A Multi-Institutional Natural Language Processing Pipeline to Extract Performance Status From Electronic Health Records.

Journal: Cancer control : journal of the Moffitt Cancer Center
Published Date: Jan 1, 2024

Abstract

PURPOSE: Performance status (PS), an essential indicator of patients' functional abilities, is often documented in clinical notes of patients with cancer. The use of natural language processing (NLP) in extracting PS from electronic medical records (EMRs) has shown promise in enhancing clinical decision-making, patient monitoring, and research studies. We designed and validated a multi-institute NLP pipeline to automatically extract performance status from free-text patient notes.

Authors

  • Arash Maghsoudi
    Department of Biomedical Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
  • Yvonne H Sada
    Center for Innovations in Quality, Effectiveness, and Safety, Michael E. DeBakey VA Medical Center, Houston, TX, USA.
  • Sara Nowakowski
    Center for Innovations in Quality, Effectiveness, and Safety, Michael E. DeBakey VA Medical Center, Houston, TX, USA.
  • Danielle Guffey
    Dan L. Duncan Institute for Clinical and Translational Research, Baylor College of Medicine.
  • Huili Zhu
    Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
  • Sudha R Yarlagadda
    Department of Medicine, Baylor College of Medicine, Houston, TX, USA.
  • Ang Li
    Section of Hematology-Oncology, Department of Medicine, Baylor College of Medicine, Houston, Texas; Clinical Research Division, Fred Hutchinson Cancer Research Center, Seattle, Washington. Electronic address: ang.li2@bcm.edu.
  • Javad Razjouyan
    Center for Innovations in Quality, Effectiveness, and Safety, Michael E. DeBakey VA Medical Center, Houston, TX, USA.

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