QI-Core Implementation Guide
6.0.0 - STU6 United States of America flag

QI-Core Implementation Guide, published by HL7 International / Clinical Quality Information. This guide is not an authorized publication; it is the continuous build for version 6.0.0 built by the FHIR (HL7® FHIR® Standard) CI Build. This version is based on the current content of https://github.com/HL7/fhir-qi-core/ and changes regularly. See the Directory of published versions

Quality Improvement Core (QI-Core) Implementation Guide

Official URL: http://hl7.org/fhir/us/qicore/ImplementationGuide/hl7.fhir.us.qicore Version: 6.0.0
Active as of 2023-12-04 Computable Name: QICore

This STU 6.0 update to the QI-Core profiles updates to US-Core STU v6.1.0. See the version history for a complete listing of changes to this version.

Summary

The QI-Core Implementation Guide defines a set of FHIR profiles with extensions and bindings needed to create interoperable, quality-focused applications. The profiles in this implementation guide derive from and extend the US Core profiles to provide a common foundation for building, sharing, and evaluating knowledge artifacts across quality improvement efforts in the US Realm.

As an HL7 FHIR Implementation Guide, changes to this specification are managed by the sponsoring workgroup, Clinical Quality Information, and incorporated as part of the standard balloting process. The current roadmap follows closely behind the base FHIR roadmap, and the US Core Implementation Guide.

Contents

This guide is divided into pages which are listed at the top of each page in the menu bar:

  • Home: The home page provides summary and background information
  • Profiles: The profiles page provides a complete listing of all the profiles defined in or used by QI-Core
  • Patterns: The patterns page describes patterns of usage for QI-Core applications
  • Model Info: The model info page provides the QI-Core model information to support implementation
  • Extensions: The extensions page lists all the extensions defined as part of QI-Core
  • Terminology: The terminology page lists all terminology defined as part of QI-Core
  • Examples: The examples page provides an index of all the examples defined as part of QI-Core
  • Downloads: Downloads for definitions, examples, as well as the entire IG
  • QDM-to-QI-Core Mapping: This page provides a detailed description of mapping from QDM to QI-Core

Background

This Implementation Guide originated as a US Realm Specification with support from the Clinical Quality Framework (CQF) initiative (that concluded in 2017), which was a public-private partnership sponsored by the Centers for Medicare & Medicaid Services (CMS) and the U.S. Office of the National Coordinator (ONC) to harmonize standards for clinical decision support and electronic clinical quality measurement. The Clinical Quality Framework effort transitioned to HL7’s Clinical Quality Information (CQI) and Clinical Decision Support (CDS) Work Groups in 2016. The HL7 CQI Work Group maintains this Implementation Guide, co-sponsored by the Clinical Decision Support (CDS) HL7 Work Group to inform electronic clinical quality improvement (i.e., measurement and decision support). This Quality Improvement Core (QI-Core) Implementation Guide is intended to be usable for multiple use cases across domains, and much of the content is likely to be usable outside the US Realm.

Understanding QI-Core and its use in quality applications requires an understanding of the role of common reference models. Electronic Health Records (EHRs) are stored in many different local formats. Exchanging data between EHRs requires mapping between local data formats. It is well understood that standards can reduce the number of data maps each data provider must create. In a similar manner, to share quality measures and clinical decision support artifacts, the measures and artifacts must refer to data in a standardized way.

In the US Realm, the common reference model for electronic clinical quality measures (eCQMs) is the Quality Data Model (QDM). For clinical decision support, a common reference model is the HL7 Virtual Medical Record for Clinical Decision Support (vMR). Decision support and quality measures are closely related, and can be viewed as “two sides of the same coin”. Specifically, decision support provides guidance for clinical best practices, and quality measures assess whether clinical best practices have been followed. It therefore makes intuitive sense to use the same common reference model for both types of applications.

