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Article Abstract
Objective: To implement an open source, free, and easily deployable high throughput natural language processing module to extract concepts from clinician notes and map them to Fast Healthcare Interoperability Resources (FHIR).
Materials And Methods: Using a popular open-source NLP tool (Apache cTAKES), we create FHIR resources that use modifier extensions to represent negation and NLP sourcing, and another extension to represent provenance of extracted concepts.
Results: The SMART Text2FHIR Pipeline is an open-source tool, released through standard package managers, and publicly available container images that implement the mappings, enabling ready conversion of clinical text to FHIR.
Discussion: With the increased data liquidity because of new interoperability regulations, NLP processes that can output FHIR can enable a common language for transporting structured and unstructured data. This framework can be valuable for critical public health or clinical research use cases.
Conclusion: Future work should include mapping more categories of NLP-extracted information into FHIR resources and mappings from additional open-source NLP tools.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10081439 | PMC |
| http://dx.doi.org/10.1101/2023.03.21.23287499 | DOI Listing |
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The SMART Text2FHIR Pipeline.
AMIA Annu Symp Proc
January 2024
Boston Children's Hospital, Boston, MA.
: To implement an open source, free, and easily deployable high throughput natural language processing module to extract concepts from clinician notes and map them to Fast Healthcare Interoperability Resources (FHIR). : Using a popular open-source NLP tool (Apache cTAKES), we create FHIR resources that use modifier extensions to represent negation and NLP sourcing, and another extension to represent provenance of extracted concepts. : The SMART Text2FHIR Pipeline is an open-source tool, released through standard package managers, and publicly available container images that implement the mappings, enabling ready conversion of clinical text to FHIR.
View Article and Find Full Text PDFThe SMART Text2FHIR Pipeline.
medRxiv
March 2023
Computational Health Informatics Program, Boston Children's Hospital, Department of Pediatrics, Department of Biomedical Informatics, Harvard Medical School, 401 Park Drive, Landmark Center, 5th Floor East, Boston, MA 02215, U.S.A.
Article Synopsis
- The goal is to create a free and easy-to-use NLP module to extract concepts from clinician notes and convert them to FHIR resources.
- Using Apache cTAKES, the project develops tools that handle negation and sourcing of the extracted concepts within FHIR.
- The resulting SMART Text2FHIR Pipeline is open-source, accessible through package managers, and can enhance data sharing in healthcare, supporting public health and research initiatives.