FHIR Clincal Guidelines (v0.1.0) (STU1 Ballot)

This page is part of the Clinical Guidelines (v0.1.0: STU 1 Ballot 1) based on FHIR R4. The current version which supercedes this version is 1.0.0. For a full list of available versions, see the Directory of published versions

1.0.0FHIR Clinical Guidelines

This implementation is organized with the following sections, accessible via the menu bar at the top of every page:

  • Home: The home page provides summary and background information
  • Profiles: Index of all profiles
  • Artifacts: Index of all artifacts (e.g. activity and plan definitions)
  • Terminology: Index of all terminology (e.g. code systems and value sets)
  • Examples: Index of examples
  • Extensions: Index of extensions
  • Documentation: Index of specification documentation
    • Approach: Describes the overall approach taken to representing computable guideline content
    • Terminology: Describes expectations for terminology defined as part of computable guideline content
    • Profiles: Describes expectations for profiles defined as part of computable guideline content
    • Libraries: Describes expectations for the use of libraries as part of computable guideline content
    • Recommendations: Describes how recommendations are structured and distributed
    • Care Planning: Describes expectations for the use dynamic care planning with computable guideline content
  • Downloads: Downloads for the specification
  • Checklists: Checklists provided for moving guideline content from L1-L4
  • ​Version History: Index of all versions of this implementation guide

    • 1.1.0 Introduction

    This implementation guide supports the development of standards-based computable representations of the content of clinical care guidelines. Its content pertains to technical aspects of digital guidelines implementation and is intended to be usable across multiple use cases across clinical domains as well as in the International Realm.

    This implementation guide has been developed through a multi-stakeholder effort, holistically involving a range of stakeholders, including those who work at the beginning of the process (e.g., guideline developers) to the end users (e.g., clinical implementation team representatives, health IT developers, patients/patient advocates), and others in between (e.g., informaticists, communicators, evaluators, public health organizations, clinical quality measure and clinical decision support developers).

    The premise involves determining the representation of clinical practice guideline recommendations in FHIR as part of an iterative guideline development and implementation process (Figure 1.1). By including all the relevant perspectives (e.g., guideline authors, informaticists, implementers, communicators, evaluators) as part of the iterative process, the resulting computable representation of the recommendations should be well-vetted and more readily implemented.

    Guideline development cycle

    Figure 1.1

    1.2.0 Scope

    The implementation guide focuses on establishing patterns, profiles, conformance requirements, and guidance for the patient-independent representation, and analogous patterns for the patient-specific representation of guideline recommendations.

    1.3.0 Goals

    Direct:

    • Reduce duplicate development effort involved in the implementation of clinical practice guideline recommendations in clinical systems
    • Reduce unnecessary and/or unintentional variability in clinical practice guideline implementation

    Indirect:

    • Minimize the time needed to implement clinical practice guideline recommendations in clinical systems

    1.4.0 Audience

    Clinical informaticists, health system integrators and clinical systems developers. Assumes familiarity with relevant standards, including FHIR and Clinical Quality Language (CQL).

    1.5.0 Background

    The need for computable care guidelines can be considered in the context of the data lifecycle, where the representation of the guideline recommendations in FHIR helps deliver actionable knowledge (Figure 1.2).

    Delivering actionable knowledge

    Figure 1.2

    By translating the recommendations in clinical practice guidelines at the source, and disseminating a computable version along with the narrative version of the guidelines, the effort of translation would not be repeated across every organization that intends to apply the recommendations. Likewise, unnecessary or unintentional variations as a result of duplicative translation efforts could be prevented with a standard, computable version that is ready to be implemented. In removing the need for translating recommendations at each local clinical system, and removing as much variation as possible through a standard translation, the time needed to apply the recommendations in practice should also be reduced, helping scientific evidence reach patient care more easily, quickly, accurately, and consistently.

    In considering common patterns across multiple guidelines, this implementation guide can apply to a variety of use cases across multiple clinical domains, as is evidenced by the examples provided. These common patterns not only create a way to organize the content for the translation into computable recommendations but also help implementers operationalize the recommendations within clinical workflows.

    1.6.0 References

    1.7.0 Acknowledgements

    Author Name Affiliation Role
    J. Rex Astles, PhD, FAACC CDC, Health Scientist Contributor
    Wendy Blumenthal, MPH CDC, Health Scientist Contributor
    Matthew M. Burton, MD Apervita, Inc., VP Clinical Informatics Contributor
    Zahid Butt MD, FACG Medisolv Inc, CEO Contributor
    Dave Carlson, PhD Clinical Cloud Solutions, Solution Architect Contributor
    Daryl Chertcoff HLN Consulting, Solution Architect Contributor
    Jeffrey Danford, MS Allscripts, Sr Principal Software Engineer Contributor
    Floyd Eisenberg, MD, MPH iParsimony Contributor, Co-Chair (Clinical Quality Information)
    Margaret S. Filios, MSc, BSN, RN, CAPT USPHS CDC, Senior Scientist Contributor
    Daniel Futerman Jembi Health Systems, Senior Program Manager Contributor
    Joel C. Harder, MBA AiCPG, Executive Director Contributor
    Aaron M. Harris, MD, MPH, FACP CDC, Subject Matter Expert Contributor
    Dwayne Hoelscher, DNP, RN-BC, CPHIMS Nursing Informaticist Contributor
    Emma Jones RN-BC, MSN Allscripts, Expert Business Analyst Contributor, Co-Chair (Patient Care), IHE Co-Chair (Patient Care Coordination)
    James Kariuki CDC, Health Scientist Contributor
    Kensaku Kawamoto, MD, PhD, MHS Contributor, Co-Chair (Clinical Decision Support)
    Robert Lario, MSE, MBA University of Utah/US Department of Veterans Affairs, Health Standards Architect Contributor
    Ira M. Lubin, PhD CDC, Health Scientist Contributor
    Laura Haak Marcial RTI International, Health Informaticist Contributor
    Robert McClure, MD, MPH Contributor, Co-Chair (Vocabulary)
    Maria Michaels CDC Contributor
    Blackford Middleton, MD, MPH, MSc, FACP, FACMI, FHIMSS, FIAHSI Apervita, Chief Informatics & Innovation Officer Contributor
    Nikhil Patel MBBS, BSc NHS, Physician Contributor
    Bryn Rhodes Dynamic Content Group Editor, Co-Chair (Clinical Decision Support)
    Derek Ritz ecGroup Inc., Principal Consultant Contributor, IHE Co-Chair (Quality Reporting and Public Health)
    Julie Scherer, PhD Motive Medical Intelligence, Chief Informatics Officer Contributor
    Julia Skapik Cognitive Medical Systems, CHIO Contributor
    Larie Smoyer, MD Motive Medical Intelligence, VP of Product Development Contributor
    Jodi Wachs MD, FAAPM&R FAMIA Clinical Informaticist Contributor