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Extraction and analysis of discrete synoptic pathology report data using R.

Alexander Boag1

  • 1Department of Pathology and Molecular Medicine, Queen's University, Kingston, Ontario, K7L 3N6, Canada.

Journal of Pathology Informatics
|January 6, 2016
PubMed
Summary

A low-cost R system efficiently extracts discrete data from synoptic pathology reports, enabling easier cancer information analysis for quality assurance and research.

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Area of Science:

  • Pathology Informatics
  • Cancer Data Management
  • Health Informatics

Background:

  • Synoptic pathology reports are valuable for cancer information when data is in discrete electronic fields.
  • Provincial programs generate these reports, but local data extraction and analysis are challenging.
  • Current systems limit the accessibility of structured pathology data for local use.

Purpose of the Study:

  • To develop a cost-effective system for extracting and analyzing discrete data from synoptic pathology reports.
  • To improve the accessibility of cancer information contained within pathology reports at the local level.
  • To facilitate quality assurance and research activities through readily available structured data.

Main Methods:

  • Utilized the open-source R scripting and data analysis environment.
Keywords:
CancerRqualitysynoptic

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  • Developed a system to parse synoptic report results into a data frame.
  • Implemented basic summary statistics for data analysis.
  • Main Results:

    • Successfully processed text reports from 427 prostate needle biopsies in a pilot project.
    • Parsed data elements from synoptic reports into appropriate data classes for analysis.
    • Demonstrated the feasibility of extracting discrete data for research.

    Conclusions:

    • The developed R-based system offers a simple, low-cost solution for accessing discrete synoptic report data.
    • This approach enhances the utility of pathology reports for quality assurance and research.
    • Facilitates the use of structured cancer data for improved healthcare insights.