Appalachian Node

项目总结/摘要 由SARS-CoV-2引起的COVID-19大流行导致了社交距离措施， 其后果，特别是与药物使用和药物过量死亡有关的后果尚不清楚。 新闻报道和早期研究表明，阿片类药物过量死亡人数增加。此外，大流行病 也改变了医学的实践方式，减少了面对面的访问， 远程医疗的发展缓慢。鉴于阿片类药物过量死亡在美国呈上升趋势， 阿片类药物使用障碍（MOUD）的药物在大流行之前就已经受到限制， 戒毒治疗现在比以往任何时候都更加紧迫。IQVIA纵向处方（IQVIA LRx）数据库 包含全国所有处方的92%，包括丁丙诺啡制剂。我们寻求 利用该数据库了解COVID-19相关社交距离措施的影响，MOUD 围绕远程医疗的监管变化，以及整个美国丁丙诺啡的失业率。 我们的第一个目标是了解几项政策变化如何影响丁丙诺啡的获得 在特定时间点发生的，包括实施社交距离措施和联邦 MOUD规定了与远程医疗相关的指南。我们将通过中断时间来实现这一点 采用分段回归分析系列，以了解丁丙诺啡 在特定时间点的访问和事件。我们的第二个目标是解决保险范围的影响 获得治疗。2020年3月至5月，美国至少有4000万人申请失业。 考虑到大多数拥有医疗保险的人都是通过雇主获得的，我们预计， 雇主提供的医疗保险覆盖面减少。因此，我们假设患者 与商业健康保险将有更多的中断，在他们访问MOUD，特别是 丁丙诺啡，与公共保险（医疗补助/医疗保险）的患者相比。这些发现将在 第一个描述COVID-19背景下MOUD处方变化的人。在随后的研究中， 我们将寻求利用额外的数据集来确定MOUD访问的变化之间的关系， 阿片类药物相关的发病率和死亡率结果，包括致死性和非致死性过量。了解这些 关系将告知MOUD处方的最佳实践，以减少患者在 流行病

Project Summary/Abstract The COVID-19 pandemic caused by SARS-CoV-2 has resulted in social distancing measures, the total consequences of which, particularly as they relate to substance use and drug overdose deaths, are unknown. News reports and early studies have suggested increases in opioid overdose deaths. In addition, the pandemic has also changed how medicine is practiced, with decreased face-to-face visits and a commensurate, albeit slower, rise in telemedicine. Given that opioid overdose deaths are on the rise in the United States and access to medications for opioid use disorder (MOUD) was already limited before the pandemic, ensuring access to addiction treatment is more urgent now than ever. The IQVIA Longitudinal Prescription (IQVIA LRx) database contains 92% of all prescriptions dispensed nationwide, including buprenorphine formulations. We seek to utilize this database to understand the impact of COVID-19-related social distancing measures, MOUD regulatory changes around telemedicine, and unemployment on access to buprenorphine across the entire US. Our first aim seeks to understand how access to buprenorphine was affected by several policy changes occurring at specific timepoints, including implementation of social distancing measures and changes in federal MOUD prescribing guidelines related to telemedicine. We will achieve this by conducting an interrupted time series with segmented regression analysis to understand the time-varying relationship between buprenorphine access and events at specific time points. Our second aim seeks to address the impact of insurance coverage on access to treatment. From March to May 2020, at least 40 million people filed for unemployment in the US. Given that most people with health insurance receive it through their employer, we anticipate significant reductions in access to employer-based health insurance coverage. As a result, we hypothesize that patients with commercial health insurance will have more disruptions in their access to MOUD, specifically buprenorphine, compared to patients with public insurance (Medicaid/Medicare). These findings will be among the first to characterize the changes to MOUD prescribing in the setting of COVID-19. In subsequent research, we will seek to utilize additional datasets to determine the relationship between changes in MOUD access and opioid-related morbidity and mortality outcomes, including fatal and nonfatal overdoses. Understanding these relationships will inform best practices for MOUD prescribing to reduce patient harm in the setting of a pandemic.