Sharing statewide health data for genetic research

描述（由申请人提供）：本研究将促进研究和解决与一系列疾病的家族聚集性相关的问题。其目的是创建一个对美国医疗个性化具有无与伦比价值的研究资源，同时保持个人的机密性。促进研究人员获取现有数据的需求日益增加。该提案提供了整合两个超大数据存储库的方法，由此产生的研究基础设施将利用目前在不同机构中持有的前所未有的数据量。犹他州卫生部和犹他大学将合作整合数以百万计的记录，以提供这样的资源。证据表明，很少有疾病具有简单的遗传基础，即由单个基因的完全渗透突变引起的疾病。相反，大多数疾病是复杂的，这意味着许多基因可能导致疾病的发展。通过该提案创建的关联数据集将使研究人员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。索赔数据（ICD9代码）是全州范围内的一部分，犹他州卫生部的行政数据库将用于提供诊断信息。家谱记录和相连的出生证明是世界上最大的此类收藏之一，犹他州人口数据库的一部分，将提供家庭结构。有三个具体目标：

DESCRIPTION (provided by applicant): 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).