Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report.

Identifying Care Home Residents in Electronic Health Records - An OpenSAFELY Short Data Report.
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DOI:
10.12688/wellcomeopenres.16737.1
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发表时间:
2021
影响因子:
--
通讯作者:
Goldacre B
Goldacre B
中科院分区:
其他
文献类型:
--
作者:
Schultze A;Bates C;Cockburn J;MacKenna B;Nightingale E;Curtis HJ;Hulme WJ;Morton CE;Croker R;Bacon S;McDonald HI;Rentsch CT;Bhaskaran K;Mathur R;Tomlinson LA;Williamson EJ;Forbes H;Tazare J;Grint DJ;Walker AJ;Inglesby P;DeVito NJ;Mehrkar A;Hickman G;Davy S;Ward T;Fisher L;Evans D;Wing K;Wong AY;McManus R;Parry J;Hester F;Harper S;Evans SJ;Douglas IJ;Smeeth L;Eggo RM;Goldacre B

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背景:新冠肺炎疫情对养老院居民造成了严重影响。电子健康记录(EHR)在研究这一弱势群体的医疗保健需求方面具有巨大潜力;然而,在电子病历中识别养老院居民并不简单。我们描述并比较了在新创建的opensafety - tpp数据分析平台中识别养老院居民的三种不同方法。方法:我们代表英国国家医疗服务体系(NHS England),确定了2020年2月1日可能住在养老院的65岁或以上的个人,使用了(1)复杂的地址链接,其中使用护理和质量委员会(CQC)的数据将清洁的全科医生注册地址与老年护理家庭地址相匹配;(2)电子病历中的编码事件;(3)家庭标识符、年龄和家庭规模,识别有3名以上65岁或以上老人的家庭为潜在的安老院居民。调查人员无法获得原始地址。结果:在4,437,286名65岁及以上的老年人中,使用复杂地址链接识别为潜在养老院居民的比例为2.27%,使用编码事件识别为1.96%,使用家庭规模和年龄识别为3.13%,使用上述两种方法中的任何一种识别为3.74%。使用所有三种方法将53,210人(占所有潜在养老院居民的32.0%)归类为养老院居民。地址链接与其他方法重叠最大;93.3%使用地址链接识别为护理院居民的个人也使用编码事件或家庭年龄和规模识别为护理院居民。结论:我们描述了EHR中识别养老院居民的三种方法之间的部分重叠,并提供了如何在opensafety - tpp中实施这些方法的详细说明,以支持研究COVID-19大流行对养老院居民的影响。
Background: Care home residents have been severely affected by the COVID-19 pandemic. Electronic Health Records (EHR) hold significant potential for studying the healthcare needs of this vulnerable population; however, identifying care home residents in EHR is not straightforward. We describe and compare three different methods for identifying care home residents in the newly created OpenSAFELY-TPP data analytics platform.  Methods: Working on behalf of NHS England, we identified individuals aged 65 years or older potentially living in a care home on the 1st of February 2020 using (1) a complex address linkage, in which cleaned GP registered addresses were matched to old age care home addresses using data from the Care and Quality Commission (CQC); (2) coded events in the EHR; (3) household identifiers, age and household size to identify households with more than 3 individuals aged 65 years or older as potential care home residents. Raw addresses were not available to the investigators. Results: Of 4,437,286 individuals aged 65 years or older, 2.27% were identified as potential care home residents using the complex address linkage, 1.96% using coded events, 3.13% using household size and age and 3.74% using either of these methods. 53,210 individuals (32.0% of all potential care home residents) were classified as care home residents using all three methods. Address linkage had the largest overlap with the other methods; 93.3% of individuals identified as care home residents using the address linkage were also identified as such using either coded events or household age and size.  Conclusion: We have described the partial overlap between three methods for identifying care home residents in EHR, and provide detailed instructions for how to implement these in OpenSAFELY-TPP to support research into the impact of the COVID-19 pandemic on care home residents.