Abstract
INTRODUCTION:
Diabetic retinopathy (DR) is a leading cause of vision loss globally, and its burden is increasing, particularly in regions with a high prevalence of diabetes like Oman. Early detection and timely intervention are crucial for preventing vision loss and improving patient outcomes. This study aimed to evaluate referral patterns and screening outcomes for DR at Bowsher Specialized Polyclinics (BSP) in Muscat, Oman.
METHODOLOGY:
In this cross-sectional study conducted between January 1 and December 31, 2023, data were retrospectively collected from the electronic health records of 6677 patients referred to BSP. The assessment included referral sources, reasons for referral, patient demographics, waiting times, screening results, and follow-up plans.
RESULTS:
A high proportion of external referrals (79%), with 90.6% being routine. Nearly half of the referrals were for DR screening, and among those screened, 16.9% had abnormal findings, with mild nonproliferative DR (NPDR) being the most prevalent. Males showed a significantly higher proportion of abnormal screening outcomes. In addition, mean waiting times were long (145.8 days), and 39.5% of patients were defaulters.
CONCLUSIONS:
These findings highlight the need for targeted interventions to optimize referral pathways, expand screening capacity, and enhance patient engagement to improve DR management.
Keywords: Diabetic retinopathy, ophthalmology clinic, referral patterns, screening outcomes, Oman
Introduction
Diabetic retinopathy (DR) is a significant microvascular complication of diabetes mellitus, posing a major public health challenge worldwide.[1] With a global prevalence of approximately 22.27% among diabetic individuals, nearly one in five diabetic patients is affected, leading to considerable vision loss and socioeconomic consequences such as reduced productivity and increased healthcare utilization.[2,3]
The burden of DR is not uniformly distributed.[2] In the Middle East, individuals with diabetes face an elevated risk of developing DR compared to other regions, a disparity highlighted by a systematic review and meta-analysis.[2] This elevated risk is particularly concerning for countries like Oman, where the prevalence of diabetes is on the rise.[4,5] Notably, the prevalence of DR among Omani diabetic patients rose from 14.3% in 2003 to 19.3% in 2017,[6] highlighting the growing challenge of this complication. Early detection and timely intervention are crucial in preventing the progression of DR and averting vision loss. According to the World Health Organization, timely screening can reduce the incidence of vision loss by up to 95% when appropriate treatment is administered.[7]
In Oman, where ophthalmology represents one of the highest-volume specialties—reflected by the 390,036 outpatient ophthalmic visits reported in the Ministry of Health’s Annual Health Report 2023 —the efficient integration of DR screening is a vital component of the broader strategy to reduce vision loss and optimize resource allocation.[8] This trend underscores the importance of efficient referral systems to manage the substantial patient load requiring specialized ophthalmic services. Since 2006, the Ministry of Health (MOH) has implemented an electronic patient referral system to streamline the referral process and ensure timely access to specialized care.[9,10] This system facilitates communication between primary and secondary care providers, promoting continuity of care and optimizing resource utilization within the healthcare infrastructure.[9]
Recognizing the urgent need for DR management, the MOH, Oman has recently launched an initiative to integrate artificial intelligence (AI)-assisted screening devices in selected healthcare facilities across the country. The project is designed to improve screening capacity, streamline referral processes, and eventually improve patient outcomes by facilitating early detection of DR and ensure appropriate interventions. Bowsher Specialized Polyclinics (BSP), a secondary care ophthalmology clinic in MOH, Oman, is one of the settings where the AI-assisted screening devices have been installed.
Despite this promising initiative, there is a substantial burden of DR, and room for improvement in patient management. Efficient referral systems from primary healthcare centers to secondary or tertiary ophthalmic clinics are pivotal to ensure timely, specialized care, and optimize resource utilization.[11,12] Conversely, suboptimal referral practices can lead to delays in diagnosis and treatment, contributing to the progression of DR and increased healthcare burdens.[13]
Although the critical role of referral systems is well recognized, there is limited data examining the patterns and outcomes of referrals for DR screening in Oman. A study conducted in Saudi Arabia, a neighboring country with similar healthcare infrastructure found that vision screening and DR evaluation comprised 55.5% of total referrals, highlighting the significant demand for DR-related ophthalmic services and the necessity of assessing referral patterns to identify potential inefficiencies and areas for improvement.[14]
Given the rising prevalence of diabetes and the associated risk of DR in Oman,[4,5] it is imperative to assess current referral patterns and screening outcomes as a baseline. Such an evaluation will not only quantify the existing burden of DR but also provide a reference point against which the impact of the MOH’s AI initiatives can be measured.
