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The cloud4health Project: Secondary Use of Clinical Data with Secure Cloud-Based Text Mining Services

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Scientific Computing and Algorithms in Industrial Simulations

Abstract

Advances in translational and personalized medicine require the integration of multiple patient related resources across different organizational bodies. Thus, secure cloud environments for huge data processing, storage and data integration are needed. Moreover, the integration of clinical patient data is indispensable for translational research. Although operational e-health record systems are established in most hospitals, many clinical and phenotypically relevant parameters can only be found in unstructured texts like medical records and reports. To meet these challenges, the cloud4health project established a cloud-based text mining platform to facilitate information extraction of biomedical texts in a secure cloud environment. In order to comply with privacy regulations, general technical demands and security rules for such a cloud installation were developed and have been implemented. Different clinical use cases show the wide spectrum of application of specific text mining services in a secure cloud environment. As application examples, two use cases utilizing text mining technologies to analyse pathology and surgery reports are analysed in detail.

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Notes

  1. 1.

    A recent example is the “Heartbleed bug” of the OpenSSL cryptography libraries. The vulnerability causing code was found over 2 years after its initial integration into the libraries’ code base. The flawed code rendered approximately 20% of all Internet servers vulnerable to a potential theft of private data (such as private keys).

  2. 2.

    It should be noted that the ID does not allow identifying the patient because this ID already is a result of the anonymization process. If an agreement with the responsible data protection officers can be reached, it would be desirable to only pseudonymise the documents instead, as patients could benefit from results of the text mining if these results could be mapped to a patient.

  3. 3.

    in cooperation with the Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.

  4. 4.

    RHÖN-KLINIKUM AG, Bad Neustadt/Saale, Germany.

  5. 5.

    http://www.uicc.org/.

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Acknowledgements

The project cloud4health has been funded by the German Federal Ministry of Economics and Technology in the funding program “Trusted Cloud” (FKZ 01MD11009).

Besides Fraunhofer SCAI, four other partners participated in and contributed to the project: Averbis GmbH, located in Freiburg, coordinated cloud4health, set up the UMIA based text mining environment in the cloud and developed text mining services as well. The Friedrich-Alexander-University Erlangen-Nuremberg and the RHÖN-KLINIKUM AG Bad Neustadt/Saale provided the clinical data and set up the clinical extraction workflow. Finally, TMF—Technology, Methods, and Infrastructure for Networked Medical Research, Berlin, was responsible for data protection related issues.

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Authors and Affiliations

  1. Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Schloss Birlinghoven, 53757, Sankt Augustin, Germany

    Juliane Fluck, Philipp Senger, Wolfgang Ziegler, Steffen Claus & Horst Schwichtenberg

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  1. Juliane Fluck
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  2. Philipp Senger
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  3. Wolfgang Ziegler
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  4. Steffen Claus
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  5. Horst Schwichtenberg
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Correspondence to Juliane Fluck .

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  1. Schloss Birlinghoven, Fraunhofer-Institut SCAI, Sankt Augustin, Germany

    Michael Griebel

  2. Schloss Birlinghoven, Fraunhofer-Institut SCAI, Sankt Augustin, Germany

    Anton Schüller

  3. Schloss Birlinghoven, Fraunhofer-Institut SCAI, Sankt Augustin, Germany

    Marc Alexander Schweitzer

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Fluck, J., Senger, P., Ziegler, W., Claus, S., Schwichtenberg, H. (2017). The cloud4health Project: Secondary Use of Clinical Data with Secure Cloud-Based Text Mining Services. In: Griebel, M., Schüller, A., Schweitzer, M. (eds) Scientific Computing and Algorithms in Industrial Simulations. Springer, Cham. https://doi.org/10.1007/978-3-319-62458-7_15

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