Rapid Prototyping Strategy for a Surgical Data Warehouse

S.-T. Tang; Y.-F. Huang; M.-L. Hsiao; S.-H. Yang; S.-T. Young

doi:10.1055/s-0038-1634364

Methods of Information in Medicine, Table of Contents

Methods Inf Med 2003; 42(03): 243-250
DOI: 10.1055/s-0038-1634364

Original article

Schattauer GmbH

Rapid Prototyping Strategy for a Surgical Data Warehouse

S.-T. Tang

¹Institute of Biomedical Engineering, National Yang-Ming University, Taiwan

,

Y.-F. Huang

²Department of Nursing, Chang-Gung Institute of Nursing, Taiwan

,

M.-L. Hsiao

³Experimental Surgery Division, Department of Surgery, Taipei Veterans General Hospital, Taiwan

,

S.-H. Yang

⁴Colorectal Surgery Division, Department of Surgery, Taipei Veterans General Hospital, Taiwan

,

S.-T. Young

¹Institute of Biomedical Engineering, National Yang-Ming University, Taiwan

› Author Affiliations

Abstract

Summary

Objectives: Healthcare processes typically generate an enormous volume of patient information. This information largely represents unexploited knowledge, since current hospital operational systems (e.g., HIS, RIS) are not suitable for knowledge exploitation. Data warehousing provides an attractive method for solving these problems, but the process is very complicated. This study presents a novel strategy for effectively implementing a healthcare data warehouse.

Methods: This study adopted the rapid prototyping (RP) method, which involves intensive interactions. System developers and users were closely linked throughout the life cycle of the system development. The presence of iterative RP loops meant that the system requirements were increasingly integrated and problems were gradually solved, such that the prototype system evolved into the final operational system.

Results: The results were analyzed by monitoring the series of iterative RP loops. First a definite workflow for ensuring data completeness was established, taking a patient-oriented viewpoint when collecting the data. Subsequently the system architecture was determined for data retrieval, storage, and manipulation. This architecture also clarifies the relationships among the novel system and legacy systems. Finally, a graphic user interface for data presentation was implemented.

Conclusions: Our results clearly demonstrate the potential for adopting an RP strategy in the successful establishment of a healthcare data warehouse. The strategy can be modified and expanded to provide new services or support new application domains. The design patterns and modular architecture used in the framework will be useful in solving problems in different healthcare domains.

Keywords

Databases - data collection - integrated information - systems integration

Full Text

References

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