mp-509
print Print Back Back

Retinal Telescreening for Diabetic Retinopathy

Policy Number: MP-509

 

Latest Review Date: April 2019

Category: Medical                                                                 

Policy Grade: B

Description of Procedure or Service:

Retinopathy screening and risk assessment with digital imaging systems are proposed as an alternative to conventional dilated fundus examination in diabetic individuals. Digital imaging systems use a digital fundus camera to acquire a series of standard field color images and/or monochromatic images of the retina of each eye. Captured digital images may be transmitted via the Internet to a remote center for interpretation by trained readers, storage, and subsequent comparison.

Diabetic Retinopathy

Diabetic retinopathy is the leading cause of blindness among adults aged 20–74 years in the United States. The major risk factors for developing diabetic retinopathy are duration of diabetes and severity of hyperglycemia. After 20 years of disease, almost all patients with Type I and greater than 60% of patients with Type II diabetes will have some degree of retinopathy. Other factors that contribute to the risk of retinopathy include hypertension and elevated serum lipid levels.

Diabetic retinopathy progresses, at varying rates, from asymptomatic, mild nonproliferative abnormalities to proliferative diabetic retinopathy (PDR), with new blood vessel growth on the retina and posterior surface of the vitreous. The two most serious complications for vision are diabetic macular edema and PDR. At its earliest stage (nonproliferative retinopathy), the retina develops microaneurysms, intraretinal hemorrhages, and focal areas of retinal ischemia. With disruption of the blood-retinal barrier, macular retinal vessels become permeable, leading to exudation of serous fluid and lipids into the macula (macular edema). As the disease progresses, retinal blood vessels are blocked, triggering the growth of new and fragile blood vessels (proliferative retinopathy). The new blood vessels that occur in PDR may fibrose and contract, resulting in tractional retinal detachments with significant vision loss. Severe vision loss with proliferative retinopathy arises from vitreous hemorrhage. Moderate vision loss can also arise from macular edema (fluid accumulating in the center of the macula) during the proliferative or nonproliferative stages of the disease. Although proliferative disease is the main cause of blinding in diabetic retinopathy, macular edema is more frequent and is the leading cause of moderate vision loss in people with diabetes.

Screening

There is potential value in screening for diabetic retinopathy because diabetic retinopathy has few visual or ocular symptoms until vision loss develops. Because treatments are primarily aimed at preventing vision loss, and retinopathy can be asymptomatic, it is important to detect disease and begin treatment early in the process. Annual dilated, indirect ophthalmoscopy, coupled with biomicroscopy or 7-standard field stereoscopic 30 degree fundus photography, has been considered the screening technique of choice. Because these techniques require a dedicated visit to a competent eye care professional, typically an ophthalmologist, retinopathy screening is underutilized. This underuse has resulted in the exploration of remote retinal imaging, using film or digital photography, as an alternative to direct ophthalmic examination of the retina.

Treatment

With early detection, diabetic retinopathy can be treated with modalities that can decrease the risk of severe vision loss. Tight glycemic and blood pressure control is the first line of treatment to control diabetic retinopathy, followed by laser photocoagulation for patients whose retinopathy is approaching the high-risk stage. Although laser photocoagulation is effective at slowing the progression of retinopathy and reducing visual loss, it causes collateral damage to the retina and does not restore lost vision. Focal macular edema (characterized by leakage from discrete microaneurysms on fluorescein angiography) may be treated with focal laser photocoagulation, while diffuse macular edema (characterized by generalized macular edema on fluorescein angiography) may be treated with grid laser photocoagulation. Corticosteroids may reduce vascular permeability and inhibit vascular endothelial growth factor production, but are associated with serious adverse events including cataracts and glaucoma, with damage to the optic nerve. Corticosteroids can also worsen diabetes control. Vascular endothelial growth factor inhibitors (e.g., ranibizumab, bevacizumab, pegaptanib), which reduce permeability and block the pathway leading to new blood vessel formation (angiogenesis), are being evaluated for the treatment of diabetic macular edema and PDR.