This study, therefore, aims to assess the current referral patterns and screening outcomes for DR at BSP. By analyzing referral sources, reasons for referrals, waiting times, and screening results, the study seeks to identify strengths and weaknesses within the current system. Ultimately, the findings will inform strategies to optimize referral pathways, improve patient adherence to appointments, enhance screening programs, and contribute to the overall improvement of DR management in Oman.
Methodology
Study design
This study is a retrospective cross-sectional study designed to evaluate referral patterns and screening outcomes for DR in ophthalmology at BSP. The study encompasses a 1-year period, from January 1 to December 31, 2023, serving as a baseline in parallel with the MOH’s recently launched initiative to integrate AI-assisted DR screening devices across the selected healthcare facilities.
Study setting and context
BSP, a key secondary healthcare facility in the Oman Governorate, plays a crucial role in providing specialist outpatient services, including ophthalmology, and serves as a significant referral center within the region. Notably, BSP is one of 25 healthcare locations in Oman selected for the MOH national initiative to implement AI for DR screening. This program, which involves the distribution of advanced fundus cameras and AI applications, aims to enhance early DR detection and improve patient outcomes by increasing screening capacity and streamlining referral processes. Therefore, this study provides crucial baseline data that will enable future evaluations to measure the impact of AI integration on referral efficiency, waiting times, and overall patient outcomes at BSP and across the national program.
Data collection
Data for this retrospective study were extracted from the electronic health records (AL Shifa 3 + EHRs) for individual patients referred to the ophthalmology clinics at BSP. All new incoming referrals to the ophthalmology clinics during the study period were included, irrespective of their source or the reason for referral. A predefined data collection template was utilized to systematically extract relevant information from the EHRs.
This included:
Patient demographics, such as age and gender.
Referral information, including the date, source (internal, external, walk-in), reason (DR screening, refractive error, vision loss, red eye, painful eye, other complaint), and type (routine or urgent).
Screening outcomes (normal or abnormal). For abnormal screenings, the severity of DR was recorded as mild nonproliferative DR (NPDR), moderate NPDR, severe NPDR, or proliferative DR (PDR).
Follow-up recommendations, detailing any documented plans for subsequent appointments or treatment referrals.
Waiting times, specifically the duration between the date of referral and the date of the initial ophthalmology consultation, as well as the interval to the date of any DR screening performed.
Statistical analysis
Descriptive statistics were employed to summarize the data, with results presented as frequencies, percentages, means, and standard deviations. Inferential statistical tests, such as Chi-square tests for categorical variables and t-tests for continuous variables, were used to identify significant differences and associations within the dataset. Statistical significance was set at a P < 0.05. Data analysis was conducted using R software, leveraging its robust statistical and graphical capabilities to ensure accurate and comprehensive analysis.
Ethical approval
This study adhered to ethical principles and guidelines to protect patient rights and confidentiality. Ethical approval was obtained from the Ethical Approval Committee (MH/DGHS/DPT/373/2025). All data were anonymized to ensure patient privacy, with identifiers removed during the extraction process. The study complies with the ethical standards outlined in the Declaration of Helsinki.
Results
Participant demographics
The study examined 11,047 newly booked appointments at the BSP ophthalmology clinic. A total of 6677 patients attended their scheduled appointments, whereas 4370 missed their appointments. Among those who attended, 57.5% (n = 3836) were female and 42.5% (n = 2841) were male. The age distribution was as follows: 19.3% (n = 1291) were children (<18 years), 25.5% (n = 1701) were adults (18–45 years), 39.3% (n = 2623) were middle-aged adults (45–65 years), and 15.9% (n = 1062) were seniors (>65 years).
Source and type of referral
The majority of referrals to the ophthalmology clinic were external, originating from primary healthcare centers and other healthcare facilities outside of BSP, accounting for 78.97% (n = 5273) of all cases. Walk-in patients constituted 19.96% (n = 1333), and internal referrals, originating from other departments within BSP itself, comprised only 1.06% (n = 71) of the total. The majority of referrals were routine (90.6%, n = 6047), with urgent referrals comprising only 9.4% (n = 630).
