2019冠状病毒病大流行对2000年至2021年威尔士常规电子健康记录中确定的长期疾病记录发病率趋势的影响:一项人口数据联系研究。

IF 1.6 Q3 HEALTH CARE SCIENCES & SERVICES
Cathy Qi, T. Osborne, R. Bailey, J. Hollinghurst, A. Akbari, A. Cooper, Ruth Crowder, H. Peters, R. Law, Anthony Davies, R. Lewis, Mark C Walker, Adrian Edwards, R. Lyons
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引用次数: 0

摘要

新冠肺炎疫情导致癌症患者的诊断和治疗延迟,择期手术等待名单增加。对其他“长期”状况(ltc)的影响尚不清楚。我们研究了大流行对20例LTCs记录发病率的影响,为治疗途径和资源分配决策提供信息。我们纳入了2000年至2021年间首次被诊断患有20种LTCs中的任何一种的威尔士居民。数据在安全匿名信息链接(SAIL)数据库中被访问和分析。主要目的是评估COVID-19大流行对记录发病率趋势的影响。其次,我们检查了社会人口统计学和临床亚组的发病率:年龄、性别、剥夺五分之一、种族、虚弱评分和学习障碍。发病率以每个LTC的月发病率表示。我们进行了中断时间序列分析来估计;大流行后发病率的近期和长期变化;以及未确诊人群的规模。结果:我们纳入了2,206,070名被诊断为至少一种LTC的个体。2020年4月,所有20个长期诊断中心的新诊断记录立即减少,随后在接下来的18个月里逐渐恢复到大流行前的水平,尽管不同条件下的恢复速度不同。2020年1月至2021年6月期间观察到的发病率与预期发病率(根据大流行前趋势预测)之间的最大差异是慢性阻塞性肺病(-43%,95%可信区间(-50%,-34%))、哮喘、高血压和抑郁症的诊断,差异最小的是1型糖尿病、痴呆、中风和TIA(-8%, 95%可信区间(-19%,5%))。还分析了在大流行前后几年中社会人口和临床亚组发病率的差异(结果有待最后确定)。结论:2020年3月之后,所有20例LTCs的观察发病率突然下降,随后几个月逐渐恢复到大流行前的水平。在20个LTCs中,有15个强烈表明存在尚未确诊的患者。这项研究的结果将对资源分配产生影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The impact of COVID-19 pandemic on trends in the recorded incidence of Long-Term Conditions identified from routine electronic health records between 2000 and 2021 in Wales: a population data linkage study.
BackgroundThe COVID-19 pandemic has resulted in delayed diagnosis and treatment for cancer patients and increases in elective surgery waiting lists. The impact on other ‘long-term’ conditions (LTCs) is unclear. We examined the effects of the pandemic on the recorded incidence of 20 LTCs to inform decisions on treatment pathways and resource allocation. ApproachWe included Welsh residents diagnosed with any of 20 LTCs for the first time between 2000-2021. Data were accessed and analysed within the Secure Anonymised Information Linkage (SAIL) Databank. The primary aim was to assess the impact of the COVID-19 pandemic on trends in recorded incidence. Secondarily we examined incidence by socio-demographic and clinical subgroups: age, sex, deprivation quintile, ethnicity, frailty score and learning disability. Incidence were presented as monthly rates for each LTC. We performed interrupted time series analyses to estimate; the immediate and long-term change in rates following the pandemic; and the size of the undiagnosed population. ResultsWe included 2,206,070 individuals diagnosed with at least one LTC. An immediate reduction in recording of new diagnoses was observed in April 2020 across all 20 LTCs, followed by a gradual recovery towards pre-pandemic levels over the next 18 months, though at different rates across conditions. The largest difference between observed and expected (as predicted using pre-pandemic trends) incidence between January 2020 and June 2021 were in the diagnoses of COPD (-43%, 95% CI (-50%, -34%)), Asthma, Hypertension and Depression and the smallest difference was in Type 1 diabetes, dementia, stroke and TIA (-8%, 95% CI (-19% ,5%)). Differences in the proportions of incidence by socio-demographic and clinical subgroups in the years preceding and following the pandemic have also been analysed (results to be finalised). ConclusionThere was an abrupt reduction in the observed incidence of all 20 LTCs after March 2020 followed by a gradual recovery over consequent months towards pre-pandemic levels. Of 20 LTCs, 15 strongly indicate a reservoir of yet undiagnosed patients. The results from this study will have implications in resource allocation.
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CiteScore
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