比较组成社区对等组的可选方法:一个数据仓库应用程序。

J. Studnicki, A. Hevner, D. Berndt, S. Luther
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引用次数: 10

摘要

一种评估社区健康状况的方法在南佛罗里达大学已经研究了十年。该方法被称为CATCH(跟踪社区健康的综合评估),利用来自多个数据源的健康状况指标。在联邦拨款的支持下,已经创建了一个独特的数据仓库,用于自动化CATCH评估,并增强在线分析处理,以实现高效的数据浏览、知识发现和模型测试。本文回顾了两种同伴分组方法(人口规模与预测年龄调整死亡率)的比较,以证明仓库的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Comparing alternative methods for composing community peer groups: a data warehouse application.
A method for assessing the health status of communities has been under development for a decade at the University of South Florida. Known as CATCH (Comprehensive Assessment for Tracking Community Health), the method utilizes health status indicators from multiple data sources. With federal grant support, a unique data warehouse has been created to automate CATCH assessments and to enhance online analytical processing for efficient data browsing, knowledge discovery, and model testing. A comparison of two peer grouping methods (population size versus predicted age-adjusted mortality) is reviewed to demonstrate the warehouse capabilities.
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