This initiative began in 2013 with the creation of the Quality Improvement Domain Analysis Model (QIDAM), which drew on the vMR and QDM as sources of requirements. The goal was to align on a unified logical model, Quality Information and Clinical Knowledge (QUICK), consisting of objects, attributes, and relationships such that the QUICK model could reference specific Quality Improvement Core (QI-Core) profiles aligned with specific versions of FHIR. The first QUICK model representations included a logical view derived from the corresponding FHIR profiles for the respective version of FHIR upon which QI-Core profiles are based. Recognizing the broader community focus on FHIR, QUICK logical view was aligned, structurally and semantically, as closely as possible to FHIR. While this alignment creates a common model for quality and interoperability that more easily leverages future FHIR-related efforts including Clinical Document Architecture (CDA) on FHIR. However, we recognize that defining a different conceptual/logical model for quality improvement capability splits the focus of the community. The QI-Core profiles represent the most appropriate place for the mindshare and consensus development of the exchange semantics for quality improvement use cases. The QI-Core versions have evolved with FHIR-specific tooling to include views showing differential from base FHIR resources or US Core profiles, and a Must Support view indicating all Must Support elements for each respective QI-Core profile.

Relevance of QI-Core Profiles to Authors

QI-Core classes and attributes are the most relevant to the broader QI community, lying in the intersection of clinical quality measures (CQM) and CDS, thus providing a common foundation for reusability. QI-Core derives content from US Core profiles and extensions to the extent possible. The expectation is that QI-Core will continue to grow in concert with US Core by incorporating needed extensions with broad applicability. Further extensions and coordinated profiles may be required in specific domains beyond QI-Core, e.g., radiology-specific profiles. The CQI and CDS Work Groups coordinate with HL7 Work Groups that manage specific FHIR resources to align definitions and value sets including concepts required for CDS and retrospective CQM use cases. When additional classes and attributes are needed for specific quality applications, they can be added through FHIR’s extension mechanism. These extensions, however, would not automatically result in shareable artifacts without additional coordinating agreements between interested parties. It is expected that QI-Core will evolve to include some of the extensional content when the community identifies a common need and the additional content has been validated.

QI-Core profile authoring will provide a more facile method for creating CQM and CDS artifacts with CQL that expand to full FHIR representation for implementation through CQL-to-ELM conversion.

Scope

The QI-Core FHIR Implementation Guide provides requirements and guidance for using FHIR in quality measurement and decision support. The profiles in this implementation guide will be used to meet QI-Core project objectives of:

  • Encouraging consistent access and use of data for clinical quality applications across organizations and between healthcare systems,
  • Providing guidance for consistent use of vocabularies and value sets, and
  • Standardizing the requirements for data servers and data consumers (clients) that exchange quality-related clinical data needed for calculation of quality measures and decision support.

This IG is focused on representation of clinical data and is limited in breadth to the profiles currently included in QI-Core. Not all FHIR resources are profiled, especially those that do not have clinical value in the context of quality improvement, or do not map to QIDAM. Additional extensions may be added to the current set of profiles, and additional profiles may be added at a later time. In particular, QI-Core represents a subset of the semantics covered in QIDAM, vMR, and QDM. The parts of the latter specifications that are not in the QI-Core profiles could be handled with additional profiles, if the DSTU period reveals the need for such additions. Keeping the QI-Core profiles in line with FHIR and FHIR’s “80%” rule is one way to make sure that the quality artifacts produced from QI-Core are computable, based on commonly-collected clinical data. The current set of profiles will evolve to reflect changes to the underlying FHIR resources.

The following topics are explicitly out of scope for this implementation guide:

  • Representing knowledge artifacts, analogous to Health Quality Measures Format (HQMF) or Clinical Decision Support (CDS) Knowledge Artifact Specification (KAS)
  • Representation of patient-data documents, analogous to Quality Reporting Document Architecture (QRDA) Cat I
  • Representation of documents containing results of quality measures, analogous to QRDA Cat III
  • Specifying implementation architectures and platforms for QI-Core
  • User extensions to the QI-Core profiles

Some of the above topics are under active investigation and will be topics of future standards efforts. Specifically, the FHIR Clinical Reasoning module provides resources and guidance representing and evaluating quality improvement artifacts within FHIR.

