Consistency, completeness and external validity of ethnicity recording in NHS primary care records: a cohort study in 25 million patients’ records at source using OpenSAFELY

medRxiv - Primary Care Research Pub Date : 2023-11-22 DOI:10.1101/2023.11.21.23298690

The OpenSAFELY Collaborative, Colm D Andrews, Rohini Mathur, Jon Massey, Robin Park, Lisa Hopcroft, Helen J Curtis, Amir Mehrkar, Seb Bacon, George Hickman, Rebecca Smith, David Evans, Tom Ward, Simon Davy, Peter Inglesby, Iain Dillingham, Steven Maude, Thomas O’Dwyer, Ben Butler-Cole, Lucy Bridges, Chris Bates, John Parry, Frank Hester, Sam Harper, Jonathan Cockburn, Ben Goldacre, Brian MacKenna, Laurie Tomlinson, Alex J Walker, William J Hulme

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Abstract

Background Ethnicity is known to be an important correlate of health outcomes, particularly during the COVID-19 pandemic, where some ethnic groups were shown to be at higher risk of infection and adverse outcomes. The recording of patients’ ethnic groups in primary care can support research and efforts to achieve equity in service provision and outcomes; however the coding of ethnicity is known to present complex challenges. We therefore set out to describe ethnicity coding in detail with a view to supporting the use of this data in a wide range of settings, as part of wider efforts to robustly describe and define methods of using administrative data.

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NHS初级保健记录中种族记录的一致性、完整性和外部有效性:一项使用opensafety对2500万患者记录进行的队列研究

众所周知，种族是健康结果的一个重要相关因素，特别是在2019冠状病毒病大流行期间，一些种族群体被证明面临更高的感染风险和不良后果。在初级保健中记录患者的种族群体可以支持研究和努力，以实现服务提供和结果的公平性;然而，种族编码是一项复杂的挑战。因此，我们开始详细描述种族编码，以支持在广泛的环境中使用这些数据，作为更广泛的努力的一部分，以健壮地描述和定义使用管理数据的方法。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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medRxiv - Primary Care Research

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