The SAIL databank: linking multiple health and social care datasets.
The SAIL databank: linking multiple health and social care datasets.
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DOI：
10.1186/1472-6947-9-3
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发表时间：
2009-01-16
影响因子：
3.5
通讯作者：
Leake K
中科院分区：
文献类型：
--
作者：
Lyons RA;Jones KH;John G;Brooks CJ;Verplancke JP;Ford DV;Brown G;Leake K
在提供保健和社会护理服务的过程中，收集了关于病人和服务使用者的大量数据。病历电子数据系统有可能彻底改变服务提供和研究。但是，为了实现这一目标，必须保留在单个记录级别链接数据的能力，同时坚持信息治理的原则。SAIL（安全匿名信息链接）数据库已使用不同的数据集建立，迄今已加载来自多个卫生和社会保健服务提供者的5亿多条记录，并正在进一步增长。在建立了数据库的基础设施之后，这项工作的目的是开发和实施一个准确的匹配过程，以便能够为基于个人的记录分配一个独特的匿名链接字段，使数据库为记录链接研究做好准备。为此，开发了一种基于SQL的匹配算法（MACLAL，匿名链接中一致结果的匹配算法）。首先，使用MACROL评估了使用有效NHS编号作为唯一标识符基础的适用性。其次，MACRAL依次应用于将初级保健、二级保健和社会服务数据集与NHS行政登记册（NHSAR）相匹配，以评估这一过程的有效性和最佳匹配技术。在50%阈值下，使用NHS编号的验证产生了> 99.8%的特异性值和> 94.6%的灵敏度值，并且错误率<0.2%。应用了一系列将数据集与NHSAR相匹配的技术，最佳技术的敏感性值为：初级保健的GP数据集为99.9%，二级保健的PEDW数据集为99.3%，社会保健的巴黎数据库为95.2%。随着基础设施的建立，所开发的可靠的匹配程序使ALF能够始终如一地分配给数据库中的记录。SAIL数据库是记录关联研究的研究平台。
Vast amounts of data are collected about patients and service users in the course of health and social care service delivery. Electronic data systems for patient records have the potential to revolutionise service delivery and research. But in order to achieve this, it is essential that the ability to link the data at the individual record level be retained whilst adhering to the principles of information governance. The SAIL (Secure Anonymised Information Linkage) databank has been established using disparate datasets, and over 500 million records from multiple health and social care service providers have been loaded to date, with further growth in progress. Having established the infrastructure of the databank, the aim of this work was to develop and implement an accurate matching process to enable the assignment of a unique Anonymous Linking Field (ALF) to person-based records to make the databank ready for record-linkage research studies. An SQL-based matching algorithm (MACRAL, Matching Algorithm for Consistent Results in Anonymised Linkage) was developed for this purpose. Firstly the suitability of using a valid NHS number as the basis of a unique identifier was assessed using MACRAL. Secondly, MACRAL was applied in turn to match primary care, secondary care and social services datasets to the NHS Administrative Register (NHSAR), to assess the efficacy of this process, and the optimum matching technique. The validation of using the NHS number yielded specificity values > 99.8% and sensitivity values > 94.6% using probabilistic record linkage (PRL) at the 50% threshold, and error rates were < 0.2%. A range of techniques for matching datasets to the NHSAR were applied and the optimum technique resulted in sensitivity values of: 99.9% for a GP dataset from primary care, 99.3% for a PEDW dataset from secondary care and 95.2% for the PARIS database from social care. With the infrastructure that has been put in place, the reliable matching process that has been developed enables an ALF to be consistently allocated to records in the databank. The SAIL databank represents a research-ready platform for record-linkage studies.
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影响因子：
7.2
作者：
Meray, Nora;Reitsma, Johannes B.;Bonsel, Gouke J.
通讯作者：
Bonsel, Gouke J.
影响因子：
7.7
作者：
Blakely, T;Salmond, C
通讯作者：
Salmond, C
影响因子：
3.5
作者：
ZOBEL, J;DART, P
通讯作者：
DART, P
影响因子：
--
作者：
Karmeshu, J.;Agrawal, Rajeev
通讯作者：
Agrawal, Rajeev