Digital Photography and Transmission Systems for Retinal Imaging

A number of photographic methods have been evaluated that capture images of the retina to be interpreted by expert readers, who may or may not be located proximately to the patient. Retinal imaging can be performed using digital retinal photographs with (mydriatic) or without (nonmydriatic) dilating of the pupil. One approach is mydriatic standard field 35-mm stereoscopic color fundus photography. Digital fundus photography has also been evaluated as an alternative to conventional film photography. Digital imaging has the advantage of easier acquisition, transmission, and storage. Digital images of the retina can also be acquired in a primary care setting and evaluated by trained readers in a remote location, in consultation with retinal specialists.

Policy:

Retinal telescreening with digital imaging and manual grading of images may be considered medically necessary as a screening technique for the detection of diabetic retinopathy.

Retinal telescreening is considered not medically necessary and investigational for all other indications, including the monitoring and management of disease in individuals diagnosed with diabetic retinopathy.

Key Points:

The most recent literature review was updated through February 6, 2019.

Evidence reviews assess the clinical evidence to determine whether the use of a technology improves the net health outcome. Broadly defined, health outcomes are length of life, quality of life, and ability to function; including benefits and harms. Every clinical condition has specific outcomes that are important to patients and to managing the course of that condition. Validated outcome measures are necessary to ascertain whether a condition improves or worsens; and whether the magnitude of that change is clinically significant. The net health outcome is a balance of benefits and harms.

To assess whether the evidence is sufficient to draw conclusions about the net health outcome of technology, two domains are examined: the relevance and the quality and credibility. To be relevant, studies must represent one or more intended clinical use of the technology in the intended population and compare an effective and appropriate alternative at a comparable intensity. For some conditions, the alternative will be supportive care or surveillance. The quality and credibility of the evidence depend on study design and conduct, minimizing bias and confounding that can generate incorrect findings. The randomized controlled trial (RCT) is preferred to assess efficacy; however, in some circumstances, nonrandomized studies may be adequate. RCTs are rarely large enough or long enough to capture less common adverse events and long-term effects. Other types of studies can be used for these purposes and to assess generalizability to broader clinical populations and settings of clinical practice.

Optometrist or Ophthalmologist Image Interpretation

Clinical Context and Test Purpose

The purpose of retinal telescreening with manual grading of imagesin patients who have diabetes is to inform a decision whether to refer to an ophthalmologist.

The benefit of early treatment of diabetic retinopathy was established in the early 1990's in the large Early Treatment Diabetic Retinopathy Study (ETDRS), which was supported by the National Eye Institute. Local acquisition/remote interpretation technique, with interpretation by skilled readers, was used to consistently detect and evaluate the retinal changes of participants in the study. ETDRS used mydriatic 30° stereoscopic color fundus 35-mm photographs of 7 standard fields evaluated by a single reading center. While 7-field fundus photography with evaluation by a skilled examiner has high sensitivity for diabetic retinopathy detection, its time-consuming nature limits its value as a screening tool. As a result, the use of digital image acquisition, with evaluation of images by an ophthalmologist who may or may not be co-located with the patient, has been evaluated for screening.

The question addressed in this evidence review is: Does digital retinal imaging with manual grading of images improve the net health outcome?

The following PICOTS were used to select literature to inform this review.

Patients

The relevant population of interest are patients with diabetes who are undergoing screening for diabetic retinopathy.

Interventions

The test being considered is digital retinal imaging with manual image interpretation.

The diabetic retinopathy screening recommendations of the American Diabetes Association (2017) are provided in Table 1.

