Literature DB >> 16160254

Design of a Multi Dimensional Database for the Archimed DataWarehouse.

Claudine Bréant1, Gérald Thurler, François Borst, Antoine Geissbuhler.   

Abstract

The Archimed data warehouse project started in 1993 at the Geneva University Hospital. It has progressively integrated seven data marts (or domains of activity) archiving medical data such as Admission/Discharge/Transfer (ADT) data, laboratory results, radiology exams, diagnoses, and procedure codes. The objective of the Archimed data warehouse is to facilitate the access to an integrated and coherent view of patient medical in order to support analytical activities such as medical statistics, clinical studies, retrieval of similar cases and data mining processes. This paper discusses three principal design aspects relative to the conception of the database of the data warehouse: 1) the granularity of the database, which refers to the level of detail or summarization of data, 2) the database model and architecture, describing how data will be presented to end users and how new data is integrated, 3) the life cycle of the database, in order to ensure long term scalability of the environment. Both, the organization of patient medical data using a standardized elementary fact representation and the use of the multi dimensional model have proved to be powerful design tools to integrate data coming from the multiple heterogeneous database systems part of the transactional Hospital Information System (HIS). Concurrently, the building of the data warehouse in an incremental way has helped to control the evolution of the data content. These three design aspects bring clarity and performance regarding data access. They also provide long term scalability to the system and resilience to further changes that may occur in source systems feeding the data warehouse.

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Year:  2005        PMID: 16160254

Source DB:  PubMed          Journal:  Stud Health Technol Inform        ISSN: 0926-9630


  2 in total

1.  From episodes of care to diagnosis codes: automatic text categorization for medico-economic encoding.

Authors:  Patrick Ruch; Julien Gobeilla; Imad Tbahritia; Antoine Geissbühlera
Journal:  AMIA Annu Symp Proc       Date:  2008-11-06

2.  Unlocking the PACS DICOM Domain for its Use in Clinical Research Data Warehouses.

Authors:  Mathias Kaspar; Leon Liman; Maximilian Ertl; Georg Fette; Lea Katharina Seidlmayer; Laura Schreiber; Frank Puppe; Stefan Störk
Journal:  J Digit Imaging       Date:  2020-08       Impact factor: 4.056

  2 in total

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