TY - GEN
T1 - Automated Modeling of Clinical Narrative with High Definition Natural Language Processing sing Solor and Analysis Normal Form
AU - Resnick, Melissa P.
AU - Lehouillier, Frank
AU - Brown, Steven H.
AU - Campbell, Keith E.
AU - Montella, Diane
AU - Elkin, Peter L.
N1 - Publisher Copyright:
© 2021 The European Federation for Medical Informatics (EFMI) and IOS Press. All rights reserved.
PY - 2021/11/18
Y1 - 2021/11/18
N2 - Objective: One important concept in informatics is data which meets the principles of Findability, Accessibility, Interoperability and Reusability (FAIR). Standards, such as terminologies (findability), assist with important tasks like interoperability, Natural Language Processing (NLP) (accessibility) and decision support (reusability). One terminology, Solor, integrates SNOMED CT, LOINC and RxNorm. We describe Solor, HL7 Analysis Normal Form (ANF), and their use with the high definition natural language processing (HD-NLP) program. Methods: We used HD-NLP to process 694 clinical narratives prior modeled by human experts into Solor and ANF. We compared HD-NLP output to the expert gold standard for 20% of the sample. Each clinical statement was judged 'correct' if HD-NLP output matched ANF structure and Solor concepts, or 'incorrect' if any ANF structure or Solor concepts were missing or incorrect. Judgements were summed to give totals for 'correct' and 'incorrect'. Results: 113 (80.7%) correct, 26 (18.6%) incorrect, and 1 error. Inter-rater reliability was 97.5% with Cohen's kappa of 0.948. Conclusion: The HD-NLP software provides useable complex standards-based representations for important clinical statements designed to drive CDS.
AB - Objective: One important concept in informatics is data which meets the principles of Findability, Accessibility, Interoperability and Reusability (FAIR). Standards, such as terminologies (findability), assist with important tasks like interoperability, Natural Language Processing (NLP) (accessibility) and decision support (reusability). One terminology, Solor, integrates SNOMED CT, LOINC and RxNorm. We describe Solor, HL7 Analysis Normal Form (ANF), and their use with the high definition natural language processing (HD-NLP) program. Methods: We used HD-NLP to process 694 clinical narratives prior modeled by human experts into Solor and ANF. We compared HD-NLP output to the expert gold standard for 20% of the sample. Each clinical statement was judged 'correct' if HD-NLP output matched ANF structure and Solor concepts, or 'incorrect' if any ANF structure or Solor concepts were missing or incorrect. Judgements were summed to give totals for 'correct' and 'incorrect'. Results: 113 (80.7%) correct, 26 (18.6%) incorrect, and 1 error. Inter-rater reliability was 97.5% with Cohen's kappa of 0.948. Conclusion: The HD-NLP software provides useable complex standards-based representations for important clinical statements designed to drive CDS.
KW - Clinical Decision Support
KW - Controlled Terminology
KW - Interoperability
KW - Natural Language Processing
UR - https://www.scopus.com/pages/publications/85120521352
U2 - 10.3233/SHTI210822
DO - 10.3233/SHTI210822
M3 - Conference contribution
C2 - 34795088
AN - SCOPUS:85120521352
T3 - Studies in Health Technology and Informatics
SP - 89
EP - 93
BT - Applying the FAIR Principles to Accelerate Health Research in Europe in the Post COVID-19 Era - Proceedings of the 2021 EFMI Special Topic Conference
A2 - Delgado, Jaime
A2 - Benis, Arriel
A2 - de Toledo, Paula
A2 - Gallos, Parisis
A2 - Giacomini, Mauro
A2 - Martinez-Garcia, Alicia
A2 - Salvi, Dario
PB - IOS Press BV
T2 - 2021 European Federation for Medical Informatics (EFMI) Special Topic Conference, STC 2021
Y2 - 22 November 2021 through 24 November 2021
ER -