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

这项研究将有助于研究和解决与广泛的家庭聚集性相关的问题， 一系列疾病。其目的是创造一个研究资源的无与伦比的价值， 在美国的医疗个性化，同时保持 个人的保密性。越来越需要为研究人员获得 现有数据采集。该建议提供了整合两个极端 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 目前在不同机构中保存的大量数据。犹他州卫生部 和犹他州大学将合作整合数以百万计的记录，以提供这样一个 resource.有证据表明，很少有疾病有一个简单的遗传基础，也就是说， 是由单个基因的完全外显突变引起的相反，大多数疾病是复杂的，这意味着 许多基因可能导致这种疾病的发展。创建的链接数据集 通过这项提议，将使研究人员能够研究复杂的遗传疾病， 完成原本不可能完成的科学。声明数据（ICD 9代码）， 犹他州卫生部全州范围内的行政数据库的一部分将用于 提供诊断信息。家谱记录和相关的出生证明， 犹他州人口数据库是世界上最大的人口数据库之一， 结构有三个具体目标： 1.制定各机构之间以安全和保密的方式分享数据的方法。 2.创建并维护健康数据与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. 该结果将创建一个新的数据源，用于未来的研究，其中 个人的广泛健康史与这些个人的文件相协调， 他们的大家庭的一部分（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).