Cohort profile of the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register: current status and recent enhancement of an Electronic Mental Health Record-derived data resource.
Cohort profile of the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register: current status and recent enhancement of an Electronic Mental Health Record-derived data resource.
复制标题
DOI：
10.1136/bmjopen-2015-008721
复制
发表时间：
2016-03-01
期刊：
影响因子：
2.9
通讯作者：
Stewart R
中科院分区：
文献类型：
--
作者：
Perera G;Broadbent M;Callard F;Chang CK;Downs J;Dutta R;Fernandes A;Hayes RD;Henderson M;Jackson R;Jewell A;Kadra G;Little R;Pritchard M;Shetty H;Tulloch A;Stewart R
伦敦南部和莫德斯利国家医疗服务(NHS)基金会信托生物医学研究中心(SLAM BRC)病例登记及其临床记录互动搜索(CRIS)应用程序于2008年开发，生成了一个实时、匿名、结构化和开放文本数据的研究存储库，这些数据来自伦敦东南部的大型精神卫生保健提供商SLAM使用的电子健康记录系统。在本文中，我们更新了该寄存器的描述数据，并描述了自其最初的发展以来，该数据资源的实质性扩展和延伸。描述性数据来自2014年12月31日的SLAM BRC案例登记册。目前，通过CRIS访问的患者记录超过25万份 。自2008年以来，SLAM BRC案例登记册最重要的发展是采用自然语言处理从开放文本字段提取结构化数据、与外部数据源的链接以及增加并行关系数据库(结构化查询语言)输出。到目前为止，自然语言处理应用程序已经带来了关于认知功能、教育、社会护理收据、吸烟、诊断陈述和药物治疗的新的和迄今无法访问的数据。此外，通过外部数据链接，获得了关于死亡率、医院就诊和癌症登记的大量补充信息。再加上强大的数据安全和治理结构，电子健康记录提供了有关精神障碍和常规临床护理结果的潜在变革性信息。SLAM BRC病例登记册作为一个数据库继续增长，除了延长现有病例的后续行动外，每年新增约2万个 000个新病例。数据链接和自然语言处理为进一步加强这类研究资源，实现数据的数量和深度提供了重要机会。然而，研究项目仍然需要仔细调整，以便它们考虑到来源信息的性质和质量。
The South London and Maudsley National Health Service (NHS) Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive Search (CRIS) application were developed in 2008, generating a research repository of real-time, anonymised, structured and open-text data derived from the electronic health record system used by SLaM, a large mental healthcare provider in southeast London. In this paper, we update this register's descriptive data, and describe the substantial expansion and extension of the data resource since its original development. Descriptive data were generated from the SLaM BRC Case Register on 31 December 2014. Currently, there are over 250 000 patient records accessed through CRIS. Since 2008, the most significant developments in the SLaM BRC Case Register have been the introduction of natural language processing to extract structured data from open-text fields, linkages to external sources of data, and the addition of a parallel relational database (Structured Query Language) output. Natural language processing applications to date have brought in new and hitherto inaccessible data on cognitive function, education, social care receipt, smoking, diagnostic statements and pharmacotherapy. In addition, through external data linkages, large volumes of supplementary information have been accessed on mortality, hospital attendances and cancer registrations. Coupled with robust data security and governance structures, electronic health records provide potentially transformative information on mental disorders and outcomes in routine clinical care. The SLaM BRC Case Register continues to grow as a database, with approximately 20 000 new cases added each year, in addition to extension of follow-up for existing cases. Data linkages and natural language processing present important opportunities to enhance this type of research resource further, achieving both volume and depth of data. However, research projects still need to be carefully tailored, so that they take into account the nature and quality of the source information.