Reasons for referral
The primary reason for referral was DR screening, which accounted for 46.64% of cases (n = 3114). Other referral reasons included refractive errors causing blurry vision (18.99%, n = 1268), vision loss (3.19%, n = 213), red eye (1.23%, n = 82), painful eye (0.33%, n = 22), and other unspecified complaints (29.62%, n = 1978). Detailed information on patient demographics and referral characteristics is presented in Table 1.
Table 1.
Patient demographics and referral characteristics (n=6677)
| Group | Subgroup | Diabetic retinopathy screening, n (%) | Other complaint, n (%) | Painful eye, n (%) | Red eye, n (%) | Refractive error, n (%) | Vision loss, n (%) | Total cases, n (%) |
|---|---|---|---|---|---|---|---|---|
| Gender | Female | 1772 (46.2) | 1121 (29.2) | 17 (0.4) | 39 (1) | 770 (20.1) | 117 (3.1) | 3836 (57.5) |
| Male | 1342 (47.2) | 857 (30.2) | 5 (0.2) | 43 (1.5) | 498 (17.5) | 96 (3.4) | 2841 (42.5) | |
| Source of referral | Internal | 22 (31) | 36 (50.7) | 0 | 0 | 13 (18.3) | 0 | 71 (1.1) |
| External | 2282 (43.3) | 1630 (30.9) | 19 (0.4) | 69 (1.3) | 1091 (20.7) | 182 (3.5) | 5273 (79) | |
| Walk in | 810 (60.8) | 312 (23.4) | 3 (0.2) | 13 (1) | 164 (12.3) | 31 (2.3) | 1333 (20) | |
| Age group | Adult (18–45) | 639 (37.6) | 624 (36.7) | 9 (0.5) | 35 (2.1) | 382 (22.5) | 12 (0.7) | 1701 (25.5) |
| Child (<18) | 15 (1.2) | 574 (44.5) | 0 | 32 (2.5) | 663 (51.4) | 7 (0.5) | 1291 (19.3) | |
| Middle-aged (45–65) | 1757 (67) | 521 (19.9) | 10 (0.4) | 12 (0.5) | 213 (8.1) | 110 (4.2) | 2623 (39.3) | |
| Senior (>65) | 703 (66.2) | 259 (24.4) | 3 (0.3) | 3 (0.3) | 10 (0.9) | 84 (7.9) | 1062 (15.9) | |
| Type of referral | Urgent | 153 (24.3) | 303 (48.1) | 5 (0.8) | 18 (2.9) | 118 (18.7) | 33 (5.2) | 630 (9.4) |
| Routine | 2961 (49) | 1675 (27.7) | 17 (0.3) | 64 (1.1) | 1150 (19) | 180 (3) | 6047 (90.6) |
Distribution of patients by gender, referral source, age group, and referral type, correlated with primary reasons for referral to the ophthalmology clinic
Diabetic retinopathy screening outcomes and severity of abnormality
Among the 3114 patients screened for DR, 82.4% (n = 2586) had normal findings. 17.6% (n = 528) exhibited some degree of DR. Of those with abnormal findings, 54.6% (n = 301) were diagnosed with mild NPDR, 22.1% (n = 116) were diagnosed with moderate NPDR, 6.2% (n = 34) were diagnosed with severe NPDR, and 14.1% (n = 77) were diagnosed with PDR.
As shown in Table 2, 1342 (43.1%) of the screened patients were male and 1772 (56.9%) were female. Notably, the proportion of males was higher in severe cases, with 21 (61.8%) males diagnosed with severe NPDR compared to 13 (38.2%) females. The majority of referrals originated from external sources (73.3%, n = 2282), followed by walk-in patients (26.0%, n = 810), whereas only 0.7% (n = 22) were referred internally. The percentage of externally referred patients increased with severity, reaching 88.3% (n = 68) for PDR and 85.3% (n = 29) for severe NPDR.
Table 2.
