Sharing statewide health data for genetic research (1 R01 RR021746-01A1)

这项研究将促进研究和解决与广泛的家庭聚集性有关的问题 一系列疾病。其目的是创造一个无与伦比的研究资源， 美国国内医疗的个性化，同时保持 个人的保密。越来越需要便利研究人员访问 现有数据获取。这一建议提供了将两个极端的 大型数据存储库和由此产生的研究基础设施将利用前所未有的 目前保存在不同机构中的数据量。犹他州卫生部 犹他大学将合作整合数百万条记录，以便提供这样一种 资源。有证据表明，很少有疾病有简单的遗传基础，即 由单基因的完全穿透性突变引起。相反，大多数疾病是复杂的，这意味着 许多基因可能在疾病的发展中起作用。已创建的链接数据集 通过这项提议，研究人员将能够调查复杂的遗传疾病， 完成原本不可能完成的科学研究。符合以下条件的索赔数据(ICD9代码) 犹他州卫生部的部分全州行政数据库将用于 提供有关诊断的信息。家谱记录和相关的出生证明是 世界上最大的此类收藏之一，犹他州人口数据库将为家庭提供 结构。具体目标有三个： 1.制定各机构之间以安全和保密的方式共享数据的方法。 2.创建和维护健康数据和犹他州人口数据库之间的链接数据集。 3.开发安全的网络查询工具，修改亲属关系分析工具，并指导研究人员 使用。 这一成果将创建一个新的数据源，用于未来的研究，其中 个人广泛的健康史与这些个人的文件相协调，如 他们大家庭的一部分(亲属或血统)。

This study will facilitate research and address questions associated with familial clustering of a wide range of diseases. The purpose is to create a research resource of unmatched value to the personalization of medicine within the United States while at the same time maintaining the confidentiality of individuals. There is an increasing need to facilitate the access of researchers to existing data acquisitions. This proposal provides the methodology for integration of two extremely large data repositories and the resulting research infrastructure will harness an unprecedented volume of data that is currently held in separate institutions. The Utah State Department of Health and the University of Utah will collaborate to integrate millions of records in order to provide such a resource. Evidence suggests that few diseases have a simple genetic basis, that is, one that is caused by fully penetrant mutations in single genes. Instead, most disorders are complex, meaning that many genes may contribute to the development of the disease. The linked data sets, created through this proposal, will allow researchers to investigate complex genetic disorders, accomplishing science that would otherwise not be possible. Claims data (ICD9 codes) that are part of statewide, administrative databases at the Utah State Department of Health will be used to provide information on diagnosis. Genealogical records and linked birth certificates that are part of one of the largest such collections worldwide, the Utah Population Database, will provide family structure. There are three specific aims: 1. Develop methodology for data sharing in a secure and confidential manner between institutions. 2. Create and maintain linked data sets between health data and the Utah Population Database. 3. Develop secured web query tools, modify kinship analysis tools and instruct researchers in their use. The outcome will create a new data source to be used in future research studies, one in which extensive health histories of individuals are coordinated with documentation of those individuals as part of their larger extended family (kindred or pedigree).