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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Evaluating the potential of fast healthcare interoperability resources for clinical registry data submission
James E Tcheng1, David Finney2, Keith Boone3
1Department of Medicine, Duke University School of Medicine, Durham, NC 27705, United States.
Objective:
We conducted the Clinical Registry Extraction and Data Submission (CREDS) project to evaluate the readiness of HL7 Fast Healthcare Interoperability Resources (FHIR) for provisioning data from health information systems for the American College of Cardiology Cardiac Catheterization Percutaneous Coronary Intervention (CathPCI) Registry.
Materials And Methods:
The CREDS project had 3 workstreams: (1) evaluation of the readiness of clinical documentation for data transforms, (2) modeling of a FHIR-based clinical workflow for registry data submission, and (3) development and demonstration of a CREDS FHIR implementation for registry data submission.
Results:
Of the 344 data concepts comprising the CathPCI Registry, only 111 (32%) were sufficiently discrete to be listed in the CathPCI Data Dictionary with a terminology mapping. Cardiologist informaticians identified an additional 42 concepts suitable for provisioning via a FHIR payload. The resulting notional workflow combined FHIR-based data assembly with manual chart abstraction of compound, summative, and complex clinical concepts. A CathPCI FHIR StructureDefinition artifact was authored, incorporated into a CREDS FHIR Implementation Guide, and balloted to Standard for Trial Use status.
Discussion:
CREDS demonstrated both potential and limitations for using FHIR for registry data submission. The largest technical impediment was the volume of code (>11 000 lines) for the FHIR StructureDefinition. Lack of regularized clinical vocabularies, reliance of registries on complex clinical concepts, and absence of FHIR infrastructure must be overcome before CREDS can be used at scale.
Conclusion:
CREDS demonstrated proof-of-concept FHIR-based provisioning of clinical data for registry submission. All artifacts are open source to inform others with similar interests.
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