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Modeling Flowsheet Data for Clinical Research.

Steven G Johnson1, Matthew D Byrne2, Beverly Christie3

  • 1University of Minnesota, Institute for Health Informatics.

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Summary
This summary is machine-generated.

Clinical data repositories need more interprofessional data for care coordination. This study details creating an ontology to organize extended electronic health record data, improving research accessibility and clinical insights.

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Area of Science:

  • Health Informatics
  • Clinical Data Management
  • Ontology Engineering

Background:

  • Clinical data repositories (CDRs) are vital for healthcare analytics but often lack comprehensive interprofessional data.
  • Care coordination necessitates integrating data from all clinicians to assess collaborative impact on patient outcomes.
  • Existing CDRs require enhanced data structures to support research on collaborative care.

Purpose of the Study:

  • To characterize extended clinical data within the University of Minnesota's CDR from electronic health record (EHR) flowsheet data.
  • To describe a process for developing an ontology to organize and improve accessibility of this extended clinical data for researchers.
  • To evaluate the utility of the ontology using a pressure ulcer example and compare data retrieval efficiency.

Main Methods:

  • Extraction and characterization of extended clinical data from EHR flowsheet data in a CDR.
  • Development of a data organization process using ontology engineering principles.
  • Implementation and testing of the ontology within the i2b2 research environment.
  • Comparative analysis of concept retrieval efficiency with different data organization strategies.

Main Results:

  • The study identified and characterized significant extended clinical data within the CDR.
  • A novel ontology creation process was established for organizing EHR flowsheet data.
  • The pressure ulcer ontology demonstrated improved concept accessibility in i2b2.
  • Challenges in manual data processing and concept harmonization were identified.

Conclusions:

  • Integrating extended interprofessional data into CDRs is crucial for understanding collaborative care.
  • Ontology development provides a structured approach to enhance the utility and accessibility of complex clinical data.
  • Further research is needed to refine manual processes and address concept heterogeneity for comprehensive data utilization.