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Semantic processing of EHR data for clinical research.

Hong Sun1, Kristof Depraetere1, Jos De Roo1

  • 1Advanced Clinical Applications Research Group, Agfa HealthCare, Moutstraat 100, 9000 Gent, Belgium.

Journal of Biomedical Informatics
|October 31, 2015
PubMed
Summary
This summary is machine-generated.

This study introduces a semantic data virtualization approach to integrate electronic health records (EHRs) from diverse sources. It enables on-demand data generation in various formats for clinical research, enhancing data reusability and accessibility.

Keywords:
Clinical researchEHRN3 rulesRESTfulSemantic interoperabilitySemantic web stack

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Area of Science:

  • Health Informatics
  • Clinical Data Management
  • Semantic Web Technologies

Background:

  • Increasing demand for semantically processed and integrated clinical data from heterogeneous sources for research.
  • Challenges in unifying disparate Electronic Health Record (EHR) systems for effective clinical research applications.

Purpose of the Study:

  • To present a novel approach for integrating EHRs from heterogeneous resources.
  • To generate integrated data in various formats and semantics tailored for diverse clinical research needs.
  • To avoid costly upfront data dumping and synchronization processes.

Main Methods:

  • Implementation of semantic data virtualization layers over existing data sources.
  • Mapping of EHR data to Resource Description Framework (RDF) with source semantics.
  • Conversion to harmonized domain semantics using ontologies and terminologies.
  • Further conversion to application semantics for storage in clinical research databases (e.g., i2b2, OMOP).
  • Utilization of N3 rules and an N3 Reasoner (EYE) for semantic conversions and proof generation.

Main Results:

  • Successful integration of EHRs from heterogeneous resources.
  • On-demand generation of data in requested semantics or formats.
  • Enhanced data reusability through semantic harmonization.
  • Demonstrated applicability in real-world scenarios processing large-scale EHR data.

Conclusions:

  • The proposed semantic data virtualization approach effectively integrates diverse EHR data.
  • This method supports various clinical research applications by providing data in required formats and semantics.
  • The approach offers a flexible and efficient solution for clinical data integration and reuse.