Diabetic retinopathy screening outcomes and severity (n=3114)
| Total (n=3114), n (%) | Mild NPDR (n=301), n (%) | Moderate NPDR (n=116), n (%) | Normal (n=2586), n (%) | PDR (n=77), n (%) | Severe NPDR (n=34), n (%) | |
|---|---|---|---|---|---|---|
| Gender | ||||||
| Male | 1342 (43.1) | 151 (50.2) | 62 (53.4) | 1066 (41.2) | 42 (54.5) | 21 (61.8) |
| Female | 1772 (56.9) | 150 (49.8) | 54 (46.6) | 1520 (58.8) | 35 (45.5) | 13 (38.2) |
| Source of referral | ||||||
| External | 2282 (73.3) | 212 (70.4) | 89 (76.7) | 1884 (72.9) | 68 (88.3) | 29 (85.3) |
| Internal | 22 (0.7) | 2 (0.7) | 0 | 20 (0.8) | 0 | 0 |
| Walk in | 810 (26.0) | 87 (28.9) | 27 (23.3) | 682 (26.4) | 9 (11.7) | 5 (14.7) |
| Age group | ||||||
| Child (<18) | 15 (0.5) | 0 | 0 | 15 (0.6) | 0 | 0 |
| Adult (18–45) | 639 (20.5) | 49 (16.3) | 18 (15.5) | 548 (21.2) | 16 (20.8) | 8 (23.5) |
| Middle-aged (45–65) | 1757 (56.4) | 183 (60.8) | 69 (59.5) | 1436 (55.5) | 47 (61.0) | 22 (64.7) |
| Senior (>65) | 703 (22.6) | 69 (22.9) | 29 (25.0) | 587 (22.7) | 14 (18.2) | 4 (11.8) |
| Type of referral | ||||||
| Routine | 2961 (95.1) | 282 (93.7) | 98 (84.5) | 2499 (96.6) | 57 (74.0) | 25 (73.5) |
| Urgent | 153 (4.9) | 19 (6.3) | 18 (15.5) | 87 (3.4) | 20 (26.0) | 9 (26.5) |
Breakdown of DR diagnoses (normal, mild NPDR, moderate NPDR, severe NPDR, PDR) by patient demographics and referral characteristics. NPDR: Non-PDR, PDR: Proliferative DR, DR: Diabetic retinopathy
In terms of age distribution, the majority of patients (56.4%, n = 1757) belonged to the middle-aged group (45–65 years), followed by seniors (>65 years) at 22.6% (n = 703), adults aged 18–45 years at 20.5% (n = 639), and children (<18 years) at 0.5% (n = 15). Notably, middle-aged patients comprised 60.8% (n = 183) of mild NPDR cases and 59.5% (n = 69) of moderate NPDR cases. The proportion of seniors was highest in mild NPDR (22.9%, n = 69) and moderate NPDR (25.0%, n = 29), but decreased in severe NPDR (11.8%, n = 4). Out of 15 screened children (0.5% of total patients), none were diagnosed with DR.
The majority of patients were referred for routine screening (95.1%, n = 2,961), whereas only 4.9% (n = 153) were classified as urgent referrals. Urgent referrals were more frequent in severe cases, accounting for 26.5% (n = 9) of severe NPDR and 26.0% (n = 20) of PDR cases, compared to 6.3% (n = 19) in mild NPDR and 15.5% (n = 18) in moderate NPDR.
Waiting times
The mean waiting time for patients with abnormal screening outcomes was 136.72 days, with a median of 129 days, whereas those with normal outcomes had a mean waiting time of 150.80 days and a median of 193 days. The detailed breakdown of waiting times by DR severity is provided in Table 3. Among patients with different severity levels of DR, those with mild NPDR had the longest waiting times, with a mean of 142.3 days and a median of 155.5 days, with a maximum delay of 727 days. Patients with moderate NPDR had a mean waiting time of 122.16 days and a median of 90 days, whereas those with severe NPDR had a mean of 122.68 days and a median of 104 days. PDR cases had a mean waiting time of 143.18 days and a median of 131 days, with a maximum waiting time of 475 days. The range of waiting times varied widely, from a minimum of 0 days to a maximum of 727 days across all groups.
Table 3.
Waiting times (days) for patients by severity of diabetic retinopathy abnormality
| Severity of abnormality | Mean waiting time (days) | Median waiting time (days) | Minimum waiting time (days) | Maximum waiting time (days) | SD | Total cases |
|---|---|---|---|---|---|---|
| Mild NPDR | 142.30 | 155.5 | 0 | 727 | 129.88 | 300 |
| PDR | 143.18 | 131.0 | 0 | 475 | 121.82 | 76 |
| Severe NPDR | 122.68 | 104.0 | 0 | 315 | 99.06 | 34 |
| Moderate NPDR | 122.16 | 90.0 | 0 | 418 | 117.15 | 116 |
This table summarizes the mean, median, minimum, maximum waiting times, and SD for patients diagnosed with different DR severities. PDR: Proliferative DR, NPDR: Non-PDR, DR: Diabetic retinopathy, SD: Standard deviation
Follow-up and treatment plans
The distribution of follow-up and treatment plans is summarized in Table 4. The treatment plan distribution showed that the majority of patients (48.97%) were referred to local health centers (discharged from ophthalmology clinics), accounting for 3270 out of 6677 cases. Follow-up at polyclinics varied in frequency, with 25.94% of patients scheduled for follow-up within 6-12 months, 8.46% within 3-6 months, and 4.21% within < 3 months. In addition, 4.75% of cases were scheduled for follow-up beyond 12 months. A total of 512 patients (7.67%) were referred for treatment, indicating the need for further medical intervention.
Table 4.
Summary of follow-up and treatment plans for patients (n=6677)
| Treatment plan | Count | Total cases | Percentage |
|---|---|---|---|
| Follow up at polyclinic 3–6 months | 565 | 6677 | 8.46 |
| Follow up at polyclinic 6–12 months | 1732 | 6677 | 25.94 |
| Follow up at polyclinic <3 months | 281 | 6677 | 4.21 |
| Follow up at polyclinic more than 12 months | 317 | 6677 | 4.75 |
| Refer for treatment | 512 | 6677 | 7.67 |
| Refer to local health center (discharge) | 3270 | 6677 | 48.97 |
This table outlines the various dispositions, including follow-up frequencies at polyclinics, referrals for treatment, and discharge to local health centers
Discussion
This study provides significant insights into referral trends and DR screening outcomes at BSP. Nearly half of all new patient encounters (46.64%) were for DR screening. Of those screened, 83.1% had normal findings and 16.9% exhibited some degree of DR–with mild NPDR being the most common abnormality (57%). A statistically significant gender difference was observed (Chi-squared test: χ2 = 21.33, df = 1, P < 0.001), with males having a higher proportion of abnormal results, particularly in severe cases (61.8% of males diagnosed with severe NPDR compared to 38.2% of females). The high proportion of external referrals (79%) for DR screening suggests that the referral system is functioning as intended in terms of patient flow from primary healthcare facilities to secondary care. However, while referral policies are in place to streamline access to specialized care, the observed data reveal significant operational inefficiencies. The substantial demand for DR screening relative to available resources leads to long waiting times (mean 145.8 days) and a high defaulter rate (39.5%). These findings indicate that the system’s practical implementation is challenged by systemic and logistical barriers, which hinder the timely and efficient delivery of care despite the existence of a formal referral policy.
The higher incidence of abnormal results in males is consistent with previous research. Several studies have noted that women are generally more proactive in seeking healthcare and attending appointments, whereas men may delay both diagnosis and treatment, potentially resulting in more severe DR manifestations.[15,16,17] Moreover, hormonal factors and lifestyle differences may contribute to the imbalanced distribution of risk factors between genders.[18,19,20] While DR can progress during pregnancy due to higher estrogen and progesterone levels , the overall findings regarding gender and DR severity remain complex.[21,22] A systematic review and meta-analysis of 49 studies reported no significant gender effect on DR or clinically significant macular edema prevalence, with only marginal significance observed in vision-threatening DR.[2] These mixed findings suggest that the relationship between gender and DR is complex and influenced by multiple factors.
