Data warehouse approach to build a decision-support platform for orthopedics based on clinical and academic requirements

Sheng Hui Lin, Yuan Chii G Lee, Chien-Yeh Hsu

研究成果: 雜誌貢獻文章同行評審

6 引文 斯高帕斯(Scopus)


The continuous quality improvement has become a trend in the contemporary medical society, and that can be achieved by the specialty database implement. Decision-support system in the academic and clinical aspects are included in the process such continuous quality improvement. The database has its limitation in the decision-support due to deficiency of on-line analytic function. The data warehouse offers the sophisticated function for decision-support processes. However, the implement of data warehouse may face a lot of obstacles, included expensive cost and large personnel. We had previously established a database of orthopedics, which collected the patients' data since 2002. The new system was constructed based on this specialty database, the knowledge architectures was build up via specialists committee and accreditation indicators. The major function was to generate sufficient information for decision-support process in the academic and clinical aspects. The execution efficiency of this system is more effective than database. The unique knowledge architecture can form a distinguishing feature of the department. The cost that saved from personnel and time reduced from reports generation for accreditation is remarkable. The stratification of web-based interface application can be assessed through questionnaires; the outcome is satisfactory as what we previously expected. The sophisticate function of the data warehouse is hard to express in a solitary department of the hospital, especially when they had already owned traditional database. The experience of this system construction can be useful as one option for upgrade of specialty database and a step forward to the goal of the continuous quality improvement.
頁(從 - 到)1-12
期刊International Journal of Bio-Science and Bio-Technology
出版狀態已發佈 - 3月 2010

ASJC Scopus subject areas

  • 生物醫學工程
  • 生物技術
  • 生物工程
  • 人工智慧


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