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与美国医疗保健差距相关的人口统计学问题因 COVID-19 大流行期间远程医疗的激增而加剧。

Demographics associated with US healthcare disparities are exacerbated by the telemedicine surge during the COVID-19 pandemic.

机构信息

University of Miami Miller School of Medicine, USA.

Department of Otolaryngology, University of Miami Miller School of Medicine, USA.

出版信息

J Telemed Telecare. 2024 Jan;30(1):64-71. doi: 10.1177/1357633X211025939. Epub 2021 Jun 23.

Abstract

INTRODUCTION

As coronavirus disease 2019 (COVID-19) hit the US, there was widespread and urgent implementation of telemedicine programs nationwide without much focus on the impact on patient populations with known existing healthcare disparities. To better understand which populations cannot access telemedicine during the coronavirus disease 2019 pandemic, this study aims to demographically describe and identify the most important demographic predictors of telemedicine visit completion in an urban health system.

METHODS

Patient de-identified demographics and telemedicine visit data ( = 362,764) between March 1, 2020 and October 31, 2020 were combined with Internal Revenue Service 2018 individual income tax data by postal code. Descriptive statistics and mixed effects logistic regression were used to determine impactful patient predictors of telemedicine completion, while adjusting for clustering at the clinical site level.

RESULTS

Many patient-specific demographics were found to be significant. Descriptive statistics showed older patients had lower rates of completion ( < 0.001). Also, Hispanic patients had statistically significant lower rates ( < 0.001). Overall, minorities (racial, ethnic, and language) had decreased odds ratios of successful telemedicine completion compared to the reference.

DISCUSSION

While telemedicine use continues to be critical during the coronavirus disease 2019 pandemic, entire populations struggle with access-possibly widening existing disparities. These results contribute large datasets with significant findings to the limited research on telemedicine access and can help guide us in improving telemedicine disparities across our health systems and on a wider scale.

摘要

简介

随着 2019 年冠状病毒病(COVID-19)袭击美国,全美各地广泛而紧急地实施远程医疗计划,但几乎没有关注对已经存在医疗保健差异的患者群体的影响。为了更好地了解在 2019 年冠状病毒病大流行期间哪些人群无法获得远程医疗服务,本研究旨在从人口统计学上描述和确定城市卫生系统中完成远程医疗就诊的最重要人口统计学预测因素。

方法

将患者匿名人口统计学数据和远程医疗就诊数据( = 362764)与 2018 年美国国内税务局个人所得税数据按邮政编码进行合并。使用描述性统计和混合效应逻辑回归来确定对远程医疗完成有影响的患者预测因素,同时调整临床站点级别的聚类。

结果

发现许多患者特定的人口统计学因素具有显著意义。描述性统计数据显示,年龄较大的患者完成率较低( < 0.001)。此外,西班牙裔患者的完成率也有统计学意义上的降低( < 0.001)。总体而言,少数民族(种族、民族和语言)与参考组相比,成功完成远程医疗的可能性降低。

讨论

虽然在 2019 年冠状病毒病大流行期间继续使用远程医疗至关重要,但整个群体在获得医疗服务方面都存在困难,这可能会扩大现有的差异。这些结果为远程医疗获取的有限研究提供了大量具有重要意义的数据集,并有助于指导我们改善我们的卫生系统和更广泛范围内的远程医疗差异。

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