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2342 A comprehensive profile of a retrospective care home cohort using linked health and social care data
Age and Ageing ( IF 6.0 ) Pub Date : 2024-08-08 , DOI: 10.1093/ageing/afae139.054
M Knight 1 , A Clegg 1 , O Todd 1
Affiliation  

Introduction Many UK care home (CH) residents live with multiple long-term conditions, leading to high levels of healthcare utilisation. Previous studies have used routine data to describe their health and social care characteristics separately. Accurately identifying when an individual is admitted to a CH from routine data is challenging. This study aims to provide a combined health and social care profile of a cohort of long-stay CH residents, at the point of admission, using linked primary, secondary and social care data. Methods Individuals aged 65 and over registered to a GP practice contributing to the ‘Connected Bradford’ dataset who were admitted to a CH between January 2016 and December 2019 were included. Start and end dates for social care packages (nursing and residential) were identified from local authority social care data. Respite and reablement packages were excluded. Complete self-funders were not identified with this method. Linked secondary and primary care data were used to describe health characteristics. CH residents identified using primary care records and local authority data will be compared. Results 2801 individuals were admitted to a CH during the study period of whom 2048 (73%) were long-stay residents (>6 weeks). Only 70% of participants identified using local authority data, had a primary care code indicating CH residency in their primary care records. Median length of stay was 272 days (IQR 63 to 480). Mean age at admission was 85 years (SD 8), median Index of Multiple Deprivation decile five. 59% of residents required nursing care from admission. 79% of individuals were taking 5 or more medications. Conclusions Using local authority data offers a novel way to identify and characterise CH residents. Linkage of primary care records to local authority data improves identification of CH residents using routine data. Additional linkage with address history would further improve accuracy.

中文翻译:


2342 使用关联的健康和社会护理数据对回顾性护理院队列进行全面分析



简介 许多英国疗养院 (CH) 居民患有多种长期疾病,导致医疗保健利用率很高。先前的研究使用常规数据分别描述他们的健康和社会护理特征。从常规数据中准确识别个人何时被送入 CH 具有挑战性。本研究旨在利用相关的初级、二级和社会护理数据,提供长期居住在 CH 的居民在入院时的综合健康和社会护理概况。方法 纳入了 2016 年 1 月至 2019 年 12 月期间入住 CH 并为“互联布拉德福德”数据集做出贡献的 GP 诊所注册的 65 岁及以上个人。社会护理套餐(护理和住宿)的开始和结束日期是根据地方当局的社会护理数据确定的。暂息和重新安置计划被排除在外。这种方法无法识别完全自筹资金的人。关联的二级和初级保健数据用于描述健康特征。将比较使用初级保健记录和地方当局数据确定的 CH 居民。结果 研究期间共有 2801 名患者入住 CH,其中 2048 名 (73%) 为长期住院医师(>6 周)。使用地方当局数据确定的参与者中,只有 70% 的初级保健代码在其初级保健记录中表明了 CH 居住地。中位住院时间为 272 天(IQR 63 至 480)。入院时平均年龄为 85 岁 (SD 8),多重剥夺指数中位数十分位五。 59% 的居民从入院起就需要护理服务。 79% 的人服用 5 种或更多药物。结论 使用地方当局数据提供了一种识别和描述 CH 居民特征的新方法。 将初级保健记录与地方当局数据联系起来,可以使用常规数据改进对 CH 居民的识别。与地址历史记录的附加链接将进一步提高准确性。
更新日期:2024-08-08
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