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Related Concept Videos

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...

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Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
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Published on: January 22, 2011

PTXT Finder - an application for finding appropriate EHR data elements for data analysis using cross referencing

Jau-Huei Lin1, Peter J Haug

  • 1Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, USA.

AMIA ... Annual Symposium Proceedings. AMIA Symposium
|August 13, 2008
PubMed
Summary
This summary is machine-generated.

PTXT Finder streamlines mapping clinical variables to electronic health record (EHR) data elements. This tool aids researchers by providing descriptions, hierarchies, and statistics for accurate data element identification.

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Area of Science:

  • Biomedical Informatics
  • Clinical Data Management
  • Health Information Technology

Background:

  • Mapping clinical variables to electronic health record (EHR) data elements is labor-intensive.
  • Data dictionary descriptions are often insufficient for precise data element identification.
  • Leveraging semantic information and usage patterns is crucial for accurate mapping.

Purpose of the Study:

  • To develop PTXT Finder, a tool to automate the mapping of clinical variables to EHR data elements.
  • To reduce manual effort in clinical data integration and analysis.
  • To enhance the accuracy of data element selection for decision support systems.

Main Methods:

  • PTXT Finder integrates description, hierarchy, and statistical views.
  • The system facilitates cross-referencing between these different information sources.
  • Utilizes semantic information derived from taxonomy and element usage.

Main Results:

  • PTXT Finder effectively reduces manual effort in mapping clinical variables.
  • Provides users with multiple views for cross-referencing and validation.
  • Improves the ability to identify appropriate EHR data elements.

Conclusions:

  • PTXT Finder is a valuable tool for improving the efficiency and accuracy of clinical data mapping.
  • Enhances the usability of EHR data for clinical decision support.
  • Supports better integration of clinical variables into health information systems.