An approach to linking education, social care and electronic health records for children and young people in South London: a linkage study of child and adolescent mental health service data
An approach to linking education, social care and electronic health records for children and young people in South London: a linkage study of child and adolescent mental health service data
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DOI：
10.1136/bmjopen-2018-024355
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发表时间：
2019-06-01
期刊：
影响因子：
2.9
通讯作者：
Hayes, Richard
中科院分区：
文献类型：
--
作者：
Downs, Johnny M.;Ford, Tamsin;Hayes, Richard
建立联系的心理健康，社会和教育记录的研究，以支持区域精神卫生服务的循证实践。设置临床记录交互式搜索（CRIS）系统被用来提取个人标识符谁访问精神科服务之间的2007年9月和2013年8月。参与者35 509名儿童和青少年的临床队列多个政府和伦理委员会批准将临床心理健康服务数据与教育部（DfE）关于教育和社会护理服务的数据相关联。在健壮的治理协议下，DfE使用模糊和确定性方法来匹配个人标识符结果测量确定了与NPD不匹配的风险因素，以及不匹配偏差对精神障碍的国际统计分类第10次修订（ICD-10）分类的潜在影响，和持续缺课（< 80%的出勤率）进行了检查。概率加权和调整的方法进行了探讨，以减轻非匹配bias.Results的影响治理的挑战，包括制定一项研究协议的数据链接，这符合国家卫生服务和DfE的立法要求。从CRIS中，29278人（82.5%）与NPD学校出勤记录相匹配。在青春期后期（调整OR（aOR）0.67，95%CI 0.59至0.75）或学校人口普查时间范围之外（aOR 0.15，95%CI 0.14至0.17）提供服务降低了匹配的可能性。调整后的连锁错误，ICD-10精神障碍仍然显着相关的持续缺课（aOR 1.13，95%CI 1.07至1.22）。结论所描述的工作为教育数据被用于医疗福利在英格兰的先例。健康和教育记录之间的联系为评估心理健康对学校功能的影响提供了一个强有力的工具，但由于联系错误而产生的偏见可能会产生误导性的结果。需要与数据提供者进行合作研究，以开发链接方法，最大限度地减少链接数据分析中的潜在偏差。
Objectives Creation of linked mental health, social and education records for research to support evidence-based practice for regional mental health services.Setting The Clinical Record Interactive Search (CRIS) system was used to extract personal identifiers who accessed psychiatric services between September 2007 and August 2013.Participants A clinical cohort of 35 509 children and young people (aged 4-17 years).Design Multiple government and ethical committees approved the link of clinical mental health service data to Department for Education (DfE) data on education and social care services. Under robust governance protocols, fuzzy and deterministic approaches were used by the DfE to match personal identifiers (names, date of birth and postcode) from National Pupil Database (NPD) and CRIS data sources.Outcome measures Risk factors for non-matching to NPD were identified, and the potential impact of nonmatch biases on International Statistical Classification of Diseases, 10th Revision (ICD-10) classifications of mental disorder, and persistent school absence (< 80% attendance) were examined. Probability weighting and adjustment methods were explored as methods to mitigate the impact of non-match biases.Results Governance challenges included developing a research protocol for data linkage, which met the legislative requirements for both National Health Service and DfE. From CRIS, 29 278 (82.5%) were matched to NPD school attendance records. Presenting to services in late adolescence (adjusted OR (aOR) 0.67, 95% CI 0.59 to 0.75) or outside of school census timeframes (aOR 0.15, 95% CI 0.14 to 0.17) reduced likelihood of matching. After adjustments for linkage error, ICD-10 mental disorder remained significantly associated with persistent school absence (aOR 1.13, 95% CI 1.07 to 1.22).Conclusions The work described sets a precedent for education data being used for medical benefit in England. Linkage between health and education records offers a powerful tool for evaluating the impact of mental health on school function, but biases due to linkage error may produce misleading results. Collaborative research with data providers is needed to develop linkage methods that minimise potential biases in analyses of linked data.