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Methods Inf Med 2004; 43(02): 171-183
DOI: 10.1055/s-0038-1633856
Original Article
Schattauer GmbH

A Meta-Model of Chemotherapy Planning in the Multi-Hospital/Multi-Trial-Center-Environment of Pediatric Oncology

S. Garde
1   Department of Medical Informatics, University of Heidelberg, Germany
,
B. Baumgarten   *
1   Department of Medical Informatics, University of Heidelberg, Germany
,
O. Basu
2   Pediatric Hematology-Oncology and Endocrinology, University Hospital, Essen, Germany
,
N. Graf
3   University Hospital of the Saarland, Pediatric Hematology and Oncology, Homburg, Germany
,
R. Haux   **
1   Department of Medical Informatics, University of Heidelberg, Germany
,
R. Herold
4   Competence Network Pediatric Oncology and Hematology, Coordination and Management Group, Charité – Universitary Medicine, Campus Virchow-Klinikum, Berlin, Germany
,
U. Kutscha
1   Department of Medical Informatics, University of Heidelberg, Germany
,
F. Schilling
5   Olgahospital, Child and Adolescent Medicine, Pediatrics 5, Stuttgart, Germany
,
B. Selle   ***
6   Pediatric Oncology, Hematology and Immunology, University of Heidelberg, Germany
,
C. Spiess   ****
1   Department of Medical Informatics, University of Heidelberg, Germany
,
T. Wetter
1   Department of Medical Informatics, University of Heidelberg, Germany
,
P. Knaup
1   Department of Medical Informatics, University of Heidelberg, Germany
› Author Affiliations
Further Information

Publication History

Publication Date:
05 February 2018 (online)

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Summary

Objective: Chemotherapy planning in pediatric oncology is complex and time-consuming. The correctness of the calculation according to state-of-the-art research is crucial for curing the child. Computer-assistance can be of great value. The objective of our research was to work out a meta-model of chemotherapy planning based on the Unified Modeling Language (UML). The meta-model is used for the development of an application system which serves as a knowledge-acquisition tool for chemotherapy protocols in pediatric oncology as well as for providing protocol-based care.

Methods: We applied evolutionary prototyping, software re-engineering techniques and grounded theory, a qualitative method in social research. We repeated the following steps several times over the years: Based on a requirements analysis (i) a meta-model was developed or adapted, respectively (ii). The meta-model served as a basis for implementing evolutionary prototypes (iii). Further requirements were identified (i) from clinical use of the systems.

Results: We developed a comprehensive UML-based meta-model for chemotherapy planning in pediatric oncology (chemoMM). We implemented it and introduced evolutionary prototypes (CATIPO and DOSPO) in several medical centers. Systematic validation of the prototypes enabled us to derive a final meta-model which covers the requirements that have turned out to be necessary in clinical routine.

Conclusions: We have developed an application system that fits well into clinical routine of pediatric oncology in Germany. Validation results have shown that the implementation of the meta-model chemoMM can adequately support the knowledge acquisition process for protocol-based care.

Keywords

Chemotherapy planning - pediatric oncology - UML

* current address: Novartis Pharma AG, Department Intelligent Integration of Information, Informatics and Knowledge Management at Novartis Research, Basel, Switzerland


** current address: UMIT – University for Health Informatics and Technology Tyrol, Institute for Health Information Systems, Innsbruck, Austria


*** current address: St. Annastift Children’s Hospital, Department of Pediatric Oncology, Hematology and Immunology, Ludwigshafen, Germany


**** current address: gap GmbH, Mannheim, Germany


 

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