Telemedicine in Diabetic Retinal Screening: Pre- and Post-COVID-19 Challenges a New Perspective
Telemedicine in ophthalmology has been around for decades and has been successful with its use in diabetic retinal screening in countries like the UK (with the introduction of the UK National Diabetic Eye Screening Programme in 2003). However, most telemedicine, in the field of diabetic retinopathy,...
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| Format: | Article |
| Language: | English |
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Wolters Kluwer Medknow Publications
2024-12-01
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| Series: | Journal of Medical Evidence |
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| Online Access: | https://journals.lww.com/10.4103/JME.JME_173_23 |
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| author | Arshi Baig Azhar Zafar |
| author_facet | Arshi Baig Azhar Zafar |
| author_sort | Arshi Baig |
| collection | DOAJ |
| description | Telemedicine in ophthalmology has been around for decades and has been successful with its use in diabetic retinal screening in countries like the UK (with the introduction of the UK National Diabetic Eye Screening Programme in 2003). However, most telemedicine, in the field of diabetic retinopathy, has largely been reliant on human graders for triage purposes. With the advent of COVID-19, patients with chronic conditions, such as diabetes, were disproportionately affected. The pandemic also caused significant rise in patients on waiting lists. Before the pandemic, there have been studies illustrating the use of artificial intelligence (AI) to analyse images obtained from patients screened for monitoring of their diabetic retinopathy. The image analysis by AI and deep-learning algorithms offers insight into the future of screening in diabetes. The transition, from the use of human graders in teleophthalmology to the use of AI-based image analysis has the potential to screen a wider cohort of patients, thereby tackling waiting lists awaiting screening which has lengthened since after COVID-19. It is therefore vital to understand the role of AI in screening diabetic retinopathy patients, from a patient-acceptability, cost-effectiveness and reliability perspective as, this offers potential answers to streamline the screening process further. |
| format | Article |
| id | doaj-art-96fafcadf2834e868d809915a6468db1 |
| institution | Kabale University |
| issn | 2667-0720 2667-0739 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wolters Kluwer Medknow Publications |
| record_format | Article |
| series | Journal of Medical Evidence |
| spelling | doaj-art-96fafcadf2834e868d809915a6468db12025-01-07T07:17:43ZengWolters Kluwer Medknow PublicationsJournal of Medical Evidence2667-07202667-07392024-12-015432032310.4103/JME.JME_173_23Telemedicine in Diabetic Retinal Screening: Pre- and Post-COVID-19 Challenges a New PerspectiveArshi BaigAzhar ZafarTelemedicine in ophthalmology has been around for decades and has been successful with its use in diabetic retinal screening in countries like the UK (with the introduction of the UK National Diabetic Eye Screening Programme in 2003). However, most telemedicine, in the field of diabetic retinopathy, has largely been reliant on human graders for triage purposes. With the advent of COVID-19, patients with chronic conditions, such as diabetes, were disproportionately affected. The pandemic also caused significant rise in patients on waiting lists. Before the pandemic, there have been studies illustrating the use of artificial intelligence (AI) to analyse images obtained from patients screened for monitoring of their diabetic retinopathy. The image analysis by AI and deep-learning algorithms offers insight into the future of screening in diabetes. The transition, from the use of human graders in teleophthalmology to the use of AI-based image analysis has the potential to screen a wider cohort of patients, thereby tackling waiting lists awaiting screening which has lengthened since after COVID-19. It is therefore vital to understand the role of AI in screening diabetic retinopathy patients, from a patient-acceptability, cost-effectiveness and reliability perspective as, this offers potential answers to streamline the screening process further.https://journals.lww.com/10.4103/JME.JME_173_23covid-19diabetic retinal screeningtelemedicineteleophthalmology |
| spellingShingle | Arshi Baig Azhar Zafar Telemedicine in Diabetic Retinal Screening: Pre- and Post-COVID-19 Challenges a New Perspective Journal of Medical Evidence covid-19 diabetic retinal screening telemedicine teleophthalmology |
| title | Telemedicine in Diabetic Retinal Screening: Pre- and Post-COVID-19 Challenges a New Perspective |
| title_full | Telemedicine in Diabetic Retinal Screening: Pre- and Post-COVID-19 Challenges a New Perspective |
| title_fullStr | Telemedicine in Diabetic Retinal Screening: Pre- and Post-COVID-19 Challenges a New Perspective |
| title_full_unstemmed | Telemedicine in Diabetic Retinal Screening: Pre- and Post-COVID-19 Challenges a New Perspective |
| title_short | Telemedicine in Diabetic Retinal Screening: Pre- and Post-COVID-19 Challenges a New Perspective |
| title_sort | telemedicine in diabetic retinal screening pre and post covid 19 challenges a new perspective |
| topic | covid-19 diabetic retinal screening telemedicine teleophthalmology |
| url | https://journals.lww.com/10.4103/JME.JME_173_23 |
| work_keys_str_mv | AT arshibaig telemedicineindiabeticretinalscreeningpreandpostcovid19challengesanewperspective AT azharzafar telemedicineindiabeticretinalscreeningpreandpostcovid19challengesanewperspective |