QI-Core Implementation Guide
6.0.0 - STU6
QI-Core Implementation Guide
6.0.0 - STU6
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
| Official URL: http://hl7.org/fhir/us/qicore/ImplementationGuide/hl7.fhir.us.qicore | Version: 6.0.0 | |||
| Active as of 2024-03-12 | 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.
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.
This guide is divided into pages which are listed at the top of each page in the menu bar:
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.
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.
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:
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:
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:
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.
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.
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.
QI-Core profiles are indicated by the prefix “QICore”. For example, the QI-Core profile of Patient is named QICorePatient.
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.
QI-Core derives from US Core and so the requirements on “MustSupport” defined in US Core must be respected.
QI-Core flags elements that the quality improvement community has identified as significant to express the full intent of measures and CDS artifacts or those that are used in established measures or CDS support services. Implementers are only required to support these additional elements when they are used in the measures or CDS artifacts implemented on or otherwise supported by the system. Since not all artifacts use each of these additional elements, QI-Core does not use the “MustSupport” flag to indicate these elements. Instead, “(QI-Core)” is prepended to the element’s short description found in the Description & Constraints column of the Key Elements Table, and the computable QI-Core Key Element Extension is added to each element definition. This approach is inspired by the way that US Core communicates USCDI requirements and allows IGs that extend QI-Core, such as those representing data requirements for specific measures or supporting CDS, to avoid inheriting requirements for those QI-Core-flagged elements that they do not use.
Quality improvement artifacts communicate the elements they reference using the DataRequirement structure in FHIR. This structure allows the base resource type and profile to be specified, as well as a mustSupport element that indicates which elements of the resource and profile are reference by the logic. Implementers can use this information directly from the effective data requirements to determine which elements must be provided in order to achieve a successful evaluation of the artifact. In addition, repositories and publishers may make use of this information to define artifact-specific profiles using the effective data requirements provided by the artifact.
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.
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:
To obtain information regarding other Occupational Data for Health (ODH)-specific concepts 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.).
QI-Core’s concept of negation follows the informative publication established by HL7.1 QI-Core constrains these concepts in the following way:
Absence of data
The measure or CDS artifact uses CQL to determine that an expected record artifact does not exist
Documented absence of data with a valid reason
The measure or CDS artifact uses a specifically designed QI-Core profile to indicate that an activity intentionally did not occur for a valid reason.
When there is a need to document evidence that an expected activity was not done due to patient intent and/or specific criteria, systems should use one of the ten QI-Core specific negation rationale profiles that align with existing profiles representing the expected actions. QI-Core Negation provides detailed descriptions and guidance.
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.
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.
Conformance to this QI-Core Implementation Guide requires the following (in addition to adherence to core FHIR requirements):
| 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 |
For further information about representing negatives in HL7 standards, see: HL7 Cross Paradigm Specification: Representing Negatives, Release I. April 2022. Available at: http://www.hl7.org/implement/standards/product_brief.cfm?product_id=592. Retrieved 31 December 2023. ↩
IG © 2019+ HL7 International / Clinical Quality Information. Package hl7.fhir.us.qicore#6.0.0 based on FHIR 4.0.1. Generated 2024-03-12
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