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Updated: Jul 18, 2026

Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research
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Generation of Comprehensive Thoracic Oncology Database - Tool for Translational Research

Published on: January 22, 2011

A reference model for clinical tumour documentation.

Udo Altmann1, Frank Rüdiger Katz, Joachim Dudeck

  • 1Institute of Medical Informatics, University of Giessen, Germany. udo.altmann@informatik.med.uni-giessen.de

Studies in Health Technology and Informatics
|November 17, 2006
PubMed
Summary

Establishing common system semantics is crucial for data exchange in cancer registries. This paper details a 15-year experience with a data model for a tumor documentation system (GTDS) and its requirements for effective data integration.

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Area of Science:

  • Oncology
  • Health Informatics
  • Data Management

Background:

  • Common system semantics are essential for data comparability and exchange between different healthcare systems.
  • Hospital cancer registries face challenges in data integration and exchange with other information systems.
  • A cooperative effort led to the development of a data model for a new tumor documentation system (GTDS) based on a common basic dataset agreed upon by the German Association of Comprehensive Cancer Centres (ADT).

Purpose of the Study:

  • To present an entity-relationship view of the GTDS data model.
  • To describe a method for importing data from hospital or practice information systems into cancer registries.
  • To discuss the requirements for effective data exchange between hospital cancer registries and external systems.

Main Methods:

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  • Development of a data model based on a common basic dataset for hospital cancer registries.
  • Utilizing an entity-relationship view to represent the data model.
  • Describing a data import method for integrating external data into the registry system.

Main Results:

  • A robust data model for a tumor documentation system (GTDS) has been developed over 15 years.
  • A method for importing data from hospital and practice information systems has been established.
  • Key requirements for effective data exchange include the ability to associate disease phenomena and therapies with a central tumor entity across encounters.

Conclusions:

  • The presented reference model and proposed requirements for data exchange are crucial for enhancing interoperability in cancer registries.
  • The developed data model and exchange methods can potentially be adapted for other chronic diseases.
  • Effective data exchange relies on a common understanding of system semantics and the ability to link related clinical information.