Changes in QI-Core STU 6.0 scope include a simplification to reduce the number of must support elements and further constraints on US Core content. The approach in previous QI-Core versions listed as key elements all metadata that might be relevant to clinical quality measurement and clinical decision support use cases. QI-Core STU 6.0 advances the concept that measurement and decision support real-world use cases should drive content for the IG. Thus, the profile key element tables are more concise, including only those elements necessary due to the base resource or relevant US Core profile and those elements used by tested and implemented use cases.

Quality applications may make use of patient-specific information. For this reason, all transactions must be appropriately secured, limiting access to authorized individuals and protecting data while in transit (as laid out in the FHIR Implementer’s Safety Check List). These considerations relate to any FHIR implementation, including authentication, authorization, access control consistent with patient consent, transaction logging, and following best practices. QI-Core security conformance rules are as follows:

  • Systems SHOULD use TLS version 1.1 or higher with bi-directional certificate validation for all transmissions not taking place over a secure network connection.
  • Systems SHOULD use OAuth or an equivalent mechanism to provide necessary authentication (user or system-level).
  • Systems SHOULD use either IHE’s ATNA standard for audit logging or an equivalent using the AuditEvent resource.

The server (data provider) is responsible for ensuring that any necessary consent records exist and are reviewed prior to each exchange of patient-identifiable healthcare information. This verification should be logged in the same manner as other transactions, as discussed above under General Security Considerations.

Provenance

QI-Core addresses provenance at a data element level. We address data element provenance as defined by each respective FHIR resource. Each FHIR resource has its own way to address provenance (author, performer, author or issued date, occurrence date, etc.). Therefore, we assure QI-Core can handle provenance based on the resource modeling. The US domain Quality Data Model handles provenance in the same way and the mapping tables from QDM attributes to QI-Core/FHIR resource elements occurs at that level. There are some instances for which QI-Core creates extensions to ensure it captures the resource-specific data provenance. Decisions to create such extensions are intentionally consistent with each resource owner’s future FHIR version direction and with discussions with the HL7 Work Groups responsible for the respective resource. QI-Core closely follows US Core and will address future US Core versions that enhance its approach to provenance.

Relationship to Other Initiatives

QI-Core has been harmonized with other FHIR-based initiatives, particularly, the Data Access Framework (DAF). US Core is a US Realm Implementation Guide, developed under the DAF initiative, that maps ONC Common Clinical Data Set elements to FHIR resources. The data elements in US Core are also in QI-Core, and whenever possible, profiles defined in QI-Core are derived from the profiles in US Core. As a result, conforming to US Core automatically satisfies a significant subset of the conformance requirements of QI-Core. QI-Core conformance involves supporting certain additional data elements not required by US Core, because they are needed for quality measures or clinical decision support.

Because QI-Core profiles derive from US Core profiles where possible, wherever US Core defines a binding, the QI-Core profiles inherit that binding. QI-Core may specify additional constraints, such as requiring a binding that is only preferred in the US Core base profile, but in general, the QI-Core profiles use the same bindings as US Core. This means that QI-Core is currently a US Realm specification. To support applications outside the US Realm, additional binding analysis and effort would be required.

QI-Core’s extensions have also been reviewed by HL7 Work Groups and other initiatives to validate that QI-Core extensions will not create future conflicts. Other initiatives that the QI-Core effort is aligning with include the Clinical Information Modeling Initiative (CIMI) and Graphite Health.

In addition, the QI-Core effort continues to update the mapping from QDM to QI-Core such that a CQL-based artifact written with QDM as the model would be executable against a QI-Core compliant FHIR endpoint.

Naming Conventions

QI-Core profiles are indicated by the prefix “QICore”. For example, the QI-Core profile of Patient is named QICorePatient.

Extensions and Mappings

QI-Core adds a variety of extensions to core FHIR classes. These extensions derive from two primary sources: the Quality Improvement Domain Analysis Model (QIDAM), and the Quality Data Model (QDM). Profile pages contain definitions of extensions and mappings to QDM as an aid for current users of QDM.

MustSupport Flag

QI-Core derives from US Core and so the requirements on “MustSupport” defined in US Core must be respected.

