Telemedicine-based remote digital fundus imaging (RDFI-TM) offers a promising platform for the screening of retinopathy of prematurity. This advanced technology facilitates early detection and management of this potentially blinding condition in premature infants.
RDFI-TM addresses some of the challenges faced by ophthalmologists in examining this vulnerable population in both low- and high-income countries, such as limited access to specialized care, the need for timely diagnosis, and the logistical difficulties of in-person screenings.
By enabling remote consultations and real-time image sharing, RDFI-TM enhances the reach and efficiency of retinal screenings, ultimately improving the outcomes for premature infants at risk of retinopathy, as also illustrated by ANTONIO CAPONE, Associated Retinal Consultants at Royal Oak, Michigan, during his intervention.
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“It’s an honor to be here with you today. I’d like to acknowledge my colleague and friend Professor and Chair Doctor Paul Chan.
Causes of pediatric blindness vary from country to country for different reasons. Congenital cataract is a primary cause of pediatric visual impairment in low-income countries retinopathy of prematurity (ROP) and prevails in middle-income countries.
The story of the deployment of telemedicine to bear on the management of retinopathy prematurity is informative, as the learnings are extrapolatable to other disciplines and conditions. Technology, human resources, and data are all critical to achieving the desired goal.
Underlined successful initiatives in this area are teamwork and collaboration, for all of the workstreams. Here’s an image of one of the early ROP classification groups, taken 20 years ago in Canada.
Retinopathy prematurity (ROP) is a proliferative disorder of the retina occurring principally in. newborn preterm infants, that was first described in 1942. It remains today a global, impactful, and challenging disease, particularly from a diagnostic perspective, since it takes years to acquire the appropriate clinical acumen. As was the case of 1942, every time a low to middle-income country evolves to having neonatal intense care units and availability of incubators, a wave of retinopathy of prematurity follows.
ROP Is an eminently treatable disease - with a timely and appropriate diagnosis. 99% of children are effectively managed, and that underscores the importance of surveillance, as an at-risk child will only do well if they can access the care pathways. For example, in Armenia, in 1995 there was only one intensive care unit. By 2010, they had 9, and a wave of retinopathy followed. However, with tele-medicine and tele-education with an effective transfer of diagnostic and treatment skills, and ongoing tele-mentoring, an important impact was made on minimizing the negative impact of retinopathy of prematurity on that population.
Analysis of local data demonstrated that ROP was more common in the Armenian co-hort and also children who Id ROP tended to be bigger at birth than those in the USA. If the criteria used in managing children in the USA had been applied, a significant number of children in Armenia would have gone blind. These findings underscore the importance of having on-site data after the telemedicine construct is implemented. The ideal is a global expert at every baby’s bedside.
In practical terms, however, it specifically underscores the need for “expertise-extenders” via technological solutions. 20 years ago, my colleagues and I Id a “smart” diagnostic software that conveyed some of the critical diagnostic elements, in order that less Ied could correctly diagnose disease. This has evolved in the current day to AI algorithms for direct output. By way of example, 40 years ago, when the first classification system was created, the notion of plus disease was binary, normal side-left and normal side-right in these 2 images. This concept has Id into something more nuanced, with vascular change occurring In the continuum and risk accruing across the continuum.
My colleague Dr. Chan and his team have Id a cloud-based technology that combines clinical features with the diagnostic features of the retina deployed in the treatment of ROP. There are examples of this deployment in Mongolia, Nepal, and more recently in India (Aravind), where the AI component has been implemented in full.
When we have conversations about the digital divide, we have to go beyond the discussion of high-speed availability to telemedical infrastructure (hardware, software, technical expertise, service support/ infrastructure, data management, data security (PHI), validated, ease of use, reading center) and beyond (education, Ie, governmental support like local consideration and cost rationalization).
AI will be a tool to bridge the implementation gap, but there are a variety of other important aspects that need to be device-agnostic so they can be deployed in full, as well as Iing consideration of local circumstances. We also need to emphasize publication of our findings when we have a successful deployment in the interest of gaining support, and in generating sustainability.
Our learnings from deploying a telesystem construct are the requirements listed here (multidisciplinary team-based approach, leveraging technology, investing in data, pipeline programs, leadership development, advocacy, and people will make the change with the assistance of technology).
Most importantly, the critical element is dedicating persevering people. As Helen Keller is quoted as having said: “Alone we can do so little, but together we can do so much.”
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