College of Software Engineering, Southeast University, Nanjing, China.
TerryDr Infomation Technology, Nanjing, China.
JMIR Mhealth Uhealth. 2020 Jul 13;8(7):e18226. doi: 10.2196/18226.
Young children's vision screening, as part of a preventative health care service, produces great value for developing regions. Besides yielding a high return on investment from forestalling surgeries using a low-cost intervention at a young age, it improves school performance and thus boosts future labor force quality. Leveraging low-skilled health care workers with smartphones and automated diagnosis to offer such programs can be a scalable model in resource-limited areas.
This study aimed to develop and evaluate an effective, efficient, and comprehensive vision screening solution for school children in resource-limited areas. First, such an exam would need to cover the major risk factors of amblyopia and myopia, 2 major sources of vision impairment effectively preventable at a young age. Second, the solution must be integrated with digital patient record-keeping for long-term monitoring and popular statistical analysis. Last, it should utilize low-skilled technicians and only low-cost tools that are available in a typical school in developing regions, without compromising quality or efficiency.
A workflow for the screening program was designed and a smartphone app was developed to implement it. In the standardized screening procedure, a young child went through the smartphone-based photoscreening in a dark room. The child held a smartphone in front of their forehead, displaying pre-entered personal information as a quick response code that duplexed as a reference of scale. In one 10-second procedure, the child's personal information and interpupillary distance, relative visual axis alignment, and refractive error ranges were measured and analyzed automatically using image processing and artificial intelligence algorithms. The child's risk for strabismus, myopia, and anisometropia was then derived and consultation given.
A preliminary evaluation of the solution was conducted alongside yearly physical exams in Luoyang, Henan, People's Republic of China. It covered 20 students with suspected strabismus and 80 randomly selected students, aged evenly between 8 and 10. Each examinee took about 1 minute, and a streamlined workflow allowed 3 exams to run in parallel. The 1-shot and 2-shot measurement success rates were 87% and 100%, respectively. The sensitivity and specificity of strabismus detection were 0.80 and 0.98, respectively. The sensitivity and specificity of myopia detection were 0.83 and 1.00, respectively. The sensitivity and specificity of anisometropia detection were 0.80 and 1.00, respectively.
The proposed vision screening program is effective, efficient, and scalable. Compared with previously published studies on utilizing a smartphone for an automated Hirschberg test and photorefraction screening, this comprehensive solution is optimized for practicality and robustness, and is thus better ready-to-deploy. Our evaluation validated the achievement of the program's design specifications.
儿童视力筛查作为预防保健服务的一部分,对发展中地区具有重要价值。除了通过在年幼时进行低成本干预来预防手术以获得高投资回报外,它还可以提高学习成绩,从而提高未来劳动力的质量。在资源有限的地区,利用智能手机和自动化诊断的低技能医疗保健工作者来提供此类服务可以是一种具有可扩展性的模式。
本研究旨在为资源有限地区的学童开发和评估一种有效、高效和全面的视力筛查解决方案。首先,这样的检查需要涵盖弱视和近视的主要风险因素,这是两种可以在年幼时有效预防的主要视力损害来源。其次,该解决方案必须与数字患者病历记录相结合,以进行长期监测和流行的统计分析。最后,它应该利用低技能技术人员和仅在发展中地区的典型学校中可用的低成本工具,而不会降低质量或效率。
设计了筛查程序的工作流程,并开发了一个智能手机应用程序来实施该流程。在标准化的筛查程序中,一个小孩在暗室中通过基于智能手机的照片筛查。孩子将智能手机举到前额前,显示预先输入的个人信息作为快速响应代码,该代码同时作为比例尺的参考。在一个 10 秒的程序中,孩子的个人信息和瞳孔间距离、相对视轴对齐以及屈光不正范围会自动使用图像处理和人工智能算法进行测量和分析。然后,根据孩子的斜视、近视和屈光参差风险进行咨询。
对该解决方案进行了初步评估,同时在中国河南省洛阳市进行了年度体检。它涵盖了 20 名疑似斜视的学生和 80 名随机选择的年龄在 8 至 10 岁之间的学生。每位受检者大约需要 1 分钟,简化的工作流程允许同时进行 3 次检查。单次拍摄和两次拍摄的测量成功率分别为 87%和 100%。斜视检测的灵敏度和特异性分别为 0.80 和 0.98。近视检测的灵敏度和特异性分别为 0.83 和 1.00。屈光参差检测的灵敏度和特异性分别为 0.80 和 1.00。
提出的视力筛查方案是有效、高效且可扩展的。与之前利用智能手机进行自动化 Hirschberg 测试和视网膜折射筛查的研究相比,该综合解决方案针对实用性和稳健性进行了优化,因此更易于部署。我们的评估验证了该方案设计规格的实现。