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The SMART Text2FHIR Pipeline.

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This summary is machine-generated.

A new open-source tool, SMART Text2FHIR Pipeline, converts clinical text into Fast Healthcare Interoperability Resources (FHIR). This enables seamless data exchange for public health and clinical research.

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Area of Science:

  • Health Informatics
  • Natural Language Processing
  • Clinical Data Interoperability

Background:

  • Clinician notes contain valuable unstructured data.
  • Extracting and structuring this data is crucial for research and public health.
  • Existing methods for data extraction and interoperability can be complex and costly.

Purpose of the Study:

  • To develop an open-source, free, and easily deployable high-throughput natural language processing (NLP) module.
  • To extract concepts from clinical notes.
  • To map these concepts to Fast Healthcare Interoperability Resources (FHIR).

Main Methods:

  • Utilized Apache cTAKES, a popular open-source NLP tool.
  • Developed FHIR resources with modifier extensions for negation and NLP sourcing.
  • Incorporated extensions for concept provenance.

Main Results:

  • The SMART Text2FHIR Pipeline is an open-source tool.
  • It is available through standard package managers and container images.
  • Enables efficient conversion of clinical text to FHIR.

Conclusions:

  • The SMART Text2FHIR Pipeline facilitates data liquidity and a common language for data transport.
  • This framework supports critical public health and clinical research use cases.
  • Future work includes expanding NLP concept mapping and integrating additional NLP tools.