Li Charles, Lum Flora, Chen Evan M, Collender Philip A, Head Jennifer R, Khurana Rahul N, Cunningham Emmett T, Moorthy Ramana S, Parke David W, McLeod Stephen D
American Academy of Ophthalmology, San Francisco, CA, USA.
Department of Ophthalmology, University of California, San Francisco, CA, USA.
Commun Med (Lond). 2023 Dec 14;3(1):181. doi: 10.1038/s43856-023-00416-4.
Healthcare restrictions during the COVID-19 pandemic, particularly in ophthalmology, led to a differential underutilization of care. An analytic approach is needed to characterize pandemic health services usage across many conditions.
A common analytical framework identified pandemic care utilization patterns across 261 ophthalmic diagnoses. Using a United States eye care registry, predictions of utilization expected without the pandemic were established for each diagnosis via models trained on pre-pandemic data. Pandemic effects on utilization were estimated by calculating deviations between observed and expected patient volumes from January 2020 to December 2021, with two sub-periods of focus: the hiatus (March-May 2020) and post-hiatus (June 2020-December 2021). Deviation patterns were analyzed using cluster analyses, data visualizations, and hypothesis testing.
Records from 44.62 million patients and 2455 practices show lasting reductions in ophthalmic care utilization, including visits for leading causes of visual impairment (age-related macular degeneration, diabetic retinopathy, cataract, glaucoma). Mean deviations among all diagnoses are 67% below expectation during the hiatus peak, and 13% post-hiatus. Less severe conditions experience greater utilization reductions, with heterogeneities across diagnosis categories and pandemic phases. Intense post-hiatus reductions occur among non-vision-threatening conditions or asymptomatic precursors of vision-threatening diseases. Many conditions with above-average post-hiatus utilization pose a risk for irreversible morbidity, such as emergent pediatric, retinal, or uveitic diseases.
We derive high-resolution insights on pandemic care utilization in the US from high-dimensional data using an analytical framework that can be applied to study healthcare disruptions in other settings and inform efforts to pinpoint unmet clinical needs.
2019冠状病毒病大流行期间的医疗保健限制措施,尤其是眼科领域的限制,导致了医疗服务利用的差异。需要一种分析方法来描述多种疾病的大流行期间医疗服务使用情况。
一个通用的分析框架确定了261种眼科诊断的大流行期间医疗利用模式。利用美国眼保健登记处的数据,通过基于大流行前数据训练的模型,为每种诊断建立了无大流行情况下预期利用情况的预测。通过计算2020年1月至2021年12月观察到的和预期的患者数量之间的偏差,估计大流行对利用的影响,重点关注两个子时期:中断期(2020年3月至5月)和中断期后(2020年6月至2021年12月)。使用聚类分析、数据可视化和假设检验分析偏差模式。
来自4462万名患者和2455家医疗机构的记录显示,眼科护理利用持续减少,包括因视力障碍主要原因(年龄相关性黄斑变性、糖尿病视网膜病变、白内障、青光眼)而进行的就诊。在中断期高峰时,所有诊断的平均偏差比预期低67%,在中断期后为13%。病情较轻的疾病利用减少幅度更大,不同诊断类别和大流行阶段存在异质性。在无视力威胁的疾病或视力威胁性疾病的无症状前驱疾病中,中断期后出现了大幅减少。许多中断期后利用率高于平均水平的疾病存在不可逆发病的风险,如儿童急症、视网膜疾病或葡萄膜炎疾病。
我们使用一个分析框架从高维数据中获得了关于美国大流行期间医疗利用的高分辨率见解,该框架可应用于研究其他环境中的医疗保健中断情况,并为确定未满足的临床需求提供信息。