National Database for Autism Research (NDAR): Big Data Opportunities for Health Services Research and Health Technology Assessment
National Database for Autism Research (NDAR): Big Data Opportunities for Health Services Research and Health Technology Assessment
复制标题
DOI：
10.1007/s40273-015-0331-6
复制
发表时间：
2016-02-01
影响因子：
4.4
通讯作者：
Ungar, Wendy J.
中科院分区：
文献类型：
--
作者：
Payakachat, Nalin;Tilford, J. Mick;Ungar, Wendy J.
国家自闭症研究数据库（NDAR）是美国国立卫生研究院（NIH）资助的研究数据存储库，通过自闭症研究人员和NIH之间的数据共享协议整合异构数据集而创建。迄今为止，NDAR被认为是自闭症研究中最大的神经科学和基因组数据库。除了生物医学数据外，NDAR还包含大量临床和行为评估以及新干预措施的健康结果。重要的是，NDAR具有全球唯一的患者标识符，可以链接到汇总的个人水平数据，用于假设生成和测试，以及复制研究结果。因此，NDAR促进合作，并最大限度地提高对原始数据收集的公共投资。由于自闭症儿童的筛查和诊断技术以及干预措施非常昂贵，因此需要进行卫生服务研究（HSR）和卫生技术评估（HTA），以获得更多证据，以便在必要时促进实施。本文介绍了NDAR，并解释了它的价值，卫生服务研究人员和决策科学家感兴趣的自闭症和其他心理健康状况。我们提供了NDAR的范围和结构的描述，并说明了数据可能会随着时间的推移而增长，并成为可用于HSR和HTA。
The National Database for Autism Research (NDAR) is a US National Institutes of Health (NIH)-funded research data repository created by integrating heterogeneous datasets through data sharing agreements between autism researchers and the NIH. To date, NDAR is considered the largest neuroscience and genomic data repository for autism research. In addition to biomedical data, NDAR contains a large collection of clinical and behavioral assessments and health outcomes from novel interventions. Importantly, NDAR has a global unique patient identifier that can be linked to aggregated individual-level data for hypothesis generation and testing, and for replicating research findings. As such, NDAR promotes collaboration and maximizes public investment in the original data collection. As screening and diagnostic technologies as well as interventions for children with autism are expensive, health services research (HSR) and health technology assessment (HTA) are needed to generate more evidence to facilitate implementation when warranted. This article describes NDAR and explains its value to health services researchers and decision scientists interested in autism and other mental health conditions. We provide a description of the scope and structure of NDAR and illustrate how data are likely to grow over time and become available for HSR and HTA.