Computable Care Guidelines
The Computable Care Guidelines (CCG) profile supports the expression of and sharing of health care guidelines in a grammar that can be ingested and understood by a software application.
Summary
The evidence shows that improved adherence to care guidelines can yield significant population health impacts. The Computable Care Guidelines (CCG) profile helps close what WHO calls the know-do gap; the sometimes wide chasm between what we know are the evidence-based best practices and what is actually done during health care encounters. To close this gap, CCG provides a standards-based way to describe and to share:
- the minimum data set (including coded content) that should be collected during an encounter;
- the "workflow logic" that is to be triggered based on collected content; and
- the reportable health system management indicators that may be automatically generated from the person-centric healthcare transactions.
Importantly, CCG gives us a way to track and monitor the care delivery activities (what happened) and it provides us with a way to increase guideline-adherence by indicating what should happen. In this way, it supports both feedback and feed-forward process control.
It is expected that guideline-development organizations (e.g. WHO, CDC, Diabetes Canada) would create and publish CCGs. These CCGs may be contextualized by implementing jurisdictions (e.g. Kenya Ministry of Health) to create localized versions. The jurisdictional CCGs would be ingested by computer, tablet and phone-based digital health solutions to operationalize guideline-based care across the health system. These digital health solutions would report CCG-defined management metrics back to the jurisdiction.
Benefits
“Health care in all global settings today suffers from high levels of defects in quality across many domains, and this poor-quality care causes ongoing damage to human health. Hospitalizations in low- and middle-income countries (LMICs) lead to 134 million adverse events each year, and these adverse events contribute to more than 2.5 million deaths annually. More than 830 million people with a diagnosed noncommunicable disease (NCD) are not being treated, and more than 4 million avoidable quality-related deaths each year are attributable to ineffective care for NCDs. In total, between 5.7 and 8.4 million deaths occur annually from poor quality of care in LMICs for the selected set of conditions the committee analyzed… which represents between 10 and 15 percent of the total deaths in LMICs reported by the World Health Organization (WHO) in 2015. For some conditions, deaths due to poor quality contribute to more than half of overall deaths." (Crossing the Global Quality Chasm (2018))
Details
The CCG profile leverages IHE's Dynamic Care Planning (DCP) profile. Similar to DCP, CCG expresses the care guideline using the CarePlan, PlanDefinition, ActivityDefinition and Task resources defined in the HL7 FHIR standard. CCG particularly focuses on the definition of the minimum data sets needed to operationalize the evidence-based care and on the use of IHE's mobile Aggregate Data Exchange (mADX) profile to define reportable indicators that may be generated from these data sets. The mADX profile leverages the Measure and MeasureReport FHIR resources.
Systems Affected
- Guideline-development bodies will generate CCGs and publish them as FHIR bundles hosted on a FHIR server
- Jurisdictions will contextual CCGs and publish them as FHIR bundles hosted on a FHIR server
- Digital health solution developers will modify their applications to enable them to ingest CCGs, to operationalize a UI based on the minimum data sets and the care workflow logic, and to generate and report the management metrics (mADX messages) as defined by the CCG
Actors & Transactions:
TBD
Specification
Profile Status: Final Text <Replace "Final Text" with "Trial Implementation" or "Public Comment" as appropriate.>
Documents:
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Underlying Standards:
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See Also
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Related Profiles
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- Reporting Workflow [RWF] may use Evidence Documents as inputs to the reporting process.
- Simple Image & Numeric Reports [SINR] may include data copied from Evidence Documents.
- Cross-enterprise Document Sharing for Imaging [XDS-I] can be used to share Evidence Documents between sites over a network.
- Portable Data for Imaging [PDI] can store Evidence Documents on media such as CDs.
- Import Reconciliation Workflow [IRWF] can fix patient ids, etc. of Evidence Documents when importing.
Consumer Information
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Implementer Information
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Reference Articles
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