A taxonomy for advancing systematic error analysis in multi-site electronic health record-based clinical concept extraction.

Journal: Journal of the American Medical Informatics Association : JAMIA
PMID: 38742455

Abstract

BACKGROUND: Error analysis plays a crucial role in clinical concept extraction, a fundamental subtask within clinical natural language processing (NLP). The process typically involves a manual review of error types, such as contextual and linguistic factors contributing to their occurrence, and the identification of underlying causes to refine the NLP model and improve its performance. Conducting error analysis can be complex, requiring a combination of NLP expertise and domain-specific knowledge. Due to the high heterogeneity of electronic health record (EHR) settings across different institutions, challenges may arise when attempting to standardize and reproduce the error analysis process.

Authors

  • Sunyang Fu
    Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, USA.
  • Liwei Wang
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
  • Huan He
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • Andrew Wen
    Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR, USA.
  • Nansu Zong
    Health System Department of Biomedical Informatics, University of California, San Diego, La Jolla, California, USA.
  • Anamika Kumari
    Department of Population and Quantitative Health Sciences, University of Massachusetts Chan Medical School, Boston, MA 01655, United States.
  • Feifan Liu
    Department of Quantitative Health Sciences and Radiology, University of Massachusetts Medical School, Worcester, MA, USA.
  • Sicheng Zhou
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Texas, USA.
  • Rui Zhang
    Department of Cardiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.
  • Chenyu Li
    Key Laboratory of Resources Biology and Biotechnology in Western China, Ministry of Education, Provincial Key Laboratory of Biotechnology of Shaanxi Province, College of Life Sciences, Northwest University, Xi'an 710069, China.
  • Yanshan Wang
    Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
  • Jennifer St Sauver
    Department of Quantitative Health Sciences, Mayo Clinic, Rochester, USA.
  • Hongfang Liu
    Department of Artificial Intelligence & Informatics, Mayo Clinic, Rochester, MN, United States.
  • Sunghwan Sohn
    Department of Artificial Intelligence and Informatics, Mayo Clinic, Rochester, USA.

Keywords

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