitions which include aspects of terminology and varying context and metadata complexity (e.g., event timing, age characteristics). Each stakeholder group establishes its own method for evaluating cohort definition validity and reliability and all require data curation by one or more of the requesting entity, the responding entity, or an intermediary. Such data curation is highly time and resource intensive. Establishing a methodology for developing and validating such queries and requesting data retrieval based on standard a interoperability model (FHIR) used by entities capturing data for sharing should significantly reduce the curation effort and expense. Moreover, various stakeholders will gain significant value by the ability to share cohort (phenotype) definitions with a consistent method for validity and reliability determination.
    • Product Family Product Project Intent Lineage Ballot Type Target Cycle Actions
      		1
      FHIR
      Implementation Guide
      Create New R1 Standard
       
      Informative/STU to Normative
      January 2023
    • FHIR - OMOP model mapping
    • No
    • Yes
    • Academic/Research, Association/Goverment Agency, Healthcare Provider/user, Other, Payer/Third Party Administrator, Pharmaceutical/Biotech, Providers, Regulatory Agency, Vendor/Manufacturer
    • Universal

    Description

      This project will create guidance for bidirectional flow of queries and responses written in OMOP with Atlas expressions to FHIR with CQL and FHIR CQL expressions to OMOP Atlas expressions. The initial activity will use Digital Quality Measure (dQM) as an example. The goal is to establish common mechanisms for developing and sharing population cohorts across research, registry, quality improvement (measurement and clinical decision support), public health surveillance, and related stakeholder groups. The research community develops, validates, and assures reliability and feasibility of cohort definitions, yet retrieving data to match that definition requires significant, time consuming, curation. For the example, a hypothetical dQM cohort measure will be used as the content (such measure consistent with a COVID19 research cohort). Enabling translation of the dQM cohort measure from OMOP and Atlas to FHIR-CQL will allow queries for existing data based on standard FHIR and related profile definitions such that curation efforts should become less cumbersome. Similarly, the quality and registry communities have challenges assuring reliability and validity of cohort definitions developed independently and such definitions may require duplicate effort for implementers for cohorts defined separately by researchers, registries, and quality improvement stakeholders. The goal is to enable harmonization, providing a common source and reliable, valid, cohort definition for all three communities to query for required data in a common mechanism that will simultaneously reduce clinical care implementer burden for extracting useful data.

      See attached overview diagrams:

      1. Bidirectional OMOP Phenotype and FHIR-CQL Data Request Overview Diagram
      2. Bidirectional OMOP Phenotype and FHIR-CQL Data Request Value Metrics

      The project overall scope has Universal Domain components such as mapping from FHIR International Patient Summary to OMOP as well as some US Realm components mapping from US FHIR Core to OMOP.

      The comprehensive set of activities and requirements include the following, with annotated examples from a cohort measure to identify COVID-19 patients (cohort 1) and matched controls (cohort 2):
      Terminology Infrastructure:

      • Plan to test in May 2022 HL7 FHIR Connectathon
        • Requirement - phenotype definition and value sets - VSAC value sets and FHIR API
        • Programmatic methodology for extracting VSAC value sets and mapping terms to OMOP terminology (current manual upload)
        • Recommendations for handling concepts missing from OMOP (such as healthcare service locations - HSLOC and CDC Race and Ethnicity Codes)
        • Subscription or periodic requery when VSAC updates the terminology

      Expression Infrastructure:

      • Plan to evaluate for May 2022 HL7 FHIR Connectathon, perhaps move to July 2022 NCQA/HL7 Digital Quality Summit
        • Requirement - OMOP-Atlas instance, FHIR-CQL instance
        • Atlas - SQL capability exists - need Atlas SQL instance for pilot testing
        • FHIR - CQL capability exists - need FHIR CQL instance for pilot testing
        • Expression conversion (what infrastructure is required here):
        • Atlas phenotype to FHIR cohort conversion
        • FHIR cohort expression with CQL to Atlas phenotype conversion

      Data Query and Response Infrastructure:

      • Plan to evaluate in September 2022 HL7 FHIR Connectathon or sooner if data available:
        • Atlas data store for synthetic patients
        • FHIR data store for synthetic patients
        • Query capability for Atlas patients and retrieve of OMOP cohort(s)
        • Query capability for FHIR patients and retrieve of FHIR synthetic cohort(s)
        • Structure to compare OMOP cohort with FHIR cohort, identify concordance and challenges

      Anticipate IG STU ballot for January 2023.
      Further analysis by participants will evaluate the feasibility of importing a FHIR retrieve dataset into OMOP or an OMOP dataset into FHIR especially with respect to (a) requirements for re-use of datasets and (b) potential loss of fidelity in such a transformation.
      Expectations for International Use - requesting site compliance with International Patient Summary respective version(s) and future, International Patient Access (IPA) version(s)
      Expectations for US Realm Use - requesting site compliance with US Core consistent with United States Clinical Data for Interoperability (USCDI) respective version(s)

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              Updated: