Smartphone-based community screening for eye disease in rural India

印度农村地区基于智能手机的眼病社区筛查

• 批准号: 10527058
• 负责人: Kunal S Parikh
• 金额: $ 20.74万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-30 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10527058
• 关键词: Algorithms; Anterior; Anterior eyeball segment structure; Artificial Intelligence; Award; Biomedical Engineering; Biometry; Blindness; Calendar; Caring; Cataract; Cellular Phone; Clinical Data; Collaborations; Communities; Community Health Aides; Computer software; Continuity of Patient Care; Corneal Opacity; Data; Data Collection; Data Set; Decentralization; Dependence; Development; Devices; Diagnosis; Diagnostic; Disease; Ensure; Epidemiology; Equipment; Eye; Eye diseases; Failure; Geography; Gold; Health; Health Technology; Health system; Healthcare; Hospitals; Human Resources; Image; Improve Access; India; Information Technology; Infrastructure; Intervention; Machine Learning; Modeling; Ophthalmic examination and evaluation; Ophthalmologist; Ophthalmology; Outcome; Patients; Pattern; Performance; Periodicity; Persons; Phase; Public Health Practice; Quality Control; Refractive Errors; Research; Research Personnel; Resource-limited setting; Rural; Specialist; Standardization; System; Time; Training; Translating; Universities; Validation; Visually Impaired Persons; Vulnerable Populations; acceptability and feasibility; algorithm training; base; biomedical referral center; blind; care delivery; care providers; collaborative trial; cost; cost effectiveness; deep neural network; design; effectiveness evaluation; follow-up; innovative technologies; interoperability; low and middle-income countries; mHealth; machine learning algorithm; member; novel; patient screening; prototype; remote communities; remote grading; rural patients; rural setting; screening; skills; user centered design; user-friendly

PROJECT SUMMARY This is an application for an R21/R33 award titled “Smartphone-based community screening of anterior eye diseases in rural India.” The investigators from Johns Hopkins University and Aravind Eye Hospital have diverse expertise in ophthalmology, biomedical engineering, machine learning, epidemiology, biostatistics, and use of mobile health technology in low-resource settings. 90% of the world’s 275 million blind and visually impaired people live in low- and middle-income countries (LMICs). Cataract, refractive error, corneal opacities, and other anterior eye diseases account for the majority of global blindness. In rural LMIC settings, lack of access to highly trained eye care providers such as ophthalmologists is a key barrier to timely diagnosis and treatment for anterior eye diseases. Periodic “eye camp” screenings performed by highly trained ophthalmologists have been the mainstay of rural eye disease screening for many decades but have several limitations including lack of access to trained ophthalmologists, failure to reach the most remote communities, lack of consistent calendar coverage beyond eye camp dates, and high costs due to equipment, personnel, and community publicity. We propose development, validation, and implementation of a novel smartphone based device for community health worker (CHW)-led screening, diagnosis, and referral for eye diseases in rural LMIC settings. We will develop this smartphone platform using iterative prototyping and user-centered design approaches. After demonstrating feasibility, we will evaluate the diagnostic validity of CHW-led screenings using the smartphone platform compared to traditional in-person eye camp exams by an ophthalmologist. After collecting sufficient data and images using the platform, we will design, validate, and implement machine learning algorithms to permit real- time diagnosis and referral decisions by CHWs without dependence on ophthalmologists. This project will perform detailed data collection regarding referral patterns, loss to follow-up, cost-effectiveness, and differential outcomes among vulnerable groups in order to enable more targeted health interventions. This project is intended to overcome key longstanding geographic, financial, operational, and human resource constraints to eye screening while ensuring diagnostic validity, quality control, and interoperability with existing health system infrastructure. Our scalable approach has potential to transform global eye care delivery in low-resource settings. This collaboration will also result in permanent improvements in mobile health and research capacity at Aravind Eye Hospital.

项目总结