. Panel on December 17, 2024 3:50 - 4:20 PM ET - Riki to attend

Looking for talking points for answers for these 3 questions that will be discussed on the panel:

• Question 1: Please briefly refresh the audience regarding the vision, objectives, key participants, and scope of activities in your Collaborative Community, including highlights of recent and ongoing activities and upcoming milestones or events. [3-5 minutes]

  • website link: https://aphlinformatics.atlassian.net/wiki/spaces/SC

  • SHIELD stands for Systemic Harmonization and Interoperability Enhancement for Laboratory Data (SHIELD)

  • We have over 70 organizations representing federal agencies, in vitro diagnostics (IVD) organizations, standards development organizations , medical associations, and other professional laboratory organizations

  • SHIELD’s mission is to “Describe the SAME test the SAME way ANYWHERE in the Healthcare ecosystem”

  • We work on interoperability issues because it provides confidence for patients and doctors in laboratory results so that results from different labs can be compared and used for patient care including transition of care, clinical decision support and population trends; and other secondary uses such as regulatory decision making, public health surveillance and response as well as medical research.

  • Broken out in several Working Groups that tackle different parts of the SHIELD Roadmap:

    • Standardization and Vocabulary

      • alginment for specific lab test areas (e.g. how to best represent and report susceptibility testing (phenotypic and genotypic)

      • creation of common value sets for qualitative tests, susceptibility testing, specimen types etc.

    • Laboratory Interoperability Data Repository (LIDR)

      • creating a library of vendor specific lab test characteristics that also provides proper coding for all its data exchange elements (LOINC for the tests, SNOMED CT for coded result values, specimen information, methods), UCUM for units of quantitative result values).

    • Communication and Branding

      • creating our online presence

      • getting the word out at conferences and in articles

      • outreach to SHIELD membership

    • IVD Data Hub

      • creating a home for de-identified test specific results for secondary uses

        • post-market research

        • clinical research

        • public health

    • FDA BAA work with participation from SHIELD members:

      • Synensys Reports on FDA System Safety within Laboratory Data Exchanges including Over-the-Counter and Point-of-Care Testing

      • CAP developed proposed quality assurance program for coded representation of tests and results

      • The Deloitte team is developing a proof-of-concept for an open-source general-purpose authoring and healthcare knowledge management environment, called “Komet”, that can be used to improve the granularity, consistency, and overall quality of Real-World Data (RWD) generated by and about FDA-approved products

• Question 2: What have been the biggest challenges or barriers to achieving standardized methodology and data structures (interoperability) across variety of data-generating devices, lab tests, and organizations?

  • Limited resources allocated for this work:

    • by clinicians, HIT vendors, federal agencies results in limited time commitment for human resources and no available funding for pilot projects.

    • Shortages of laboratory professionals, lack of funding and expertise for building and mapping test terms, updating messaging with each type of reporting/exchange, etc. EHR and LIS functionality to support.

    • Standards development for new paradigms.

    • Education of providers on needs versus what they prefer (EHRs designed for their needs as primary user).

    • Lack of functionality for EHRs to consumer point of care testing results and values, and integrate into EHR and communicate to public health/other entities.

    • Consumer health product result tracking (like continuous glucose monitoring)

  • inconsistent definitions for clinical data can result in similar, but not identical data structures or vocabulary, which results in potential loss of information during transformation or, if the difference is not identified, mismatches altogether

  • lack of granularity in existing data element representation to convey the assay-to-assay variablity

• Question 3 [back-up, time-permitting]: How has your CC sought to balance the competing needs for both innovation & standardization?

  • Unsure if these two things actually interfere with each other, except maybe that getting true consensus across a large healthcare ecosystem takes time, while innovation often works in quicker sprints - trying to break down consensus building into smaller projects could mitigate some of that

  • We have been making data exchange easier to do, but have not done the standardization work to make the data understandable across organizations before the exchange was enabled, so we now have to work with existing exchanges and system functionalities

  • While some standards/areas of healthcare are further along, the focus has been on achievable standards adoption for laboratories to lift all up to same level. Discussion has occurred on innovatative aspects, but much development is needed to support their adoption. Lack of funding is an impact as above and resources from a volunteer Collaborative Community. Identification of gaps in standards allows development to occur

Notes from the panel:

Most of those communties are non-profits, so they have better support for in-person meetings, websites etc

Partner Collabotative Communitieswith whom we should consider connecting:

Digital Health Measurement (DATAcc): https://datacc.dimesociety.org/

Smart & Autonomous Medical Systems (SaAMS)

OpenOximetry

Future: