Labkovich Margarita, Paul Megan, Kim Eliott, A Serafini Randal, Lakhtakia Shreyas, Valliani Aly A, Warburton Andrew J, Patel Aashay, Zhou Davis, Sklar Bonnie, Chelnis James, Elahi Ebrahim
Department of Medical Education, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Nash Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Digit Health. 2022 May 6;8:20552076221090042. doi: 10.1177/20552076221090042. eCollection 2022 Jan-Dec.
Vision impairment continues to be a major global problem, as the WHO estimates 2.2 billion people struggling with vision loss or blindness. One billion of these cases, however, can be prevented by expanding diagnostic capabilities. Direct global healthcare costs associated with these conditions totaled $255 billion in 2010, with a rapid upward projection to $294 billion in 2020. Accordingly, WHO proposed 2030 targets to enhance integration and patient-centered vision care by expanding refractive error and cataract worldwide coverage. Due to the limitations in cost and portability of adapted vision screening models, there is a clear need for new, more accessible vision testing tools in vision care. This comparative, systematic review highlights the need for new ophthalmic equipment and approaches while looking at existing and emerging technologies that could expand the capacity for disease identification and access to diagnostic tools. Specifically, the review focuses on portable hardware- and software-centered strategies that can be deployed in remote locations for detection of ophthalmic conditions and refractive error. Advancements in portable hardware, automated software screening tools, and big data-centric analytics, including machine learning, may provide an avenue for improving ophthalmic healthcare.
视力障碍仍然是一个重大的全球问题,据世界卫生组织估计,有22亿人正遭受视力丧失或失明的困扰。然而,其中10亿例病例可通过扩大诊断能力来预防。2010年,与这些病症相关的全球直接医疗费用总计2550亿美元,预计到2020年将迅速上升至2940亿美元。因此,世界卫生组织提出了2030年目标,通过扩大全球屈光不正和白内障的覆盖范围,加强以患者为中心的视力保健整合。由于适应性视力筛查模型在成本和便携性方面存在局限性,视力保健领域显然需要新的、更易于使用的视力检测工具。这项比较性的系统综述强调了对新的眼科设备和方法的需求,同时审视了现有和新兴技术,这些技术可以扩大疾病识别能力和诊断工具的可及性。具体而言,该综述侧重于以便携式硬件和软件为中心的策略,这些策略可部署在偏远地区,用于检测眼科疾病和屈光不正。便携式硬件、自动化软件筛查工具以及以大数据为中心的分析(包括机器学习)的进步,可能为改善眼科医疗保健提供一条途径。