Many studies have examined the integration of information systems into healthcare institutions, leading to several standards in the healthcare domain (CORBAmed: Common Object Request Broker Architecture in Medicine; HL7: Health Level Seven International; DICOM: Digital Imaging and Communications in Medicine; and IHE: Integrating the Healthcare Enterprise). Due to the existence of a wide diversity of heterogeneous systems, three essential factors are necessary to fully integrate a system: data, functions and workflow. However, most of the previous studies have dealt with only one or two of these factors and this makes the system integration unsatisfactory. In this paper, we propose a flexible, scalable architecture for Hospital Information Systems (HIS). Our main purpose is to provide a practical solution to insure HIS interoperability so that healthcare institutions can communicate without being obliged to change their local information systems and without altering the tasks of the healthcare professionals. Our architecture is a mediation architecture with 3 levels: 1) a database level, 2) a middleware level and 3) a user interface level. The mediation is based on two central components: the Mediator and the Adapter. Using the XML format allows us to establish a structured, secured exchange of healthcare data. The notion of medical ontology is introduced to solve semantic conflicts and to unify the language used for the exchange. Our mediation architecture provides an effective, promising model that promotes the integration of hospital information systems that are autonomous, heterogeneous, semantically interoperable and platform-independent.
Datawarehouses can be extremely large and ressource demanding, which is not always affordable in a local environment. Hence, in order to deal with the big amounts of data held in the datawarehouses, Cloud warehousing seems to be the solution. On the other hand, many entreprises use datawarehouses for data analysis and use XML to deal with semi-structured data but also to take advantage of the web environment. Therefore, the idea of combining the two solutions in a parallel environment seems necessary. Thus, the goal of the study presented in this paper is to use XML to store and exchange data and to connect it to the distributed processing of multidimentional data. This article deals with the problematic of storing documents in distributed environments such as the cloud nodes, and discusses the possibility of combining the storage of data and the decisional analysis based on OLAP cubes in cloud environments, using the MapReduce model for query processing.
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