Pandemic Disruptions of Atrial Fibrillation Care

项目摘要 房颤(房颤)是一种心律失常，在美国有500多万人受到影响，是美国的五倍 中风的风险。房颤是衡量新冠肺炎大流行对非冠状病毒影响的关键疾病状态 疾病，因为在房颤中预防中风的每一个方面都容易受到干扰：1)新发病的患者 房颤可能更容易得不到诊断。2)已确诊的房颤患者可能会有遗留的并发症 未被发现并在不治疗的情况下恶化。3)新诊断为房颤的患者可能不太可能启动 口服抗凝(OAC)预防中风治疗。4)现有的OAC用户可能有所增加 坚持治疗有困难。5)服用华法林(一种需要常规血液测试的OAC制剂)的患者可以 不那么频繁地进行监控。 我们的目标是衡量新冠肺炎大流行对诊断、治疗启动、治疗 房颤患者的依从性、监测和健康结局。我们将确定大流行是否会 房颤护理的中断加剧了健康差距。我们还将评估远程医疗的作用，其 这场大流行促进了疫情的蔓延，抵消了危机期间获得面对面护理机会减少的影响。 我们将使用2015-2022年的联邦医疗保险服务费受益人索赔数据和Optom®集成索赔数据- 商业保险和联邦医疗保险优势受益人的电子健康记录数据。我们将建造 中断的时间序列分析，以衡量大流行开始和大流行结束后结果的变化。至 确定大流行是否加剧了差距，我们将测试变化的程度 结果因年龄、性别、种族/民族和地区层面的城市化衡量标准、社会经济地位、 剥夺、种族构成和种族隔离。在目标3和4中，我们将使用边际结构模型来 评估远程医疗访问与结果之间的关联。我们将实现四个具体目标： (1)量化2016-2021年房颤新诊断发病率的变化，包括新的房颤诊断 表现为中风；(2)确定新冠肺炎大流行是否与OAC下降有关 在新诊断的房颤患者中启动；(3)量化OAC依从性和监测的变化 在已确定的房颤患者中进行治疗；(4)量化中风、出血、 已确诊的房颤患者的心血管住院和死亡。 我们对大流行对房颤护理影响的量化将对提供慢性 紧急情况下的疾病护理。我们对受疫情影响不成比例的人群的识别 我们对远程医疗抵消面对面护理机会减少的能力的确定将提供信息 临床指导和政策，防止在卫生紧急情况下逃避护理，优化模型 在重大危机期间提供慢性病护理，并保护弱势群体。

Project Summary Atrial fibrillation (AF) is a cardiac arrythmia that affects over 5 million individuals in the US and quintuples the risk of stroke. AF is a critical disease state to measure the effects of the COVID-19 pandemic on non-COVID disease because every aspect of stroke prevention in AF is vulnerable to disruption: 1) Patients with new onset AF may be more likely to remain undiagnosed. 2) Established AF patients may have complications that remain undetected and worsen without treatment. 3) Patients newly diagnosed with AF may be less likely to initiate stroke prevention therapy with oral anticoagulation (OAC). 4) Established OAC users may have increased difficulty adhering to therapy. 5) Patients on warfarin, an OAC agent that requires routine blood tests, may have less frequent monitoring. Our goal is to measure the impact of the COVID-19 pandemic on diagnosis, therapy initiation, therapy adherence, monitoring, and health outcomes for patients with AF. We will determine whether pandemic disruptions of AF care have exacerbated health disparities. We will also assess the role of telemedicine, whose uptake has been catalyzed by the pandemic, in offsetting decreased access to in-person care during crises. We will use 2015-2022 claims data for Medicare fee-for-service beneficiaries and Optum® Integrated claims- electronic health record data for commercially insured and Medicare Advantage beneficiaries. We will construct interrupted time series analyses to measure changes in outcomes after pandemic start and pandemic end. To determine whether the pandemic has exacerbated disparities, we will test whether the degree of change in outcomes differed by age, sex, race/ethnicity, and area-level measures of urbanization, socioeconomic status, deprivation, racial composition, and segregation. In aims 3 and 4, we will use marginal structural models to estimate the association between telehealth visits and outcomes. We will achieve four specific aims: (1) quantify changes in the incidence rate of new AF diagnoses in 2016-2021, including new AF diagnoses manifesting as stroke; (2) determine whether the COVID-19 pandemic was associated with decreased OAC initiation among newly diagnosed AF patients; (3) quantify changes in adherence and monitoring of OAC therapy among established AF patients; (4) quantify changes in the incidence rates of stroke, bleeding, cardiovascular hospitalization, and death among established AF patients. Our quantification of pandemic effects on AF care will have major implications for the provision of chronic disease care during emergencies. Our identification of populations disproportionately affected by the pandemic and our determination of the ability of telemedicine to offset decreased access to in-person care will inform clinical guidance and policies that prevent care avoidance during health emergencies, optimize models for the delivery of chronic disease care during major crises, and protect vulnerable populations.