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BackgroundFor an optimal care of patients in home healthcare, it is essential to exchange healthcare-related information with other stakeholders. Unfortunately, paper-based documentation procedures as well as the heterogeneity between information systems inhibit a well-regulated communication. Therefore, a digital patient care record is introduced to establish the foundation for integrating healthcare-related information.MethodsFor the digital patient care record, suitable integration techniques are required that store data in a compact way and offer flexibility as well as robustness. For this purpose, a generic storage structure based on the entity-attribute-value (EAV) model is introduced. This storage structure fulfills the stated requirements and incoming information can be stored directly without any loss of data.Evaluation Results and DiscussionsFirst performance tests regarding the query response time are given in this paper. The tests measured the connection time, the query execution time, and the time for traversing the result set. The time for executing the query is lowest. The time for traversing the results strongly depends on the number of documents. A concept comparison to other integration techniques is also presented.ConclusionsThis approach offers flexibility concerning different standard types and the evolution in healthcare knowledge and processes. It also allows for highly sparse data to be stored in a compact way. The underlying database structure is presented, the import process for extracting incoming reports is described and the export process for generating new outgoing standardized reports is briefly illustrated.

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In recent years, the tourism assistance community is gradually shifting its emphasis to digital, interactive systems. Our project aims for digital tourism assistance by combining mobile guiding and route recommendation based on community networks. We use complex networks to tackle problems, such as deriving optimal routes in conjunction with knowledge deduced from our social tourist network, and giving a respectable prediction of which meta-and multimedia data about touristic objects are needed while the tourist is on tour. This article describes ongoing work on the recommendation system and mobile semantic replication strategies.

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