Building the Data Mart on Antibiotic Usage for Infection Control

I. Rheem
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引用次数: 1

Abstract

Data stored in hospital information systems has a great potential to improve adequacy assessment and quality management. Moreover, an establishment of a data warehouse has been known to improve quality management and to offer help to clinicians. This study constructed a data mart that can be used to analyze antibiotic usage as a part of systematic and effective data analysis of infection control information. Metadata was designed by using the XML DTD method after selecting components and evaluation measures for infection control. OLAP — a multidimensional analysis tool — for antibiotic usage analysis was developed by building a data mart through modeling. Experimental data were obtained from data on antibiotic usage at a university hospital in Cheonan area for one month in July of 1997. The major components of infection control metadata were antibiotic resistance information, antibiotic usage information, infection information, laboratory test information, patient information, and infection related costs. Among them, a data mart was constructed by designing a database to apply antibiotic usage information to a star schema. In addition, OLAP was demonstrated by calculating the statistics of antibiotic usage for one month. This study reports the development of a data mart on antibiotic usage for infection control through the implementation of XML and OLAP techniques. Building a conceptual, structured data mart would allow for a rapid delivery and diverse analysis of infection control information.
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感染控制中抗生素使用数据集市的建立
存储在医院信息系统中的数据在改进充分性评估和质量管理方面具有很大的潜力。此外,数据仓库的建立已经被认为可以改善质量管理并为临床医生提供帮助。本研究构建了一个数据集市,可用于分析抗生素使用情况,作为系统有效的感染控制信息数据分析的一部分。选取感染控制成分和评价措施后,采用XML DTD方法设计元数据。通过建模建立数据集市,开发了用于抗生素使用分析的多维分析工具OLAP。实验资料是1997年7月在天安地区某大学医院进行的为期一个月的抗生素使用资料。感染控制元数据的主要组成部分是抗生素耐药性信息、抗生素使用信息、感染信息、实验室检测信息、患者信息和感染相关费用。其中,通过设计一个数据库,将抗生素使用信息应用到星型模式中,构建了一个数据集市。此外,通过计算一个月的抗生素使用统计数据来证明OLAP。本研究报告了通过XML和OLAP技术实现的抗生素使用感染控制数据集市的开发。建立一个概念性的、结构化的数据集市将允许对感染控制信息进行快速传递和多样化的分析。
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