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Information models for data sharing.

S Quaglini1

  • 1Dipartimento di Informatica e Sistemistica, University of Pavia, Italy. silvana.quaglini@unipv.it

Neurological Sciences : Official Journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
|June 6, 2006
PubMed
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See all related articles

Sharing medical data between databases is challenging. This paper explores two practical, though sub-optimal, solutions for data exchange and interoperability in the absence of global standards.

Area of Science:

  • Medical Informatics
  • Health Data Management
  • Database Interoperability

Background:

  • Effective data sharing across diverse databases remains a significant challenge in the medical domain.
  • There is a critical need for standardized ontologies, terminologies, and data models at national and international levels.
  • A universally accepted global solution for medical data exchange is not yet available.

Purpose of the Study:

  • To address the critical issue of data sharing and exchange among different medical databases.
  • To present practical, albeit sub-optimal, solutions for medical data interoperability.
  • To describe two specific approaches nearing practical implementation.

Main Methods:

  • The paper focuses on describing existing or near-implementation solutions.

Related Experiment Videos

  • It does not detail novel methodology but rather reviews practical applications.
  • The methods involve the analysis and presentation of two distinct data exchange strategies.

    • Main Results:

    • Two sub-optimal solutions for medical data exchange are presented.
    • These solutions offer practical implementations for improving data sharing.
    • The described approaches are either currently in use or close to deployment.

    Conclusions:

    • In the absence of global standards, practical, sub-optimal solutions are necessary for medical data exchange.
    • The paper highlights two viable strategies for enhancing data interoperability.
    • These methods provide immediate benefits for sharing information across disparate medical databases.