Coathup Victoria, Macfarlane Alison, Quigley Maria
National Perinatal Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
Centre for Maternal and Child Health Research, School of Health Sciences, City University, London, UK.
BMJ Open. 2020 Oct 26;10(10):e037885. doi: 10.1136/bmjopen-2020-037885.
The objectives of this study were to describe the methods used to assess the quality of linkage between records of babies' birth registration and hospital birth records, and to evaluate the potential bias that may be introduced because of these methods.
DESIGN/SETTING: Data from the civil registration and the notification of births previously linked by the Office for National Statistics (ONS) had been further linked to birth records from the Hospital Episode Statistics (HES) for babies born in England. We developed a deterministic, six-stage algorithm to assess the quality of this linkage.
All 1 170 790 live, singleton births, occurring in National Health Service hospitals in England between 1 January 2005 and 31 December 2006.
The primary outcome was the number of successful links between ONS birth records and HES birth records. Rates of successful linkage were calculated for the cohort and the characteristics associated with unsuccessful linkage were identified.
Approximately 92% (1 074 572) of the birth registration records were successfully linked with a HES birth record. Data quality and completeness were somewhat poorer in HES birth records compared with linked birth registration and birth notification records. The quality assurance algorithms identified 1456 incorrect linkages (<1%). Compared with the linked dataset, birth records were more likely to be unlinked if babies were of white ethnic origin; born to unmarried mothers; born in East England, London, North West England or the West Midlands; or born in March.
It is possible to link administrative datasets to create large cohorts, allowing researchers to explore important questions about exposures and childhood outcomes. Missing data, coding errors and inconsistencies mean it is important that the quality of linkage is assessed prior to analysis.
本研究的目的是描述用于评估婴儿出生登记记录与医院出生记录之间关联质量的方法，并评估因这些方法可能引入的潜在偏倚。
设计/背景：国家统计局（ONS）先前关联的民事登记和出生通知数据已进一步与英格兰出生婴儿的医院事件统计（HES）出生记录相关联。我们开发了一种确定性的六阶段算法来评估这种关联的质量。
2005年1月1日至2006年12月31日期间在英格兰国民保健服务医院出生的所有1170790例活产单胎婴儿。
主要结局是ONS出生记录与HES出生记录之间成功关联的数量。计算该队列的成功关联率，并确定与未成功关联相关的特征。
约92%（1074572）的出生登记记录与HES出生记录成功关联。与关联的出生登记和出生通知记录相比，HES出生记录的数据质量和完整性略差。质量保证算法识别出1456个错误关联（<1%）。与关联数据集相比，如果婴儿为白人种族；母亲未婚；出生在英格兰东部、伦敦、英格兰西北部或西米德兰兹；或在3月出生，则出生记录更有可能未关联。
将行政数据集关联以创建大型队列是可行的，这使研究人员能够探索有关暴露因素和儿童期结局的重要问题。缺失数据、编码错误和不一致意味着在分析之前评估关联质量很重要。