In addition to the requirements defined in the US Core base, QI-Core further describes and constrains the “MustSupport” functionality.

Certain elements in the QI-Core profiles have a “MustSupport” flag. In the QI-Core quality profiles, the MustSupport flag is used to indicate whether the element must be supported in QI implementations. More specifically, labeling an element as MustSupport means that quality improvement implementations SHALL understand and process the element.

In addition, only elements where MustSupport is true can be used in quality measure criteria or decision support condition and triggering logic. This is because if the logic references an element, the conclusion is not valid unless the exchanging system supports the elements being referenced by the logic.

Although support is not guaranteed, references to elements where MustSupport is false (or does not appear) in the QI-Core profile would be useful and should be provided. All elements in the QI-Core profiles, including those that are not MustSupport, can be used in CDS actions (i.e. right-hand side or consequents of CDS rules). For example, vaccination protocol in ImmunizationRecommendation is not a MustSupport element, so it cannot be used in a quality measure or as a criteria for triggering a CDS action. However, it can be filled in as part of the recommendation of a CDS application.

Although the element may be returned in a resource when the resource is retrieved from an EHR, no logical processing involving that data element can be expected. Note that the MustSupport flag does not imply that the element will always have a value, if the lower cardinality is zero. The only assurance associated with MustSupport is that the quality improvement application will try to retrieve the data and process it if the data allows.

Specific applications can modify the profiles and set MustSupport flags to true if they will process additional elements, but setting a MustSupport flag from true to false is noncompliant.

A number of QI-Core profiles inherit directly from US Core profiles, if any, or other FHIR resources (i.e. US Core Implantable Device Profile, US Core Pediatric BMI for Age, US Core Smoking Status etc.) and the underlying Reference elements can address the US Core or FHIR profiles for the items referenced. For any other references to base FHIR resources or those not formally defined in a QI-Core Profile, the referenced resource SHALL be a QI-Core Profile if a QI-Core Profile exists for the resource type. For example, US Core Smoking Status references US Core Patient profile, the reference to Patient SHALL be a valid QI-Core Patient.

In summary, MustSupport elements represent the minimal set of data elements that must be supported in quality applications, defined as follows:

  • Data elements whenever that data is available,
  • Quality artifact authors SHOULD reference only elements that are marked must support, especially in the left-hand side of artifacts (measure criteria, decision support inclusion/exclusion criteria, etc.). However, additional expectations for the data requirements of artifacts MAY be communicated via the dataRequirements elements of knowledge artifacts, and
  • Quality improvement artifact applications SHALL recognize and process all MustSupport elements in QI-Core.

Throughout the QI-Core profiles elements that are marked as required, meaning they have a minimum cardinality of 1, will also be marked as MustSupport. In the case of complex elements if the top-level element is marked as MustSupport then any required sub-elements will be marked as MustSupport as well.

Modifying Attributes

Within FHIR resources, some elements are considered Modifying Elements, indicating that the value of that element may change the interpretation of the resource. Examples of modifying elements include status (in many resources), negations (e.g. Immunization.wasNotGiven), and certainty qualifications (e.g. Observation.reliability). Decision support and quality implementations MUST always check the values of modifying elements. For example, in processing an Immunization resource, the application must inspect the “wasNotGiven” element to determine whether the immunization was given or was not given to the patient. For this reason, modifying elements SHALL be treated as MustSupport, even if not declared.

Identifying Occupational Data for Health

The profile inherited from US Core Observation Occupation Profile is based upon the core FHIR Observation Resource and implements the US Core Data for Interoperability (USCDI) Occupation and Occupation Industry requirements. That profile’s Example Usage Scenarios include:

  • Query for a patient’s work history
  • Record or update past or present jobs belonging to a patient

To obtain information regarding other Occupational Data for Health (ODH)-specific concept as indicated in the ODH version STU 1.3 Artifacts Summary use the QI-Core SimpleObservation profile Observation.code element to reference the exact LOINC code referenced by the specific ODH element of interest (e.g., 74165-2 for History of employment status NIOSH; 11341-5 for History of Occupation, 87510-4 Date of Retirement, etc.).

