2018年至2022年剑桥郡、彼得伯勒和西萨福克地区国家腹主动脉瘤筛查项目缺席率的时空分析及其与社会经济剥夺的关系

KW Fung, M Szybka, T Lane, S Kreckler
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引用次数: 0

摘要

目的:不参加国家腹主动脉瘤筛查计划(NAAASP)筛查扫描导致失去了改善公众健康的机会,并对整个医疗保健系统产生了财务影响。本研究旨在评估“未就诊”(DNA)率的时空分布,确定高风险地理区域和相关风险因素,为未来的政策制定和医疗资源分配提供参考。方法:回顾性分析2018年至2022年剑桥郡、彼得伯勒和西萨福克地区未参加NAAASP的时空。利用国家AAA筛查系统筛选管理和转诊跟踪(SMaRT)的数据,建立每个邮编地区的DNA率,并与总体DNA率进行比较。利用每个邮编地区的“非出席者”数量,进行了优化的热点分析,以确定2018年至2022年间每年的非出席热点。多元逻辑回归研究剥夺程度与缺勤之间的关系。结果:总体而言,从2018年到2022年,23,957人中有6,364人(26.6%)没有参加筛查。优化的热点分析确定了8个统计上显著的不出勤热点。邮政编码区PE10 (n=8, 80%)、PE1 (n=433, 44.5%)、CB4 (n=331, 40.2%)、CB3 (n=114, 36.7%)和CB1 (n=320, 35.8%)是DNA率较高的地区。PE1, CB1, CB3和CB4是高DNA率和高非参与者数量的高风险区域。在2020/21年,热点的空间格局保持一致,但DNA率明显下降。在彼得伯勒,贫困程度与缺勤密切相关,而在社会经济贫困程度较低的剑桥,这种联系不那么明显。结论:PE1、CB1、CB3、CB4为高危邮编。这些地区占接受筛查人口总数的12.6%。被剥夺的程度被发现是导致缺勤的一个主要因素。将资源集中用于设法改善这些群体的出勤率,应是比针对全体人口更具成本效益的办法。未来的研究需要探索与这些邮编地区高缺勤率相关的风险因素,以确定改善接受和获得筛查服务的行动。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatio-temporal analysis of non-attendance for the National Abdominal Aortic Aneurysm Screening Program in Cambridgeshire, Peterborough and West Suffolk region between 2018 and 2022 and its link to socioeconomic deprivation
Objective: Non-attendance for National Abdominal Aortic Aneurysm Screening Program (NAAASP) screening scans results in a lost opportunity to improve public health and has financial implications for the healthcare system as a whole. This study aimed to assess the spatio-temporal distribution of the ‘did-not-attend’ (DNA) rate and identify high-risk geographical areas and associated risk factors for future policy making and allocation of healthcare resources. Methods: This was a retrospective spatio-temporal analysis of non-attendance to the NAAASP in Cambridgeshire, Peterborough and West Suffolk from 2018 to 2022. With the data from the national AAA screening system, Screening Management and Referral Tracking (SMaRT), the DNA rate was established for each postcode district and compared with the overall DNA rate. Using the number of ‘non-attenders’ in each postcode district, optimised hotspot analysis was performed to identify hotspots of non-attendance for each year between 2018 and 2022. Multiple logistic regression was used to investigate the association between degree of deprivation and non-attendance. Results: Overall, 6,364 of 23,957 people (26.6%) being called for screening did not attend from 2018 to 2022. Optimised hotspot analysis identified eight statistically significant hotspots of non-attendance. Postcode districts PE10 (n=8, 80%), PE1 (n=433, 44.5%), CB4 (n=331, 40.2%), CB3 (n=114, 36.7%) and CB1 (n=320, 35.8%) were identified as areas with statistically significantly higher DNA rates. PE1, CB1, CB3 and CB4 were high-risk areas with both high DNA rates and high numbers of non-attenders. A consistent spatial pattern of hotspots was observed while there was a significant drop in the DNA rate in 2020/21. While degree of deprivation was closely linked to non-attendance in Peterborough, the link was less obvious in Cambridge with little socioeconomic deprivation. Conclusion: PE1, CB1, CB3 and CB4 were identified as high-risk postcodes. These areas comprise 12.6% of the total screened population. The degree of deprivation is found to be a major contributing factor to non-attendance. Focusing resources to try and improve attendance in these cohorts should be a more cost-effective approach than targeting the population as a whole. Future research is needed to explore the risk factors associated with high non-attendance in these postcode districts in order to identify actions to improve uptake and access to the screening services.
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