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Methods Inf Med 2015; 54(03): 276-282
DOI: 10.3414/ME13-01-0133
Original Articles
Schattauer GmbH

Secure Secondary Use of Clinical Data with Cloud-based NLP Services

Towards a Highly Scalable Research Infrastructure
J. Christoph
1   Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
,
L. Griebel
1   Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
,
I. Leb
1   Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
,
I. Engel
1   Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
,
F. Köpcke
1   Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
,
D. Toddenroth
1   Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
,
H. -U. Prokosch
1   Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
,
J. Laufer
2   Rhön-Klinikum AG, Bad Neustadt/Saale, Germany
,
K. Marquardt
2   Rhön-Klinikum AG, Bad Neustadt/Saale, Germany
,
M. Sedlmayr
1   Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
› Author Affiliations
Further Information

Publication History

received: 01 December 2013

accepted: 08 October 2014

Publication Date:
22 January 2018 (online)

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Summary

Objectives: The secondary use of clinical data provides large opportunities for clinical and translational research as well as quality assurance projects. For such purposes, it is necessary to provide a flexible and scalable infrastructure that is compliant with privacy requirements. The major goals of the cloud4health project are to define such an architecture, to implement a technical prototype that fulfills these requirements and to evaluate it with three use cases.

Methods: The architecture provides components for multiple data provider sites such as hospitals to extract free text as well as structured data from local sources and de-identify such data for further anonymous or pseudonymous processing. Free text documentation is analyzed and transformed into structured information by text-mining services, which are provided within a cloud-computing environment. Thus, newly gained annotations can be integrated along with the already available structured data items and the resulting data sets can be uploaded to a central study portal for further analysis.

Results: Based on the architecture design, a prototype has been implemented and is under evaluation in three clinical use cases. Data from several hundred patients provided by a University Hospital and a private hospital chain have already been processed.

Conclusions: Cloud4health has shown how existing components for secondary use of structured data can be complemented with text-mining in a privacy compliant manner. The cloud-computing paradigm allows a flexible and dynamically adaptable service provision that facilitates the adoption of services by data providers without own investments in respective hardware resources and software tools.

Keywords

Cloud-computing - secondary use - text-mining - privacy - natural language processing - software design
 

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