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Related Experiment Video

Updated: Jul 5, 2025

A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
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Capturing Individual-level Social Determinants from Clinical Text.

Jennifer J Liang1, Diwakar Mahajan1, Ananya S Iyengar1

  • 1IBM Research, Yorktown Heights, NY.

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|January 15, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a new dataset for extracting social determinants of health (SDOH) from entire clinical notes, not just the social history section. This resource aims to improve patient care by making crucial nonmedical health factors more accessible.

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Area of Science:

  • Clinical Informatics
  • Natural Language Processing
  • Public Health

Background:

  • Social determinants of health (SDOH) significantly impact patient outcomes but are often buried in unstructured clinical notes.
  • Existing methods for SDOH extraction are limited by narrow definitions and focus on specific note sections.

Purpose of the Study:

  • To develop and release a comprehensive dataset for SDOH extraction from entire clinical notes.
  • To characterize the documentation of SDOH across various sections of clinical text.
  • To evaluate baseline extraction systems and the efficacy of training on limited sections.

Main Methods:

  • Creation of a new dataset with 2,007 annotations across 7 SDOH domains within 500 clinical notes.
  • Annotation of SDOH across entire notes, not restricted to the social history section.
  • Development and evaluation of token classification and generative models for SDOH extraction.

Main Results:

  • The study characterizes the presence and location of SDOH information within clinical notes.
  • Baseline models demonstrate feasibility for SDOH extraction using both token classification and generative approaches.
  • Analysis investigates the effectiveness of training solely on the social history section versus the entire note.

Conclusions:

  • A novel, broadly defined SDOH dataset annotated across entire clinical notes has been created.
  • The dataset and baseline systems provide a foundation for advancing SDOH extraction research.
  • Public release of the dataset will facilitate further investigation into improving patient care through accessible SDOH data.