Negation in QI-Core

QI-Core defines the following profiles specifically for representing negation rationale:

QI-Core Positive Profile QI-Core Negation Profile Base Resource
QICore Communication QICore Communication Not Done Communication
QICore DeviceRequest QICore Device Not Requested DeviceRequest
QICore Immunization QICore Immunization Not Done Immunization
QICore MedicationAdministration QICore MedicationAdministration Not Done MedicationAdministration
QICore MedicationDispense QICore MedicationDispense Declined MedicationDispense
QICore MedicationRequest QICore Medication Not Requested MedicationRequest
QICore Simple Observation QICore Observation Cancelled Observation
QICore Procedure QICore Procedure Not Done Procedure
QICore ServiceRequest QICore Service Not Requested ServiceRequest
QICore Task QICore Task Rejected Task

The QICore ObservationCancelled profile SHOULD be used for all specific observation profile content including:

Please note: some US Core hyperlinks are currently inaccessible as a result of US Core combining SDOH with Screening Assessment (previously Observation Survey)

Two commonly used patterns for negation in quality measurement and decision support are:

  • Absence of evidence for a particular event
  • Documentation of an event not occurring, together with a reason

For the purposes of quality measurement, when looking for documentation that a particular event did not occur, it must be documented with a reason in order to meet the intent. If a reason is not part of the intent, then the absence of evidence pattern should be used, rather than documentation of an event not occurring.

In particular, QI-Core defines several profiles that support explicit documentation of the fact that an activity or event did not occur. For these cases, the profiles define at least the following information:

  • Explicit indication that the action/event did not occur (such as doNotPerform or notDone)
  • What activity/event did not occur (typically in terms of a value set or list of codes)
  • The reason the activity/event did not occur (Preferably represented using one of an established set of Negation Reason Codes)
  • When the fact that the activity/event did not occur was recorded

Note that although these aspects are all present within each negation profile defined by QI-Core, they are represented differently in different resources. As a result, each negation profile uses a combination of constraints and extensions to provide consistent representation of negated actions or events within QI-Core.

The following examples differentiate methods to indicate (a) presence of evidence of an action, (b) absence of evidence of an action, and (c) negation rationale for not performing an action. In each case, the “action” is an administration of medication included within a value set for “Antithrombotic Therapy”.

Presence

Evidence that “Antithrombotic Therapy” (defined by a medication-specific value set) was administered:

define "Antithrombotic Administered":
  ["MedicationAdministration": "Antithrombotic Therapy"] AntithromboticTherapy
    where AntithromboticTherapy.status = 'completed'
      and AntithromboticTherapy.category ~ QICoreCommon."Inpatient"

Absence

No evidence that “Antithrombotic Therapy” medication was administered:

define "No Antithrombotic Therapy":
  not exists (
    ["MedicationAdministration": "Antithrombotic Therapy"] AntithromboticTherapy
      where AntithromboticTherapy.status = 'completed'
        and AntithromboticTherapy.category ~ QICoreCommon."Inpatient"
  ) #### Negation Rationale

Evidence that “Antithrombotic Therapy” medication administration did not occur for an acceptable medical reason as defined by a particular value set (i.e., negation rationale):

define "Antithrombotic Not Administered":
  ["MedicationAdministrationNotDone": "Antithrombotic Therapy"] NotAdministered
    where NotAdministered.statusReason in "Medical Reason"

In this example for negation rationale, the logic looks for a member of the value set “Medical Reason” as the rationale for not administering any of the anticoagulant and antiplatelet medications specified in the “Antithrombotic Therapy” value set.

NOTE: The above example uses profile-informed authoring (i.e. the QICore model) to retrieve MedicationAdministration resources with a status of not-done. Because the MedicationAdministrationNotDone profile fixes the value of the status element to not-done, expressions do not need to test the value of the status element. In other words, all resources retrieved using the MedicationAdministrationNotDone profile are guaranteed to have a status value of not-done.

