Oman’s artificial intelligence-powered diabetic retinopathy screening programme has reduced specialist eye clinic waiting lists by 87%, while identifying more than 12,000 diabetic patients who require further clinical examination.
More than 43,000 patients have been screened since the launch of the National Project for Diabetic Retinopathy Screening Using Artificial Intelligence Technologies, according to the Ministry of Health.
The AI system has analysed more than 43,000 retinal images, flagging around 30% of patients for specialist review and helping doctors identify cases requiring earlier intervention.
Waiting times fall from 62 days to eight
Anas bin Nasser Al Kimyani, Director of the National Virtual Health Centre at the Ministry of Health, said the programme reduced waiting times for examination and treatment appointments from 62 days to eight days during its first seven months.
The screening process itself has also become much faster.
Traditional examinations that involved pupil-dilating eye drops could take around one-and-a-half hours, while the AI-supported process has reduced screening time to approximately 15 minutes.
That allows ophthalmologists to spend more time on complex cases, treatment and surgery instead of routine screening.
AI system records 91.3% diagnostic accuracy
The Ministry of Health said the screening system recorded diagnostic accuracy of 91.3% and sensitivity of 85%.
These figures support its use as a triage tool to help medical teams identify patients who need further assessment.
The system is not replacing specialist diagnosis, but it is helping healthcare providers prioritise patients more effectively.
This is particularly important in diabetic retinopathy, where delayed detection can allow retinal damage to progress before symptoms become obvious.
More than 12,000 patients identified for specialist assessment
With around 30% of screened patients being referred for further examination, the programme has identified more than 12,000 people who may require closer clinical attention.
The scale of the programme reflects the wider burden of diabetes in Oman.
Around 15% of the adult population has diabetes, placing a substantial number of people at risk of diabetic retinopathy, a condition that can damage blood vessels in the retina and eventually cause vision loss.
The programme aims to cover all adults registered with Type 1 or Type 2 diabetes, with screening frequency determined by the severity of retinal disease.
First phase operating across 25 health institutions
The first phase of the project is operating at 25 health institutions across Oman’s governorates.
Retinal imaging equipment has been distributed geographically to improve access, with the highest utilisation recorded in Seeb, Bausher, Suhar and Ibri.
The Ministry of Health plans to expand the programme to additional health centres, particularly in remote areas.
According to the ministry, Oman is the third country in the world to undertake the project.
Costs fall alongside waiting times
The programme has also delivered operational savings.
The ministry said AI-supported screening reduced annual operating costs by 43.2% compared with previous procedures.
Earlier diagnosis could also reduce the cost of treating advanced disease by identifying high-risk patients before they require more complex interventions or surgery.
This creates a dual benefit: improving access while lowering the cost of delivering large-scale screening.
Oman plans AI screening for glaucoma and keratoconus
The programme’s roadmap extends beyond diabetic retinopathy.
Oman plans to introduce AI-assisted screening for glaucoma and keratoconus, while expanding the use of virtual medicine and specialist follow-up clinics.
The Ministry of Health also plans to develop a local AI engine trained on retinal images collected in Oman.
A locally trained system could allow future diagnostic models to be tailored more closely to the characteristics of the Omani population and the country’s clinical environment.
Why this matters
The programme is a strong example of AI being used to solve a practical healthcare capacity problem rather than simply adding another digital layer to existing services.
By screening large numbers of patients quickly and identifying those most likely to need specialist care, Oman is using AI to relieve pressure on ophthalmology clinics while improving the chances of earlier treatment.
The 87% reduction in waiting lists and 43.2% reduction in operating costs show that the impact is operational as well as clinical.
Editor’s note
The most important part of the programme is its role as a triage system.
AI is not replacing ophthalmologists. It is helping them spend more time on the patients who need specialist care most urgently.
The planned development of a locally trained AI engine is also significant. If Oman can build diagnostic models using its own clinical data, it could move from adopting imported AI tools toward developing healthcare AI systems better adapted to its population and health infrastructure.
