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TBase - an Integrated Electronic Health Record and Research Database for Kidney Transplant Recipients
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Network analysis of unstructured EHR data for clinical research.

Anna Bauer-Mehren1, Paea Lependu, Srinivasan V Iyer

  • 1Stanford University, Stanford, CA, USA.

AMIA Joint Summits on Translational Science Proceedings. AMIA Joint Summits on Translational Science
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Summary

Network analysis of electronic medical records identifies patient cohorts and analyzes outcomes. This approach enhances clinical research informatics by revealing relationships between diseases, drugs, and procedures.

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Area of Science:

  • Biomedical informatics
  • Clinical data analysis
  • Network science

Background:

  • Network analysis is crucial for interpreting high-throughput biomedical data, particularly protein-protein interaction networks for gene discovery.
  • Recent advancements in clinical text processing and electronic medical record (EMR) availability enable network analyses on clinical data.

Purpose of the Study:

  • To construct and utilize disease, drug, medical device, and procedure networks from clinical notes for clinical research informatics.
  • To demonstrate the application of these networks in cohort construction and outcomes analysis using a peripheral artery disease (PAD) patient safety case study.

Main Methods:

  • Extracted concepts from clinical notes in the Stanford clinical data warehouse to build networks.
  • Developed network-based methods for patient cohort construction.
  • Applied network analysis for outcomes analysis, comparing results with standard methods.

Main Results:

  • Successfully constructed networks integrating diseases, drugs, devices, and procedures from clinical notes.
  • Demonstrated the utility of network-based approaches for cohort construction in clinical research.
  • Showcased the effectiveness of network analysis for outcomes analysis, outperforming standard methods in a cilostazol safety study.

Conclusions:

  • Network-based approaches offer advantages for clinical research informatics, particularly in cohort construction and outcomes analysis.
  • The developed methodology provides a novel framework for leveraging EMR data through network science.
  • This study highlights the potential of network analysis to advance clinical research and patient care.