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Related Experiment Video

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Evaluating Health Information Systems Using Ontologies.

Shahryar Eivazzadeh1, Peter Anderberg, Tobias C Larsson

  • 1Department of Health Science, Blekinge Institute of Technology, Karlskrona, Sweden. shahryar.eivazzadeh@bth.se.

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|June 18, 2016
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Summary
This summary is machine-generated.

The Unified eValuation using Ontology (UVON) method effectively organizes health information system evaluation aspects. This approach unifies quality attributes from diverse systems and frameworks, enabling systematic and context-sensitive evaluation.

Keywords:
biomedicalevaluationhealth information systemsontologiestechnology assessment

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Area of Science:

  • Health Informatics
  • Information Systems Evaluation
  • Ontology Engineering

Background:

  • Existing health information system evaluation frameworks often lack case-specific adaptability or struggle to aggregate findings from heterogeneous systems.
  • Model-based frameworks offer general guidelines, while case-specific approaches may yield disparate evaluation aspects, hindering comparative analysis.
  • The challenge lies in unifying diverse evaluation needs for comprehensive assessment across varied health information systems.

Purpose of the Study:

  • To develop a method for suggesting relevant evaluation aspects for one or more health information systems, regardless of similarity or heterogeneity.
  • To organize, unify, and aggregate quality attributes from systems and external evaluation frameworks.
  • To enable systematic and context-sensitive evaluation across diverse health information system landscapes.

Main Methods:

  • Developed the Unified eValuation using Ontology (UVON) method, leveraging semantic networks and ontologies to structure quality attributes.
  • Integrated UVON with model-based evaluation frameworks and developed an approach to extract practical evaluation aspects from the ontology.
  • Applied and validated the UVON method within the Future Internet Social and Technological Alignment Research (FI-STAR) project, involving 7 cloud-based eHealth applications.

Main Results:

  • The UVON method successfully generated a unified ontology structure reflecting quality attributes from 7 eHealth applications and the MAST evaluation framework.
  • Stakeholders validated the relevance of UVON-derived evaluation aspects for the FI-STAR project.
  • Extracted evaluation aspects were used to develop questionnaires for patients and health professionals, facilitating individual and project-wide evaluations.

Conclusions:

  • The UVON method provides a systematic, context-sensitive, and relevant approach to defining evaluation aspects for heterogeneous health information systems.
  • It effectively organizes, unifies, and aggregates quality attributes using ontological structures, accommodating both model-based and stakeholder-elicited requirements.
  • UVON facilitates comprehensive evaluation across diverse health information system implementations.