The analysis revealed a long waiting period from referral to DR screening. This delay is primarily attributed to an overwhelming demand for DR screening relative to the available manpower and resources. As a result, both DR-related and non-DR-related referrals experience significant delays. The landmark ETDRS trial established that progression from moderate NPDR to PDR occurs at approximately 10% per year, and from severe NPDR at around 50% per year.[23,24] Such delays not only increase the risk of irreversible loss but also contribute to a backlog that strains ophthalmology services and necessitates more resource-intensive interventions in advanced cases.[25]
The study found that 73.3% of DR screening referrals originated from external sources (local health centers), with only 0.7% being internal referrals. This heavy reliance on primary healthcare providers highlights the need to raise awareness and adherence to standardized DR screening guidelines at the primary care level. In addition, the high percentage of defaulters, compounded by factors such as socioeconomic status, demographics, and systemic barriers,[26,27,28,29,30] suggest that many diabetic patients only seek care once symptomatic – a practice far from ideal for preventing visions loss. Logistical challenges, limited awareness, and poor communication further exacerbate nonattendance, ultimately increasing the risk of sight-threatening complications.[31,32,33]
Implications
The findings of this study highlight several areas for quality improvement, with implications for clinical practice and healthcare policy in Oman.
First, the high percentage of external referrals and the reliance on primary healthcare facilities highlight a critical need to standardize referral guidelines for DR screening. Improving communication and education among primary healthcare professionals regarding DR screening can help reduce delays in diagnosis.
Second, the fact that a significant proportion of patients exhibited abnormal findings indicates a need to increase screening capacity. This expansion is particularly crucial at the primary care level, where the initial identification and referral of patients at risk for DR occurs. Strengthening screening capabilities within primary care settings can facilitate earlier detection, reduce the burden on specialist clinics, and ensure timely management of DR. Investing in AI-assisted screening tools to detect early DR changes could alleviate current backlogs at secondary care centers like BSP and reduce waiting times for specialist consultations.
Third, the high default rate among referred patients highlights the need for improved patient engagement. Interventions such as automated reminder systems could improve patient education about the importance of routine screening. Better follow-up strategies are needed to improve appointment adherence.
Finally, the high burden on secondary care ophthalmology clinics suggests a need for task shifting and a reallocation of healthcare resources. This could involve training allied health professionals, such as ophthalmic technicians or nurses, to perform routine eye examinations and DR screening, freeing up ophthalmologists to focus on more complex cases and surgical interventions. Simultaneously, providing primary care physicians with basic ophthalmic skills and equipment can address simple eye complaints at the primary level.
Limitations
There are several limitations to this study that should be acknowledged. Given the retrospective and cross-sectional design, the study relies on preexisting records, which may have errors, and it is limited in its ability to establish causal relationships or to study time trends in referral patterns or screening outcomes. The fact that the study was conducted at a single secondary care clinic in Oman may limit the generalizability of the findings to other regions and healthcare settings in Oman. While the study’s results may not be directly transferable, the identified challenges – such as long waiting times, high defaulter rates, and the substantial burden of DR – are common to many overburdened healthcare systems. Therefore, the findings provide valuable insights and a baseline for future initiatives in similar settings, particularly in the Middle East, where diabetes is highly prevalent. In addition, because only patients who were referred and attended appointments were fully evaluated for DR, the characteristics and outcomes of defaulters or lost to follow-up may not be appropriately represented. One limitation of this study is that among the defaulters, it remains unclear how many were referred specifically for DR screening versus other reasons and how many were lost to follow-up due to logistical barriers, lack of awareness, or socioeconomic factors.
Conclusions
This study reveals a substantial burden of DR among referred patients, with significant challenges including long waiting times, high defaulter rates, and marked gender disparities in disease severity. These findings underscore the urgent need for targeted interventions to optimize referral pathways, expand screening capacity, and enhance patient engagement. Importantly, as Oman starts integrating AI-assisted screening into its healthcare infrastructure, this baseline study provides an important reference point for evaluating the future impact of such initiatives on DR management and the prevention of vision loss.
Data availability
The corresponding author will make the data used in this work accessible upon request.
