Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective.

Background: Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. Methods: This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning. Results: One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10-12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63-0.83. Conclusion: Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology.

Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective

Background Many artificial intelligence (AI) studies have focused on development of AI models, novel techniques, and reporting guidelines. However, little is understood about clinicians' perspectives of AI applications in medical fields including ophthalmology, particularly in light of recent regulatory guidelines. The aim for this study was to evaluate the perspectives of ophthalmologists regarding AI in 4 major eye conditions: diabetic retinopathy (DR), glaucoma, age-related macular degeneration (AMD) and cataract. Methods This was a multi-national survey of ophthalmologists between March 1st, 2020 to February 29th, 2021 disseminated via the major global ophthalmology societies. The survey was designed based on microsystem, mesosystem and macrosystem questions, and the software as a medical device (SaMD) regulatory framework chaired by the Food and Drug Administration (FDA). Factors associated with AI adoption for ophthalmology analyzed with multivariable logistic regression random forest machine learning. Results One thousand one hundred seventy-six ophthalmologists from 70 countries participated with a response rate ranging from 78.8 to 85.8% per question. Ophthalmologists were more willing to use AI as clinical assistive tools (88.1%, n = 890/1,010) especially those with over 20 years' experience (OR 3.70, 95% CI: 1.10–12.5, p = 0.035), as compared to clinical decision support tools (78.8%, n = 796/1,010) or diagnostic tools (64.5%, n = 651). A majority of Ophthalmologists felt that AI is most relevant to DR (78.2%), followed by glaucoma (70.7%), AMD (66.8%), and cataract (51.4%) detection. Many participants were confident their roles will not be replaced (68.2%, n = 632/927), and felt COVID-19 catalyzed willingness to adopt AI (80.9%, n = 750/927). Common barriers to implementation include medical liability from errors (72.5%, n = 672/927) whereas enablers include improving access (94.5%, n = 876/927). Machine learning modeling predicted acceptance from participant demographics with moderate to high accuracy, and area under the receiver operating curves of 0.63–0.83. Conclusion Ophthalmologists are receptive to adopting AI as assistive tools for DR, glaucoma, and AMD. Furthermore, ML is a useful method that can be applied to evaluate predictive factors on clinical qualitative questionnaires. This study outlines actionable insights for future research and facilitation interventions to drive adoption and operationalization of AI tools for Ophthalmology.

Digital health during COVID-19: lessons from operationalising new models of care in ophthalmology.

The COVID-19 pandemic has resulted in massive disruptions within health care, both directly as a result of the infectious disease outbreak, and indirectly because of public health measures to mitigate against transmission. This disruption has caused rapid dynamic fluctuations in demand, capacity, and even contextual aspects of health care. Therefore, the traditional face-to-face patient-physician care model has had to be re-examined in many countries, with digital technology and new models of care being rapidly deployed to meet the various challenges of the pandemic. This Viewpoint highlights new models in ophthalmology that have adapted to incorporate digital health solutions such as telehealth, artificial intelligence decision support for triaging and clinical care, and home monitoring. These models can be operationalised for different clinical applications based on the technology, clinical need, demand from patients, and manpower availability, ranging from out-of-hospital models including the hub-and-spoke pre-hospital model, to front-line models such as the inflow funnel model and monitoring models such as the so-called lighthouse model for provider-led monitoring. Lessons learnt from operationalising these models for ophthalmology in the context of COVID-19 are discussed, along with their relevance for other specialty domains.

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.

Artificial intelligence for diabetic retinopathy screening, prediction and management.

PURPOSE OF REVIEW: Diabetic retinopathy is the most common specific complication of diabetes mellitus. Traditional care for patients with diabetes and diabetic retinopathy is fragmented, uncoordinated and delivered in a piecemeal nature, often in the most expensive and high-resource tertiary settings. Transformative new models incorporating digital technology are needed to address these gaps in clinical care. RECENT FINDINGS: Artificial intelligence and telehealth may improve access, financial sustainability and coverage of diabetic retinopathy screening programs. They enable risk stratifying patients based on individual risk of vision-threatening diabetic retinopathy including diabetic macular edema (DME), and predicting which patients with DME best respond to antivascular endothelial growth factor therapy. SUMMARY: Progress in artificial intelligence and tele-ophthalmology for diabetic retinopathy screening, including artificial intelligence applications in 'real-world settings' and cost-effectiveness studies are summarized. Furthermore, the initial research on the use of artificial intelligence models for diabetic retinopathy risk stratification and management of DME are outlined along with potential future directions. Finally, the need for artificial intelligence adoption within ophthalmology in response to coronavirus disease 2019 is discussed. Digital health solutions such as artificial intelligence and telehealth can facilitate the integration of community, primary and specialist eye care services, optimize the flow of patients within healthcare networks, and improve the efficiency of diabetic retinopathy management.

