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
