Title |
A Generative Tool for Building Health Applications Driven by ISO 13606 Archetypes
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Published in |
Journal of Medical Systems, October 2011
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DOI | 10.1007/s10916-011-9783-1 |
Pubmed ID | |
Authors |
Marcos Menárguez-Tortosa, Catalina Martínez-Costa, Jesualdo Tomás Fernández-Breis |
Abstract |
The use of Electronic Healthcare Records (EHR) standards in the development of healthcare applications is crucial for achieving the semantic interoperability of clinical information. Advanced EHR standards make use of the dual model architecture, which provides a solution for clinical interoperability based on the separation of the information and knowledge. However, the impact of such standards is biased by the limited availability of tools that facilitate their usage and practical implementation. In this paper, we present an approach for the automatic generation of clinical applications for the ISO 13606 EHR standard, which is based on the dual model architecture. This generator has been generically designed, so it can be easily adapted to other dual model standards and can generate applications for multiple technological platforms. Such good properties are based on the combination of standards for the representation of generic user interfaces and model-driven engineering techniques. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Japan | 1 | 33% |
United Kingdom | 1 | 33% |
Unknown | 1 | 33% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 3 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Brazil | 3 | 9% |
United States | 2 | 6% |
Sweden | 1 | 3% |
Spain | 1 | 3% |
Unknown | 27 | 79% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Master | 7 | 21% |
Student > Ph. D. Student | 6 | 18% |
Student > Doctoral Student | 3 | 9% |
Researcher | 3 | 9% |
Student > Postgraduate | 3 | 9% |
Other | 7 | 21% |
Unknown | 5 | 15% |
Readers by discipline | Count | As % |
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Computer Science | 17 | 50% |
Engineering | 3 | 9% |
Social Sciences | 2 | 6% |
Medicine and Dentistry | 2 | 6% |
Immunology and Microbiology | 1 | 3% |
Other | 2 | 6% |
Unknown | 7 | 21% |