Diabetic retinopathy screening using a virtual reading center



To summarize the effects of centralization of diabetic fundus photograph interpretation into a virtual reading center.


In 2016 Kaiser Permanente Northern California, a large, membership-based health plan with an ethnically and racially diverse population, centralized diabetic retinopathy screening into a virtual reading center. Retina screens were based on single field, 45-degree fundus photographs. We compared the accuracy of photography interpretation the year before centralization to the year after using masked reads performed by retina specialists of 1000 randomly selected screens from each time period.


In all, 1902 patient screens with adequate quality images were included in the primary analysis. Images from pre-centralization screens were largely read by ophthalmologists (76.2%), while screens post-centralization were mainly read by optometrists (84.6%). Despite being interpreted by readers with lower levels of professional training, the sensitivity of screening increased from 43.9% (95% CI 38.0–49.8%) to 66.0% (95% CI 60.5–71.4%).


A move to a centralized virtual reading center was associated with improved accuracy of diabetic retinopathy screening.

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  1. 1.

    Lee R, Wong TY, Sabanayagam C (2015) Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss. Eye Vis 2:1–25

    Article  Google Scholar 

  2. 2.

    Ogurtsova K, da Rocha Fernandes JD, Huang Y et al (2017) Global estimates for the prevalence of diabetes for 2015 and 2040. Diabetes Res Clin Pract 128:40–50

    CAS  Article  Google Scholar 

  3. 3.

    Diabetes Report, National Eye Institute (2010) https://nei.nih.gov/eyedata/diabetic. Accessed 29 June 2019

  4. 4.

    Yau JW, Rogers SL, Kawasaki R et al (2012) Global prevalence and major risk factors of diabetic retinopathy. Diabetes Care 35:556–564

    Article  Google Scholar 

  5. 5.

    Wu L, Fernandez-Loiaza P, Sauma J et al (2013) Classification of diabetic retinopathy and diabetic macular edema. World J Diabetes 4:290–294

    Article  Google Scholar 

  6. 6.

    Olayiwola JN, Sobieraj DM, Kulowski K et al (2011) Improving diabetic retinopathy screening through a statewide telemedicine program at a large federally qualified health center. J Health Care Poor Underserved 3:804–816

    Article  Google Scholar 

  7. 7.

    Lin DY, Blumenkranz MS, Brothers R et al (2002) The sensitivity and specificity of single-field nonmydriatic monochromatic digital fundus photography with remote image interpretation for diabetic retinopathy screening: a comparison with ophthalmoscopy and standardized mydriatic color photography. Am J Ophthalmol 134:204–213

    Article  Google Scholar 

  8. 8.

    Wilkinson CP, Ferris FL, Klein RE et al (2003) Global Diabetic Retinopathy Study Group. Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scales. Ophthalmology 9:1677–1682

    Article  Google Scholar 

  9. 9.

    Jones CD, Greenwood RH, Misra A et al (2012) Incidence and progression of diabetic retinopathy during 17 years of a population-based screening program in England. Diabetes Care 35:592–596

    Article  Google Scholar 

  10. 10.

    Agardh E, Poya Tababat-Khani P (2011) Adopting 3-year screening intervals for sight-threatening retinal vascular lesions in Type 2 diabetic subjects without retinopathy. Diabetes Care 34:1318–1319

    Article  Google Scholar 

  11. 11.

    Ku JJY, Landers J, Henderson T et al (2013) The reliability of single-field fundus photography in screening for diabetic retinopathy: The Central Australian Ocular Health Study. Med J Aust 198:93–96

    Article  Google Scholar 

  12. 12.

    Pandit RJ, Taylor R (2002) Quality assurance in screening for sight-threatening diabetic retinopathy. Diabet Med 4:285–291

    Article  Google Scholar 

  13. 13.

    Chin EK, Ventura BV, See KY, Seibles J, Park SS (2014) Nonmydriatic fundus photography for teleophthalmology diabetic retinopathy screening in rural and urban clinics. Telemed J E Health 20:102–108

    Article  Google Scholar 

  14. 14.

    Scanlon PH (2017) Screening intervals for diabetic retinopathy and implications for care. Curr Diabet Rep 17:96

    Article  Google Scholar 

  15. 15.

    Hudson SM, Contreras R, Kanter MH et al (2015) Centralized reading center improves quality in a real-world setting. Ophthalmic Surg Lasers Imaging Retina 46:624–629

    Article  Google Scholar 

  16. 16.

    Chen G, Faris P, Hemmelgarn B, Walker RL, Quan H (2009) Measuring agreement of administrative data with chart data using prevalence unadjusted and adjusted kappa. BMC Med Res Methodol 9:5–12

    Article  Google Scholar 

  17. 17.

    Applied Survey Data Analysis Using SAS 9.4. https://stats.idre.ucla.edu/sas/seminars/sas-survey. Accessed 1 March 2019

  18. 18.

    Mendoza-Herrera K, Quezada AD, Pedroza-Tobias A et al (2017) A diabetic retinopathy screening tool for low-income adults in Mexico. Prev Chronic Dis 14:1–11

    Article  Google Scholar 

  19. 19.

    Williams GA, Scott IU, Haller JA et al (2004) Single field fundus photography for diabetic retinopathy screening. Ophthalmology 111:1055–1062

    Article  Google Scholar 

  20. 20.

    Gulshan V, Peng L, Coram M et al (2016) Development and validation of a deep learning algorithm for detection of diabetic retinopathy in retinal fundus photographs. JAMA 316:2402–2410

    Article  Google Scholar 

  21. 21.

    van der Heijden AA, Abramoff MD, Verbraak F et al (2018) Validation of automated screening for referable diabetic retinopathy with the IDx-DR device in the Hoorn Diabetes Care System. Acta Ophthalmol 96:63–68

    Article  Google Scholar 

  22. 22.

    Sayres R, Taly A, Rahimy E et al (2019) Using a deep learning algorithm and integrated gradients explanation to assist grading for diabetic retinopathy. Ophthalmology 126:552–564

    Article  Google Scholar 

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RBM participated in study design, served as study coordinator, researched the data, and assisted in writing manuscript. SWS participated in reading fundus images, and reviewed manuscript. CC participated in study design, researched data, provided statistical analysis and assisted in writing the manuscript. DT participated in study design, read fundus images, researched the data and wrote the manuscript. DT is the guarantor of this work and takes responsibility for the integrity of the data and accuracy of the data analysis. The study was supported by the Kaiser Permanente (Grant No. RNG 809486) Division of Research 2018 Community Benefit Grant.

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Correspondence to Dariusz Tarasewicz.

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The research was performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. The Kaiser Foundation Research Institutional Review Board approved the study.

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Our study is a retrospective, anonymized, data only project. All results are reported in aggregate. This format was approved by the local IRB and did not require informed consent.

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Melles, R.B., Conell, C., Siegner, S.W. et al. Diabetic retinopathy screening using a virtual reading center. Acta Diabetol 57, 183–188 (2020). https://doi.org/10.1007/s00592-019-01392-9

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  • Diabetic retinopathy screening
  • Virtual technology
  • Health care delivery