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An adaptive semantic based mediation system for data interoperability among Health Information Systems.

Wajahat Ali Khan1, Asad Masood Khattak, Maqbool Hussain

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Summary

Heterogeneous health information systems hinder data interoperability. The ARIEN mediation system ensures accurate data exchange between different healthcare standards, improving patient care.

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Area of Science:

  • Health Informatics
  • Computer Science
  • Medical Information Systems

Background:

  • Health Information Systems (HIS) face challenges in data interoperability due to diverse healthcare standards.
  • Heterogeneity in data management obstructs seamless information exchange among HIS.

Purpose of the Study:

  • To propose and evaluate ARIEN, an adaptive mediation engine for achieving data interoperability.
  • To facilitate accurate and seamless information exchange between HIS compliant to different healthcare standards.

Main Methods:

  • Developed ARIEN, an adaptive mediation engine, utilizing ontology matching techniques.
  • Employed the Mediation Bridge Ontology (MBO) with the System for Parallel Heterogeneity (SPHeRe) and Personalized-Detailed Clinical Model (P-DCM) for semantic mapping.
  • Evaluated accuracy through medical record transformation between Clinical Document Architecture (CDA) and Virtual Medical Record (vMR) standards.

Main Results:

  • The ARIEN system demonstrated over 90% accuracy in transforming medical records between CDA and vMR standards.
  • The pattern-oriented approach from MBO significantly improved the accuracy of the transformation process.
  • The proposed mediation system enhances communication and information exchange between HIS.

Conclusions:

  • ARIEN effectively addresses data heterogeneity, enabling data interoperability among HIS.
  • The system ensures accurate and seamless medical information exchange, leading to improved healthcare services.
  • ARIEN facilitates timely healthcare delivery by overcoming interoperability barriers.