FHIR Clinical Guidelines (v0.2.0) (Current)

Clinical Practice Guidelines, published by Clinical Decision Support WG. This is not an authorized publication; it is the continuous build for version 0.2.0). This version is based on the current content of https://github.com/HL7/cqf-recommendations/ and changes regularly. See the Directory of published versions

1.0.0 FHIR Clinical Guidelines

The CPG IG provides a means of creating a computable expression of a clinical guideline that is faithful to guideline intent and provides the means to derive downstream capabilities such as decision support, quality measures, case reporting, and documentation templates that direct clinical documentation in support of determining guideline compliance.

TODO: Overview index

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
    • Methodology: Describes methodologies for developing 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 across multiple clinical domains.

Guideline development cycle

Figure 1.1 Iterative Guideline Development and Implementation Process (Willet, D., University of Texas Southwestern, 2018)

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
  • Improve efficiency and effectiveness of guideline dissemination and implementation processes (e.g. decrease time to uptake of clinical best practices)
  • Measure compliance with clinical practice guideline recommendations
  • Improve appropriate compliance with clinical practice guideline recommendations
  • Afford means for full lifecycle feedback loop in best practice development process (e.g. Professional Guideline Development, Learning Health System, Clinical Translational and Implementation Sciences) including basic considerations for discovery to delivery.
  • [NOTE: EBM IG focused on up front processes; Public Health and QI on reporting results, and Registries on data collection and input into EBM/research activities. Suggest expolicit collaboration with these groups.]

Indirect:

  • Minimize the time needed to implement clinical practice guideline recommendations in clinical systems
  • Improve the ability to share computable biomedical knowledge artifacts (clinical knowledge definitions, value sets, order sets, expression logic, interventions, etc.)
  • Enhance the value of computable guidelines (decrease cost/effort, increase utility/usability)

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 The data lifecycle and impacts to the public’s health (Michaels, M, U.S. Centers for Disease Control and Prevention, 2019).

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
Mike Boston UX Architect Contributor
Matthew M. Burton, MD Apervita, Inc., VP Clinical Informatics Editor
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 Editor
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)
Susan J. Robinson, PhD CDC Contributor
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
Keith Toussaint KMT Strategies, Principal Contributor
Jodi Wachs MD, FAAPM&R FAMIA Clinical Informaticist Contributor
David Winters The MITRE Corporation Contributor