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Querying archetype-based EHRs by search ontology-based XPath engineering.

Stefan Kropf1, Alexandr Uciteli2, Katrin Schierle3

  • 1Institute for Medical Informatics, Statistics and Epidemiology (IMISE), Leipzig University, Härtelstraße 16-18, Leipzig, 04107, Germany. stefan.kropf@imise.uni-leipzig.de.

Journal of Biomedical Semantics
|May 13, 2018
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Summary
This summary is machine-generated.

This study introduces a method for querying XML-based Electronic Health Records (EHRs) using search ontologies and XPath engineering. This approach enhances research question answering by improving data retrieval precision from complex health databases.

Keywords:
EHR queryElectronic health recordsInformation retrievalMedical informatics applicationsPathology electronic health recordsQuery engineeringSearch ontology

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Area of Science:

  • Health Informatics
  • Information Retrieval
  • Database Management

Background:

  • Storing legacy and new data in standardized XML-based Electronic Health Records (EHRs) on XML databases is essential.
  • Querying these databases is critical for research, but free text searches yield low precision.
  • Constraining searches to specific document parts can significantly increase precision.

Purpose of the Study:

  • To introduce and evaluate a search ontology-based method for querying XML documents.
  • To enhance the precision and efficiency of retrieving information for research questions from EHR data.
  • To support the specification of complex queries without requiring deep XPath syntax knowledge.

Main Methods:

  • Developed a search ontology XML extension to link search terms to specific XML document parts.
  • Employed search ontology-based XPath engineering, leveraging ontologies and W3C standards.
  • Applied the method to real-world research questions using a data collection for information retrieval.

Main Results:

  • Search ontology-based XPath engineering effectively supports the specification of research questions.
  • The method facilitates a more precise retrieval of information from XML-based EHRs.
  • Further improvements in precision and recall require deeper entity recognition and semantic understanding.

Conclusions:

  • The introduced Search Ontology XML extension enables ontology-based query definitions for XML documents.
  • Search ontology-based XPath engineering aids in answering research questions by simplifying complex XPath expression creation.
  • Addressing the need for skilled personnel, the role of a clinical ontologist is proposed to overcome ontology development challenges.