Maximising the Use of Existing Administrative Data Sets for Wales through Data Linking

通过与各种服务机构的日常互动，以相当大的成本收集了有关威尔士人的大量信息。目前，其中很多是在不同的数据集。如果这些信息能够以一种相互关联的方式汇集在一起，就有巨大的能力创造关于干预和政策变化的影响以及对人口健康和福祉的影响的“增值”知识。可以进行研究，检查数据中出现的关系和模式，这可能为如何解决人口水平问题提供新的见解。将分散的常规数据集汇集在一起的问题是可能违反保密性;超出最初收集数据的原因以及如何使用数据的商定界限。向无意接触个人信息的人披露个人信息必须是完全不可能的。斯旺西大学的安全匿名个人链接（SAIL）项目已经证明，可以将个人特征，事件数据和与个人相关的服务交互与这些个人的可识别信息分开，以令人满意的方式为研究人员汇集和比较来自不同数据源的数据。这是通过删除每个记录的可识别部分并用称为匹配键的代码编号替换来实现的。配对密码匙是由一个受信任的第三方机构以一种方式产生，即在一个数据集内源自个人的信息可以与另一个数据集内的信息相匹配，而无需个人的身份。SAIL的工作主要基于健康数据集，现在在安全的研究环境中可以获得大量与健康相关的数据。该项目旨在通过伙伴关系进一步扩大数据收集，明确了解问题、所需的实际步骤以及更好地为决策者提供信息的潜力。这将通过对一些分析的结构化发展来实现。研究人员有多年的工作经验，与数据提供商，主要是NHS供应商，但也与地方当局在威尔士和英格兰，以及相当丰富的经验，链接数据，现在被放置在研究分析团队，直接在SAIL环境中工作。在该奖学金的范围内，SAIL内的现有数据集将被用来展示来自多个来源的关联数据的力量，以提供更有效的基准测试，增强对数据的理解，以及比以前更详细的答案，用于研究和政策相关问题。

A large amount of information collected about people in Wales through routine interaction with various services at considerable cost. Currently a lot of this is in disparate data sets. If this information can be brought together in a linked manner there is a tremendous capacity to creat 'value added' knowledge about the effects of intervention and policy change, and about what effects the health and well being of the population. Research can be carried out examining the relationships and patterns occurring in the data that may provide new insights into how to address population level problems. The problem with bringing together the disperate routine datasets is the potential to breach confidentiality;to step outside the agreed boundaries of why the data was originally collected and how it should be used. The disclosure of personal information to someone that was not intended to have access to it must remain completely impossible. It has been demonstrated through the Secure Anonymised Individual Linked, (SAIL) project at Swansea University, that it is possible to separate personal characteristics, event data and service interactions relating to individuals, from those individual's identitfiable information, in a satisfactory way for researchers to bring together and compare data from different data sources. This is achieved by the identifiable part of each record being removed and replaced with a code number called a matching key. Matching keys are generated by a trusted third party organisation in such a way that information originating from an individual in one dataset can be matched to that in another dataset without the identity of the individual being present.The work of SAIL has been heavily based upon health datasets, and an enormous quantity of linkable health related data is now available in a secure research environment. This project is about further expanding the data collection in partnership, developing a clear understanding of the issues, the practical steps required, and the potential to better inform decision makers. This will be done through the structured development development of a number of analyses. The researcher has many years of experiences of working with data providers, mainly NHS providers, but also with local authorities in Wales and England, and considerable experience of linking data, and is now placed within the research analysis team, working directly within the SAIL environment. Within the scope of this fellowship the existing datasets within SAIL will be utilised to demonstrate the power of linked data from multiple sources to provide more effective benchmarking, enhanced understanding of the data, and more detailed answers than have previously been available for research and policy related questions.