COVID-19大流行期间美国种族和少数民族中基于视频的远程医疗使用模式及其相关因素:一项混合方法范围审查

IF 7.7
PLOS digital health Pub Date : 2025-07-24 eCollection Date: 2025-07-01 DOI:10.1371/journal.pdig.0000952
John M Meddar, Ratnalekha V N Viswanadham, Defne L Levine, Tiffany R Martinez, Kendra Willis, Noah Choi, Jackson Douglas, Katharine S Lawrence
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引用次数: 0

摘要

2019冠状病毒病大流行促进了远程医疗在美国的迅速扩张,扩大了对视频服务的获取,但也引发了对少数群体公平获取、使用和体验的担忧。这项混合方法范围审查定量描述了基于视频的远程医疗利用模式,并定性评估了在COVID-19大流行期间影响美国种族/少数民族使用的因素。我们对6个数据库进行了全面的文献检索,检索了2020年1月至2023年3月期间发表的研究。符合条件的研究报告了远程保健或远程医疗的使用情况,特别是种族/族裔少数群体利用视频就诊的情况。审稿人独立筛选研究,提取数据,并使用综合混合方法综合研究结果。在1801项研究中,77项研究符合纳入标准。其中,大多数是在大都市沿海地区发表的,并且大多数在远程医疗的定义和利用方面存在差异。在数量上,33项研究(42.9%)报告了基于视频的远程医疗的使用增加,29项研究(37.7%)报告了使用减少,15项研究(20%)报告了不同种族/民族亚群的不同使用情况。大多数研究评估了非西班牙裔黑人和西班牙裔/拉丁裔人群之间的差异(分别为73和66项研究),而较少研究其他少数民族人群之间的差异(45项研究)。与采用远程医疗相关的因素包括患者和社区一级的数字访问障碍、组织数字能力和基础设施不足、隐性偏见以及提供者教育和培训不足。确定的促进因素包括对远程医疗的信任和认识、适当的提供者培训、文化和语言适应、有针对性的互联网补贴以及远程医疗报销。在COVID-19大流行期间,种族/少数民族基于视频的远程医疗利用具有异质性,受个人、系统和实施因素的影响。这种差异在亚裔和其他少数族裔人群中最为明显。尽管越来越多的人关注和努力解决获取障碍,但我们的研究结果强调,需要更有针对性、根据文化和结构量身定制的干预措施,以改善数字包容。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Video-based telemedicine utilization patterns and associated factors among racial and ethnic minorities in the United States during the COVID-19 pandemic: A mixed-methods scoping review.

Video-based telemedicine utilization patterns and associated factors among racial and ethnic minorities in the United States during the COVID-19 pandemic: A mixed-methods scoping review.

Video-based telemedicine utilization patterns and associated factors among racial and ethnic minorities in the United States during the COVID-19 pandemic: A mixed-methods scoping review.

Video-based telemedicine utilization patterns and associated factors among racial and ethnic minorities in the United States during the COVID-19 pandemic: A mixed-methods scoping review.

The COVID-19 pandemic catalyzed a rapid expansion of telemedicine across the United States, expanding access to video-based services but also raising concerns about equitable access, use, and experience among minority populations. This mixed-methods scoping review quantitatively describes patterns of video-based telemedicine utilization and qualitatively evaluates factors impacting utilization among racial/ethnic minorities in the United States during the COVID-19 pandemic. We conducted a comprehensive literature search across six databases for studies published between January 2020 and March 2023. Eligible studies reported on telehealth or telemedicine use, specifically video-based visit utilization among racial/ethnic minorities. Reviewers independently screened studies, extracted data, and synthesized findings using an integrated mixed-methods approach. Of 1801 studies, 77 studies met the inclusion criteria. Of these, a majority were published in metropolitan coastal areas, and most were heterogeneous in their definition of telemedicine and utilization. Quantitatively, 33 studies (42.9%) reported increased use of video-based telemedicine, 29 (37.7%) reported decreased use, and 15 (20%) reported variable use across racial/ethnic subgroups. Most studies assessed disparities among non-Hispanic Black and Hispanic/Latinx populations (73 and 66 studies, respectively), while fewer examined disparities among other minority populations (45 studies). Factors associated with telemedicine adoption included patient- and community-level digital access barriers, low organizational digital capacity and infrastructure, implicit bias, and inadequate provider education and training. Identified facilitators included trust and awareness of telemedicine, adequate provider training, cultural and linguistic adaptations, targeted internet subsidies, and telemedicine reimbursements. Video-based telemedicine utilization among racial/ethnic minorities during the COVID-19 pandemic was heterogeneous, influenced by individual, systemic, and implementation factors. Disparities were most pronounced among Asians and other minority populations. Despite increased attention and efforts to address access barriers, our findings highlight the need for more targeted, culturally and structurally tailored interventions to improve digital inclusion.

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