Hampshire Hospitals Director

Sloan Olsen

The World Health Organization (WHO) created a framework for the implementation of digital innovations and technology in healthcare. The WHO's recommendations for digital interventions in healthcare encourage evaluations based on "benefits, harms, acceptability, feasibility, resource use, and equitable considerations" viewsthese technologies as just that—tools in the quest to achieve universal health coverage and long-term sustainability for all (World Health Organisation, 2019). Particularly,modern healthcare IT (HIT) has immensely benefitted ophthalmologists to adapt to new models of care using telehealth supported by digital innovations. These breakthroughs includeartificial intelligence (AI), 5th generation (5G) communications networks, and the Internet of Things (IoT), offering opportunities to develop new eye care models that address several issues in the field of ophthalmology.

Over the last two years, retina specialists and their patients have learned how AI can help physicians better monitor their patients, how telemedicine could mean more than just a video chat between patients and their clinicians, and how 21st-century tools are closer to real-world practice than expected. Traditional ophthalmic illness diagnosis relies on clinical evaluation and, increasingly, image-capturing technologies of various modalities. This process is time-consuming and expensive and makes ophthalmology one among many specialties that areparticularly well-suited to deep learning(DL)techniques and their implementation in the real world. The automated screening and detection of common vision-threatening disorders, likediabetic retinopathy, has been reported using DL on ophthalmic pictures, such as digital fundus photographs and visual fields (DR), glaucoma, age-related macular degeneration (AMD), and retinopathy of prematurity (ROP). As a result, DL could be a valuable and feasible addition to existing diagnostic methods as an appropriate substitute for ophthalmologists and skilled human image graders.

Furthermore, new DL algorithms have recently been accepted for use on optical coherence tomography (OCT) pictures, which may improve the sensitivity of early diagnosis of diseases, particularly in AMD and DR with the detection of diabetic macular oedema. Although the cost-effectiveness of these systems is yet to be discovered, the integration of DL into ophthalmology practice is likely to revolutionize the present disease management process, enhance early detection, and, eventually, improve outcomes.

Tele-screening aims to strengthen screening coverage by addressing many of the current geographic obstacles and unequal distribution of services across numerous areas. It also allows physicians and health professionals to share and shift tasks, using skilled graders to read retinal pictures instead of ophthalmologists. It provides a fast, accurate, and cost-effective solution to DR screening in all resource scenarios. In many countries, the availability of experienced retinal graders is a major challenge.An AI-based DR screening system, such as one that uses fundus-on-phone (FOP) retinal imaging, could be a potential answer.

ROPis a vasoproliferative condition of the premature retina that can lead to tractional retinal detachment and permanent blindness. ROP is the root cause of blindness for over 30,000 children every year around the world, and the numberscontinue to rise. However, visual loss in children may usually be avoided with prompt treatment. As a result, regular screening for early detection and immediate treatment is critical for eye carein at-risk infants.

As widespread glaucoma screening is costly and time-consuming, and diagnostic accuracy is limited according to a majority ofophthalmologists, sophisticated techniques can make better use of information for the effective detection of eye-related disorders. Tele-glaucoma and virtual clinicsuse advanced technology to effectively screen and detect glaucomatous changes in patients, especially from fundus photographs. Through a combination of fundus photography, IOP measurements, and VF screening, teleophthalmology can increase the sensitivity of glaucoma screenings in community or primary health systems and provide healthcare access to patients in resource-depleted areas.

Traditional visual acuity testing to assess refractive error is time-consuming and needs the availability of equipment as well as examiners who are knowledgeable in the art of prescribing spectacles. People who have trouble expressing themselves, such as small children, the elderly, and individuals with verbal communication difficulties, will find the procedure problematic. Furthermore, the equipment required for prescribing, particularly the lenses, is expensive. While myopia raises the risk of posterior segment issues on its own, these concerns are amplified in pathologic myopia (PM), which occurs when potentially blinded posterior segment pathological alterations arise due to globe elongation. DL algorithms have made it possible to properly forecast refractive errors using fundus pictures, which was previously impossible for ophthalmologists owing to the fact thatonly the spherical component can be anticipated. PM can also be detected using algorithms in fundus pictures. Combining fundus photos with demographic or clinical data could increase prediction accuracy.

Without an iota of doubt, COVID-19 has accelerated the development and adoption of these digital technologies.The pandemic has created an environment suited for telemedicine in ophthalmology to thrive. Growing AI and telecommunications technologies can potentially change how the data-rich and image-dependent specialty of ophthalmology is delivered around the world.