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
References
- 1.Shukla UV, Tripathy K. StatPearls. Treasure Island (FL): StatPearls Publishing; 2025. Diabetic Retinopathy. 2023. [PubMed] [Google Scholar]
- 2.Teo ZL, Tham YC, Yu M, Chee ML, Rim TH, Cheung N, et al. Global prevalence of diabetic retinopathy and projection of burden through 2045:Systematic review and meta-analysis. Ophthalmology. 2021;128:1580–91. doi: 10.1016/j.ophtha.2021.04.027. [DOI] [PubMed] [Google Scholar]
- 3.Fenwick EK, Man RE, Gan AT, Kumari N, Wong C, Aravindhan A, et al. Beyond vision loss:the independent impact of diabetic retinopathy on vision-related quality of life in a Chinese Singaporean population. Br J Ophthalmol. 2019;103:1314–9. doi: 10.1136/bjophthalmol-2018-313082. [DOI] [PubMed] [Google Scholar]
- 4.Al-Mawali A, Al-Harrasi A, Jayapal SK, Morsi M, Pinto AD, Al-Shekaili W, et al. Prevalence and risk factors of diabetes in a large community-based study in the Sultanate of Oman:STEPS survey 2017. BMC Endocr Disord. 2021;21:42. doi: 10.1186/s12902-020-00655-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Al-Lawati JA, Panduranga P, Al-Shaikh HA, Morsi M, Mohsin N, Khandekar RB, et al. Epidemiology of diabetes mellitus in Oman:Results from two decades of research. Sultan Qaboos Univ Med J. 2015;15:e226–33. [PMC free article] [PubMed] [Google Scholar]
- 6.Al-Rashdi FA, Al-Mawali A. Prevalence of diabetic retinopathy in Oman:A two decade national study. Oman Med J. 2021;36:e238. doi: 10.5001/omj.2021.57. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Pei X, Li Z. Comprehensive guidelines and best practices for implementing effective Diabetic Retinopathy Screening Programs to mitigate global vision loss. J Infrastruct Policy Dev. 2024;8:6668. [Google Scholar]
- 8.Ministry of Health, Sultanate of Oman. Muscat: Ministry of Health; 2024. Annual Health Report 2023. Available from:https://moh.gov.om/en/statistics/annual-health-reports/annual-health-report-2023/ [Google Scholar]
- 9.Braithwaite J, Mannion R, Matsuyama Y, Shekelle P, Whittaker S, Al-Adawi S, editors. London: Taylor &Francis; 2017. Health Systems Improvement Across the Globe. [Google Scholar]
- 10.Khan SF, Ismail MY. Al-Shifa:Case study on Sultanate of Oman's National Healthcare Information System. Indian J Sci Technol. 2017;10:1–4. [Google Scholar]
- 11.Tobin-Schnittger P, O'Doherty J, O'Connor R, O'Regan A. Improving quality of referral letters from primary to secondary care:A literature review and discussion paper. Prim Health Care Res Dev. 2018;19:211–22. doi: 10.1017/S1463423617000755. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Seyed-Nezhad M, Ahmadi B, Akbari-Sari A. Factors affecting the successful implementation of the referral system:A scoping review. J Family Med Prim Care. 2021;10:4364–75. doi: 10.4103/jfmpc.jfmpc_514_21. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Negretti GS, Amin R, Webster L, Egan CA. Does delay in referral of proliferative diabetic retinopathy from the diabetic eye screening programme lead to visual loss? Eye (Lond) 2016;30:873–6. doi: 10.1038/eye.2016.56. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.AlHarkan DH, Altowayan RM, Alharbi AM, Aljumaiah SM, Alhijji LI, Alkhezzy BS. Pattern of ophthalmic referral from primary healthcare centres to secondary and tertiary hospitals in Qassim Province, Saudi Arabia. Int Surg J. 2020;7:1763. [Google Scholar]
- 15.Tong V, Raynor D, Aslani P. Gender differences in health and medicine information seeking behavior –A review. J Malta Coll Pharm Practice. 2014;20:14–6. [Google Scholar]
- 16.Thompson AE, Anisimowicz Y, Miedema B, Hogg W, Wodchis WP, Aubrey-Bassler K. The influence of gender and other patient characteristics on health care-seeking behaviour:A QUALICOPC study. BMC Fam Pract. 2016;17:38. doi: 10.1186/s12875-016-0440-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Mesa MS. Health care disparities between men and women with type 2 diabetes. Prev Chronic Dis. 2018;15:E46. doi: 10.5888/pcd15.170120. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Haffner SM, Klein R, Dunn JF, Moss SE, Klein BE. Increased testosterone in type I diabetic subjects with severe retinopathy. Ophthalmology. 1990;97:1270–4. doi: 10.1016/s0161-6420(90)32428-4. [DOI] [PubMed] [Google Scholar]
