Content Design and System Implementation of a Teleophthalmology System for Eye Disease Diagnosis and Treatment and Its Preliminary Practice in Guangdong, China

Evaluating the Efficacy of Teleophthalmology in Delivering Ophthalmic Care to Underserved Populations: A Literature Review

Technological advancement has brought commendable changes in medicine, advancing diagnosis, treatment, and interventions. Telemedicine has been adopted by various subspecialties including ophthalmology. Over the years, teleophthalmology has been implemented in various countries, and continuous progress is being made in this area. In underserved populations, due to socioeconomic factors, there is little or no access to healthcare facilities, and people are at higher risk of eye diseases and vision impairment. Transportation is the major hurdle for these people in obtaining access to eye care in the main hospitals. There is a dire need for accessible eye care for such populations, and teleophthalmology is the ray of hope for providing eye care facilities to underserved people. Numerous studies have reported the advantages of teleophthalmology for rural populations such as being cost-effective, timesaving, reliable, efficient, and satisfactory for patients. Although it is being practiced in urban populations, for rural populations, its benefits amplify. However, there are certain obstacles as well, such as the cost of equipment, lack of steady electricity and internet supply in rural areas, and the attitude of people in certain regions toward acceptance of teleophthalmology. In this review, we have discussed in detail eye health in rural populations, teleophthalmology, and its effectiveness in rural populations of different countries.

Digital technology, tele-medicine and artificial intelligence in ophthalmology: A global perspective

The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology to adapt to new models of care using tele-health supported by digital innovations. These digital innovations include artificial intelligence (AI), 5th generation (5G) telecommunication networks and the Internet of Things (IoT), creating an inter-dependent ecosystem offering opportunities to develop new models of eye care addressing the challenges of COVID-19 and beyond. Ophthalmology has thrived in some of these areas partly due to its many image-based investigations. Tele-health and AI provide synchronous solutions to challenges facing ophthalmologists and healthcare providers worldwide. This article reviews how countries across the world have utilised these digital innovations to tackle diabetic retinopathy, retinopathy of prematurity, age-related macular degeneration, glaucoma, refractive error correction, cataract and other anterior segment disorders. The review summarises the digital strategies that countries are developing and discusses technologies that may increasingly enter the clinical workflow and processes of ophthalmologists. Furthermore as countries around the world have initiated a series of escalating containment and mitigation measures during the COVID-19 pandemic, the delivery of eye care services globally has been significantly impacted. As ophthalmic services adapt and form a "new normal", the rapid adoption of some of telehealth and digital innovation during the pandemic is also discussed. Finally, challenges for validation and clinical implementation are considered, as well as recommendations on future directions.

A systematic review of mobile health interventions in China: Identifying gaps in care

INTRODUCTION

Mobile health has a promising future in the healthcare system in most developed countries. China's rapidly developing mobile technology infrastructure offers an unprecedented opportunity for wide adoption of mobile health interventions in the delivery of effective and timely healthcare services. However, there is little data on the current extent of the mobile health landscape in China. The aim of this study was to systematically review the existing mobile health initiatives in China, characterise the technology used, disease categories targeted, location of the end user (urban versus rural), and examine the potential effects of mobile health on health system strengthening in China. Furthermore, we identified gaps in development and evaluation of the effectiveness of mobile health interventions.

METHODS

A systematic review of the literature published from 18 December 2015 - 3 April 2019 was conducted and yielded 2863 articles from English and Chinese retrieval database and trial registries, including PubMed, EMBASE, China National Knowledge of Infrastructure and World Health Organization International Clinical Trials Registry Platform. Studies were included if they used mobile health to support patient healthcare outcomes.

RESULTS

A total of 1129 full-text articles were assessed and 338 were included in this study. The review found that most studies targeted client education and behaviour change via applications (apps) (65.4%), including WeChat, and text messaging (short text messages) (19.8%) to improve patient medical treatment outcomes such as compliance and appointment reminders. The most common disease-specific mobile health interventions focused primarily on chronic disease management and behaviour change in cardiology (13.3%), endocrinology/diabetes (12.1%), behavioural health (11.8%), oncology (11.2%) and neurology (6.8%). The mobile health interventions related to nutrition (0.6%) and chronic respiratory diseases (1.6%) are underrepresented in mobile health in comparison to the burden of disease in China. The majority (90.0%) of the mobile health interventions were conducted exclusively in urban areas, with few opportunities reaching rural populations.

CONCLUSIONS

Overall, mobile health has a promising future in China, with recent rapid growth in initiatives. The majority are focused on education and behaviour change in the realm of chronic diseases and target patients in urban areas. The imbalance in mobile health between the urban and rural areas, as well as between population disease spectrum and health service delivery, pose substantial dilemmas. However, mobile health may be redirected to correct this imbalance, possibly improving access to healthcare services, and filling the gaps in order to improve health equity for the underserved populations in China.

Multivariable Logistic Regression And Back Propagation Artificial Neural Network To Predict Diabetic Retinopathy

BACKGROUND

Monitoring and prediction of diabetic retinopathy (DR) is necessary in patients with diabetes for early discovery and timely treatment of disease. We aimed to analyze the association between DR and biochemical and metabolic parameters, and develop a predictive model for DR.

METHODS

A total of 530 Chinese residents including 423 with type 2 diabetes (T2D) aged 18 years or older participated in this study. The association between DR and biochemical and metabolic parameters was analyzed by the univariate and multivariable logistic regression (MLR). According to the MLR results, we developed a back propagation artificial neural network (BP-ANN) model by selecting tan-sigmoid as the transfer function of the hidden layers nodes, and pure-line of the output layer nodes, with training goal of 0.5×10^-5.

RESULTS

There were 51 (9.6%) diabetic participants with DR. After univariate and MLR analysis, duration of diabetes, waist to hip ratio, HbA₁c and family history of diabetes were independently associated with the presence of DR (all P < 0.05). Based on these parameters, the area under the receiver operating characteristic (ROC) curve for the BP-ANN model was significantly higher than that by MLR (0.84 vs. 0.77, P < 0.001).

CONCLUSION

Our evaluation demonstrated the potential role of BP-ANN model to identify DR in screening practice. The presence of DR was well predictable using the proposed BP-ANN model based on four related parameters (duration of diabetes, waist to hip ratio, HbA₁c and family history of diabetes).