连接英格兰的人口水平教育和医院数据:我们在ECHILD中遗漏了谁?

IF 2.2 Q3 HEALTH CARE SCIENCES & SERVICES
International Journal of Population Data Science Pub Date : 2026-07-06 eCollection Date: 2026-01-01 DOI:10.23889/ijpds.v11i5.3520
Vincent Nguyen, Farzan Ramzan, Milagros Ruiz Nishiki, Ruth Blackburn, Ruth Gilbert, Katie Harron
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引用次数: 0

摘要

简介:国家小学生数据库(NPD)与国家医院数据的联系有可能提供英国儿童和年轻人几乎普遍的人口覆盖。然而,量化谁被遗漏是产生无偏人口估计的关键要求。方法:通过NHS个人人口统计服务,在NPD和二级医疗服务的纵向数据之间进行确定性联系。对关联数据应用国家数据选择。当考虑到各种社会决定因素时,我们评估了关联的个体比例,并使用具有稳健标准误差的修正泊松回归来评估非关联的风险。结果:在NPD纳入的1984-2020年间出生的25,286,870人中,84%(21,287,176/25,286,870)与二级护理数据集相关。联系率从1985/86年出生的66%(507,820/765,642)提高到2019/20年的98%(306,165/311,121),黑人群体的89%(908,998/1,026,575)到白人群体的95%(13,644,182/14,401,835)。女性(IRR: 1.08, 95%CI: 1.08- 1.09)和那些生活在更贫困地区或伦敦的人更有可能没有联系。有特殊教育需要(IRR: 0.81, 95%CI: 0.81-0.82)或免费校餐(IRR: 0.67, 95%CI: 0.67-0.68)记录的个体不太可能不相关。结论:虽然关联率随着时间的推移而提高,但在关联数据集中和未包含在关联数据集中的人之间,在性别、种族、贫困和地理方面仍然存在重要差异。鉴于数据提供商报告的总体链接率很高,这些差异主要是由选择退出的应用驱动的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Linking population-level education and hospital data in England: who are we missing in ECHILD?

Introduction: Linkage of National Pupil Database (NPD) to national hospital data has the potential to provide almost universal population coverage of children and young people in England. However, quantifying who is missed is a key requirement for producing unbiased population estimates.

Methods: Deterministic linkage was conducted between longitudinal data from the NPD and secondary healthcare services via the NHS Personal Demographic Service. National Data OptOuts were applied to the linked data. We assessed the proportion of individuals who linked and used modified Poisson regression with robust standard errors to evaluate the risk of non-linkage when accounting for a variety of social determinants.

Results: Of 25,286,870 individuals born between 1984-2020 included in NPD, 84% (21,287,176/25,286,870) linked to a secondary care dataset. Linkage rates improved from 66% (507,820/765,642) for those born in 1985/86 to 98% (306,165/311,121) in 2019/20 and ranged from 89% (908,998/1,026,575) for those with Black ethnicity to 95% (13,644,182/14,401,835) in White groups. Females (IRR: 1.08, 95%CI: 1.08- 1.09) and those living in more deprived areas or in London were more likely to be unlinked. Individuals with recorded Special Educational Needs provision (IRR: 0.81, 95%CI: 0.81-0.82) or Free School Meals (IRR: 0.67, 95%CI: 0.67-0.68) were less likely to be unlinked.

Conclusions: Whilst linkage rates have improved over time, there remain important differences in sex, ethnicity, deprivation and geography, between those who are and are not included in the linked dataset. Given high overall linkage rates reported by data providers, these differences are primarily driven by the application of Opt-Outs.

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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
386
审稿时长
20 weeks
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