Devraj Kishan, Jones Lee, Higgins Bethany, Thomas Peter B M, Moosajee Mariya
Institute of Ophthalmology, University College London, London EC1V 9EL, UK.
Moorfields Eye Hospital NHS Foundation Trust, London EC1V 2PD, UK.
Healthcare (Basel). 2024 Dec 18;12(24):2550. doi: 10.3390/healthcare12242550.
Visual impairment can significantly impact an individual's daily activities. Patients require regular monitoring, typically occurring within hospital eye services. Capacity constraints have necessitated innovative solutions to improve patient care. Existing digital solutions rely on task-based digital home monitoring such as visual acuity testing. These require active involvement from patients and do not typically offer an indication of quality of life. Digital phenotyping refers to the use of personal digital devices to quantify passive behaviour for detecting clinically significant changes in vision and act as biomarkers for disease. Its uniqueness lies in the ability to detect changes passively. The objective was to co-design an accessible smartphone app () for the purposes of digital phenotyping in people with sight impairment.
Development of included stakeholder consultations following principles of user-centred design. Apple iOS software frameworks (HealthKit, ResearchKit, and SensorKit) and a SwiftUI developer toolkit were used to enable the collection of active and passive data streams. Accessibility and usability were assessed using the System Usability Scale (SUS) and feedback following a 3-month pilot study. Consultations with patients informed the design of , including preferred survey scheduling and the relevancy of patient support resources.
Twenty visually impaired participants (mean age 42 ± 19 years) were recruited to the pilot study. The average score on the SUS was 76.8 (±8.9), indicating good usability. There was a statistically significant moderate negative correlation between SUS scores and visual acuity in both the better (r = -0.494; ≤ 0.001) and worse eye (r = -0.421; ≤ 0.001).
offers promising potential for collecting patient-generated health data for the purposes of digital phenotyping in patients with eye disease. Through further testing and validation, this novel approach to patient care may ultimately provide opportunities for remote monitoring in ophthalmology.
视力障碍会对个人日常活动产生重大影响。患者需要定期监测，通常在医院眼科服务中进行。由于能力限制，需要创新解决方案来改善患者护理。现有的数字解决方案依赖于基于任务的数字家庭监测，如视力测试。这些需要患者积极参与，并且通常不能提供生活质量指标。数字表型分析是指使用个人数字设备量化被动行为，以检测视力的临床显著变化，并作为疾病的生物标志物。其独特之处在于能够被动检测变化。目的是共同设计一款可访问的智能手机应用程序（），用于视力障碍患者的数字表型分析。
的开发包括遵循以用户为中心设计原则的利益相关者咨询。使用苹果iOS软件框架（HealthKit、ResearchKit和SensorKit）以及SwiftUI开发者工具包来收集主动和被动数据流。使用系统可用性量表（SUS）以及为期3个月的试点研究后的反馈来评估可访问性和可用性。与患者协商为的设计提供了信息，包括首选的调查安排和患者支持资源的相关性。
20名视力障碍参与者（平均年龄42±19岁）被招募到试点研究中。SUS的平均得分是76.8（±8.9），表明可用性良好。在较好眼（r = -0.494；≤0.001）和较差眼（r = -0.421；≤0.001）中，SUS得分与视力之间均存在统计学上显著的中度负相关。
为收集眼病患者数字表型分析的患者生成健康数据提供了有前景的潜力。通过进一步测试和验证，这种新颖的患者护理方法最终可能为眼科远程监测提供机会。