- 19.Mehlsen J, Erlandsen M, Poulsen PL, Bek T. Identification of independent risk factors for the development of diabetic retinopathy requiring treatment. Acta Ophthalmol. 2011;89:515–21. doi: 10.1111/j.1755-3768.2009.01742.x. [DOI] [PubMed] [Google Scholar]
- 20.Nuzzi R, Caselgrandi P. Sex hormones and their effects on ocular disorders and pathophysiology:Current aspects and our experience. Int J Mol Sci. 2022;23:3269. doi: 10.3390/ijms23063269. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Negrato CA, Mattar R, Gomes MB. Adverse pregnancy outcomes in women with diabetes. Diabetol Metab Syndr. 2012;4:41. doi: 10.1186/1758-5996-4-41. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Errera MH, Kohly RP, da Cruz L. Pregnancy-associated retinal diseases and their management. Surv Ophthalmol. 2013;58:127–42. doi: 10.1016/j.survophthal.2012.08.001. [DOI] [PubMed] [Google Scholar]
- 23.Early Treatment Diabetic Retinopathy Study Research Group. Early photocoagulation for diabetic retinopathy. ETDRS report number 9. Ophthalmology. 1991;98((5 Suppl)):766–85. [PubMed] [Google Scholar]
- 24.Singh R, Ramasamy K, Abraham C, Gupta V, Gupta A. Diabetic retinopathy:An update. Indian J Ophthalmol. 2008;56:178–88. [PMC free article] [PubMed] [Google Scholar]
- 25.Sasongko MB, Wardhana FS, Febryanto GA, Agni AN, Supanji S, Indrayanti SR, et al. The estimated healthcare cost of diabetic retinopathy in Indonesia and its projection for 2025. Br J Ophthalmol. 2020;104:487–92. doi: 10.1136/bjophthalmol-2019-313997. [DOI] [PubMed] [Google Scholar]
- 26.Kelly SR, Loiselle AR, Pandey R, Combes A, Murphy C, Kavanagh H, et al. Factors associated with non-attendance in the Irish national diabetic retinopathy screening programme (INDEAR study report no. 2) Acta Diabetol. 2021;58:643–50. doi: 10.1007/s00592-021-01671-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Petersen GB, Byberg S, Vistisen D, Fangel MV, Vorum H, Joensen LE, et al. Factors associated with nonattendance in a nationwide screening program for diabetic retinopathy:A register-based cohort study. Diabetes Care. 2022;45:303–10. doi: 10.2337/dc21-1380. [DOI] [PubMed] [Google Scholar]
- 28.Ellish NJ, Royak-Schaler R, Passmore SR, Higginbotham EJ. Knowledge, attitudes, and beliefs about dilated eye examinations among African-Americans. Invest Ophthalmol Vis Sci. 2007;48:1989–94. doi: 10.1167/iovs.06-0934. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Hipwell AE, Sturt J, Lindenmeyer A, Stratton I, Gadsby R, O'Hare P, et al. Attitudes, access and anguish:A qualitative interview study of staff and patients'experiences of diabetic retinopathy screening. BMJ Open. 2014;4:e005498. doi: 10.1136/bmjopen-2014-005498. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Hartnett ME, Key IJ, Loyacano NM, Horswell RL, Desalvo KB. Perceived barriers to diabetic eye care:Qualitative study of patients and physicians. Arch Ophthalmol. 2005;123:387–91. doi: 10.1001/archopht.123.3.387. [DOI] [PubMed] [Google Scholar]
- 31.Kashim RM, Newton P, Ojo O. Diabetic retinopathy screening:A systematic review on patients'non-attendance. Int J Environ Res Public Health. 2018;15:157. doi: 10.3390/ijerph15010157. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Cushley LN, Curran K, Quinn NB, Bell A, Muldrew A, Graham UM, et al. Diabetic retinopathy screening programme:Attendance, barriers and enablers amongst young people with diabetes mellitus aged 12-26 years. Int J Transl Med. 2021;1:154–62. [Google Scholar]
- 33.Forster AS, Forbes A, Dodhia H, Connor C, Du Chemin A, Sivaprasad S, et al. Non-attendance at diabetic eye screening and risk of sight-threatening diabetic retinopathy:A population-based cohort study. Diabetologia. 2013;56:2187–93. doi: 10.1007/s00125-013-2975-0. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The corresponding author will make the data used in this work accessible upon request.