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The Catch data warehouse: support for community health care decision-making

机译:Catch数据仓库:支持社区医疗保健决策

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The measurement and assessment of health status in communities throughout the world is a massive information technology challenge. Comprehensive Assessment for Tracking Community Health (CATCH) provides systematic methods for community-level assessment that is invaluable for resource allocation and health care policy formulation. CATCH is based on health status indicators from multiple data sources, using an innovative comparative framework and weighted evaluation process to produce a rank-ordered list of critical community health care challenges. The community-level focus is intended to empower local decision-makers by providing a clear methodology for organizing and interpreting relevant health care data. Extensive field experience with the CATCH methods, in combination with expertise in data warehousing technology, has led to an innovative application of information technology in the health care arena. The data warehouse allows a core set of reports to be produced at a reasonable cost for community use. In addition, online analytic processing (OLAP) functionality can be used to gain a deeper understanding of specific health care issues. The data warehouse in conjunction with Web-enabled dissemination methods allows the information to be presented in a variety of formats and to be distributed more widely in the decision-making community. In this paper, we focus on the technical challenges of designing and implementing an effective data warehouse for health care information. Illustrations of actual data designs and reporting formats from the CATCH data warehouse are used throughout the discussion. Ongoing research directions in health care data warehousing and community health care decision-making conclude the paper.
机译:对全世界社区的健康状况进行测量和评估是一个巨大的信息技术挑战。跟踪社区健康的综合评估(CATCH)为社区级评估提供了系统的方法,这对于资源分配和医疗政策的制定是无价的。 CATCH基于来自多个数据源的健康状况指标,使用创新的比较框架和加权评估流程来生成关键社区卫生保健挑战的排名列表。社区层面的焦点旨在通过提供一种清晰的方法来组织和解释相关的医疗保健数据,从而增强当地决策者的能力。 CATCH方法的广泛现场经验与数据仓库技术的专业知识相结合,导致了信息技术在医疗保健领域的创新应用。数据仓库允许以合理的成本生成一组核心报告,以供社区使用。此外,可以使用在线分析处理(OLAP)功能来更深入地了解特定的医疗保健问题。数据仓库与支持Web的分发方法相结合,可以使信息以各种格式呈现,并在决策社区中更广泛地分发。在本文中,我们集中于设计和实施有效的医疗保健信息数据仓库的技术挑战。在整个讨论过程中,都使用了CATCH数据仓库中的实际数据设计和报告格式的插图。本文总结了医疗数据仓库和社区医疗决策中正在进行的研究方向。

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