To report Antithrombotic Therapy Not Administered, implementing systems reference the canonical URL of the “Antithrombotic Therapy” value set using the notDoneValueSet extension to indicate providers did not administer any of the medications in the “Antithrombotic Therapy” value set. By referencing the value set canonical URL to negate the entire value set rather than reporting a specific member code from the value set, clinicians are not forced to arbitrarily select a specific medication from the “Antithrombotic Therapy” value set that they did not administer in order to negate.

Similarly, to report “ProcedureNotDone”: “Cardiac Surgery” with a reason, the canonical URL of “Cardiac Surgery” value set is referenced by using the value set extension to indicate providers did not perform any of the cardiac surgery specified in the “Cardiac Surgery” value set.

Note that the negation profiles can be used to make two different types of negative statements:

  1. Documentation that a specific activity was not performed for a given reason (e.g. MedicationRequest example negative a specific code)
  2. Documentation that none of the activities in a given value set were performed for a given reason (e.g. MedicationRequest example negating a value set)

Each of the negation profiles provides an example illustrating both types of negative statements.

Guidance for the use of Negation Profiles

Quality Measure and Clinical Decision Support authors and implementers should be cautious to prevent a reason for not performing a single item from a value set to indicate that the reason applies to all value set members. This may become more problematic as automated data extraction progresses and directly impacts EHR implementation. Clinicians require a rapid way to document that none of the members of the negation set could be selected. Caution is required to prevent a single member selection from being interpreted as if all value set members were selected.

This would be the most common use case. A less frequent need is to indicate that they did not do ONE of the members of the value set. Stakeholders should understand that either a reason for not acting on a value set or a single member from that value set meet criteria for the notDone expression.

Response to a query for a reason will result in fulfilling the criteria that meet the not-performed extension as long as two criteria have been met:

  1. Presence of a concept (code) from the statusReason value set
  2. Presence of the code representing what has not occurred which may be identified as:
    1. A direct reference code (DRC) indicating the expected activity (if the measure or CDS artifact included only a DRC)
    2. A value set OID representing the expected activity
    3. Any concept or code from within the expected value set

The reason the profile indicates the .code as qicore-notDoneValueSet is to allow a clinician to indicate “I did none of these” with the respective statusReason or doNotPerformReason. Implementer feedback suggests that clinicians prefer the “none of these” approach rather than a requirement to select a single element from a list. However, there are clinical situations in which a clinician will indicate a reason for not performing a specific activity that represents one of the members of a value set bound to a specific data element in a measure or a CDS.

Examples of such a scenario:

  1. A measure numerator criterion includes an order for angiotensin-converting enzyme inhibitors (ACEI). The clinician indicates not ordering enalapril due to the patient’s intolerance (drowsiness) and, instead, orders another ACEI in the same value set, lisinopril. The order for lisinopril would fulfill criteria for the numerator regardless of meeting criteria for MedicationNotRequested. However, if the clinician did not order another medication from the value set (e.g., lisinopril), the presence of a doNotPerformReason for the value set member enalapril fulfills the criteria for MedicationNotRequested and the patient would be excluded from the measure even though numerator criteria were not met.
  2. A measure criterion for anticoagulation uses a value set containing warfarin or direct-oral-anticoagulant (DOAC). Studies may support preference of DOAC due to long-term outcomes, but the clinician may select a reason for not ordering DOAC due to its expense. That reason for the single item (DOAC) meets criteria for the expression and fail to recognize lack of compliance with any anticoagulation.
  3. A measure evaluating lipid management uses a statin value set containing atorvastatin. The clinician may provide a reason for not ordering atorvastatin, such as myopathy. That reason meets criteria for the expression and fails to recognize lack of compliance with any lipid therapy, but the patient might be able to tolerate ezetimibe/simvastatin.

Artifact developers should consider these facts when evaluating data retrieved as it pertains to each measure's intent and value set development. Implementers should consider these facts to consider providing data capture opportunities that limit practitioner burden.

Terminology Bindings

Uniformity in vocabularies and value sets enhances the interoperability of knowledge artifacts, but also forces data owners to translate local data into the required vocabulary. As a US Realm product, QI-Core requires value sets and vocabularies referenced in the ONC Common Clinical Data Set (CCDS) and the US Core Data for Interoperability. Because QI-Core is expected to be applied outside the US Realm, and also in clinical settings where local terminologies exist, US Realm bindings could be accompanied by alternative codes as translation codes in the QI-Core profiles. In the case that the US Core Data for Interoperability adopts QI-Core and CQL, policy should be created to mandate the preferred bindings given in the standard.