COVID-19: Ocular Manifestations and the APAO Prevention Guidelines for Ophthalmic Practices.

The World Health Organization declared the Coronavirus Disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus 2 a "Pandemic" on March 11, 2020. As of June 1, 2020, Severe Acute Respiratory Syndrome Coronavirus 2 has infected >6.2 million people and caused >372,000 deaths, including many health care personnel. It is highly infectious and ophthalmologists are at a higher risk of the infection due to a number of reasons including the proximity between doctors and patients during ocular examinations, microaerosols generated by the noncontact tonometer, tears as a potential source of infection, and some COVID-19 cases present with conjunctivitis. This article describes the ocular manifestations of COVID-19 and the APAO guidelines in mitigating the risks of contracting and/or spreading COVID-19 in ophthalmic practices.

SARS-CoV-2 and the Eye: Implications for the Retina Specialist from Human Coronavirus Outbreaks and Animal Models.

PURPOSE: The current SARS-CoV-2 pandemic has escalated rapidly since December 2019. Understanding the ophthalmic manifestations in patients and animal models of the novel coronavirus may have implications for disease surveillance. Recognition of the potential for viral transmission through the tear film has ramification for protection of patients, physicians, and the public. METHODS: Information from relevant published journal articles was surveyed using a computerized PubMed search and public health websites. We summarize current knowledge of ophthalmic manifestations of SARS-CoV-2 infection in patients and animal models, risk mitigation measures for patients and their providers, and implications for retina specialists. RESULTS: SARS-CoV-2 is efficiently transmitted among humans, and while the clinical course is mild in the majority of infected patients, severe complications including pneumonia, acute respiratory distress syndrome, and death can ensue, most often in elderly patients and individuals with co-morbidities. Conjunctivitis occurs in a small minority of patients with COVID-19 and SARS-CoV-2 RNA has been identified primarily in association with conjunctivitis. Uveitis has been observed in animal models of coronavirus infection and cotton-wool spots have been reported recently. CONCLUSION: SARS-CoV-2 and other coronaviruses have been rarely associated with conjunctivitis. The identification of SARS-CoV and SARS-CoV-2 RNA in the tear film of patients and its highly efficient transmission via respiratory aerosols supports eye protection, mask and gloves as part of infection prevention and control recommendations for retina providers. Disease surveillance during the COVID-19 pandemic outbreak may also include ongoing evaluation for uveitis and retinal disease given prior findings observed in animal models and a recent report of retinal manifestations.

Evolving Practice Patterns in Singapore's Public Sector Ophthalmology Centers During the COVID-19 Pandemic.

Coronavirus disease 19 (COVID-19) was first reported in Wuhan, China, in December 2019, and has since become a global pandemic. Singapore was one of the first countries outside of China to be affected and reported its first case in January 2020. Strategies that were deployed successfully during the 2003 outbreak of severe acute respiratory syndrome have had to evolve to contain this novel coronavirus. Like the rest of the health care services in Singapore, the practice of ophthalmology has also had to adapt to this rapidly changing crisis. This article discusses the measures put in place by the 3 largest ophthalmology centers in Singapore's public sector in response to COVID-19, and the challenges of providing eye care in the face of stringent infection control directives, staff redeployments and "social distancing." The recently imposed "circuit breaker," effectively a partial lockdown of the country, has further limited our work to only the most essential of services. Our staff are also increasingly part of frontline efforts in the screening and care of patients with COVID-19. However, this crisis has also been an opportunity to push ahead with innovative practices and given momentum to the use of teleophthalmology and other digital technologies. Amidst this uncertainty, our centers are already planning for how ophthalmology in Singapore will be practiced in this next stage of the COVID-19 pandemic, and beyond.