Note that quality improvement artifact authors should pay close attention to binding parameters specified in the profiles to determine whether the value set defined in the binding is exemplar or should be constrained to a specific value set when used. For example, the code element of the MedicationRequest profile is bound to the complete value set for the RxNorm code system, indicating that all MedicationRequest instances SHALL use codes from the RxNorm code system, but within any given artifact, instances will typically use a restricted value set.

Resource References and “Any”

FHIR resources frequently contain references (pointers) to other FHIR resources. For example, Encounter.patient is a reference to a Patient resource. In QI-Core, most references are constrained to QICore-profiled resourcegs. For example, QICore-Encounter.patient must point to a Patient resource that conforms to the QICore-Patient profile. Consequently, any extensions or bindings expected to exist in QICore-Patient are also present in the resource pointed to by Encounter.patient. References to QI-Core extensions accessed through references are guaranteed to be valid. References to resources that do not currently have QI-Core profiles are not constrained, and as such, only the core FHIR properties and bindings are guaranteed to exist.

A particular problem occurs when a resource reference permits any type of resource, such as Encounter.indication. When dealing with “Any” references, the current method of specifying profiles does not allow the profile author to specify something to the effect of “a QI-Core resource when there is one, and a FHIR core resource if there isn’t.” In QI-Core, the resources in “Any” references SHALL conform to QI-Core profiles if the base resource has been profiled.

Summary of Conformance Requirements

Conformance to this QI-Core Implementation Guide requires the following (in addition to adherence to core FHIR requirements):

  • Implementations SHALL support all profile types in the QI-Core set (listed in the profiles page) for resources they exchange
  • Server implementations SHALL declare their support of the QI-Core profiles in a FHIR CapabilityStatement
  • Conformant servers will at minimum support FHIR’s read and search operations
  • Servers SHALL supply the MustSupport data elements whenever that data is available
  • Quality improvement applications SHALL recognize and process all MustSupport elements in QI-Core
  • Modifying attributes SHALL be treated as MustSupport, even if not explicitly declared
  • The resources in “Any” references SHALL conform to QI-Core profiles if the base resource has a QI-Core profile
  • Applications SHALL NOT process resource instances that include unknown modifying attributes
  • Applications SHOULD use the preferred value sets
  • In the US Realm, applications SHALL be simultaneously compliant with QI-Core profiles and US Core profiles. As such, the more restrictive bindings between US Core and QI-Core SHALL be adhered to. For example, all value sets that are required in US Core SHALL be required by QI-Core, regardless of the binding strength in QI-Core.

Author Information

Author Name Affiliation Role
Abdullah Rafiqi ICF Editor
Anne Smith NCQA Contributor
Ben Hamlin NCQA Contributor
Bryn Rhodes Smile Digital Health Editor
Chris Moesel The MITRE Corporation Contributor
Claude Nanjo University of Utah Originator
Claudia Hall   Contributor
Floyd Eisenberg iParsimony, LLC Primary
James Bradley The MITRE Corporation Contributor
Jason Walonoski The MITRE Corporation Contributor
Jen Seeman ICF Editor
Juliet Rubini ICF Contributor
Linda Michaelsen Optum Contributor
Mark Kramer The MITRE Corporation Originator
Jason Mathews The MITRE Corporation Originator
Lisa Anderson Mathematica Contributor
Lloyd McKenzie Gevity Consulting Contributor
Marc Hadley The MITRE Corporation Contributor
Paul Denning The MITRE Corporation Contributor
Peter Muir ICF, Inc. Contributor
Raman Srinivasan IBM Watson Health Contributor
Robert Samples   Contributor
Sam Sayer The MITRE Corporation Contributor
Stan Rankins Telligen Contributor
Yan Heras Optimum eHealth, LLC Contributor
Yanyan Hu The Joint Commission Contributor