Table 1. Retinopathy Screening Recommendations

Patient Group

First Retinal Examination

Follow-Up

Adults with Type 1 diabetes

Initial dilated and comprehensive eye examination by an ophthalmologist or optometrist beginning 5 y after onset of diabetes

Yearly

Type 2 diabetes

Initial dilated and comprehensive eye examination by an ophthalmologist or optometrist at the time of diagnosis of diabetes

Yearly

Pregnancy in preexisting diabetes

Soon after conception and early in the first trimester

Every 1 to 3 months for severe NPRD or every 3 to 12 months if no to moderate NPRD

NPRD: non proliferative diabetic retinopathy

Adapted from American Diabetes Association (2017).

Comparators

Seven-field fundus photography is considered the criterion standard for the detection of diabetic retinopathy and has sensitivity and specificity superior to direct and indirect ophthalmoscopy by ophthalmologists. Studies from the 1970's established the accuracy of 7-field fundus photography in the detection of diabetic retinopathy. Moss et al (1985) reported on an overall agreement of 85.7% when comparing retinopathy detection by ophthalmoscopy performed by skilled examiners with 7-standard-field stereoscopic 30° fundus photography evaluated by trained readers. Kinyoun et al (1992) found fair-to-good agreement between ophthalmoscopy and evaluation of 7-standard-field stereoscopic 30° fundus photography by the examining ophthalmologist, as well as by trained readers. Analysis of the discordance suggested that conventional ophthalmoscopy could miss up to 50% of microaneurysms, which are some of the earliest manifestations of diabetic retinopathy.

Outcomes

The general outcomes of interest are sensitivity and specificity to detect retinopathy in order to facilitate early treatment and prevent a loss of visual function.

The beneficial outcome of a true-positive test is the early detection of diabetic retinopathy with treatment and preservation of vision. The beneficial outcome of a true-negative test is continued assurance with follow-up scheduled after one year.

A harmful outcome of a false-positive test is unnecessary referral to an ophthalmologist. A harmful outcome of a a false-negative test is delay in treatment potentially resulting in vision loss.

Timing

Comparison with 7-field fundus photography would be immediate. A change in retinopathy can be observed over the period of a year, while a change in vision may occur over several years.

Setting

The setting is outpatient care by a primary care physician or specialist in diabetes or in a community screening program.

Study Selection Criteria

For the evaluation of clinical validity of the test, studies that meet the following eligibility criteria were considered:

  • Reported on the accuracy of the marketed version of the technology (including any algorithms used to calculate scores)
  • Included a suitable reference standard

Review of Evidence

The efficacy of diabetic retinopathy detection with digital image acquisition, compared with 7-field fundus photography, has been evaluated in over 20 studies (total n=1960 patients) and summarized in a systematic review by Shi et al (2015). In pooled analysis, the sensitivity of digital imaging with telemedicine ophthalmologic evaluation for various diabetic retinopathy states was greater than 70%. The pooled specificity of digital imaging for various diabetic retinopathy states was greater than 90%, except for the detection of mild non-proliferative diabetic retinopathy (specificity, 89%; 95% confidence interval [CI], 88% to 91%). Summary receiver operating characteristic curves showed an area under the curve of greater than 0.9 for the detection of diabetic retinopathy and diabetic macular edema, across a range of severity.

 

The 7-field fundus photography technique used in ETDRS, and in some of the studies of digital photography, used dilated pupils. However, screening using undilated pupils has advantages regarding time, cost, and patient compliance. Thus, in addition to the examination technique and the comparison of different photographic techniques, the results of dilated (mydriatic) vs undilated (nonmydriatic) fundus photography have been studied. Bragge et al (2011) conducted a meta-analysis to evaluate variations in qualifications of photographers and mydriatic status. Twenty studies were included that assessed the accuracy of a diabetic retinopathy screening method that used photography- or examination-based retinopathy screening compared with a standard of either 7-field mydriatic photography or dilated fundal examination. In a multivariable logistic regression, variations in mydriatic status alone did not significantly influence sensitivity (odds ratio, 0.89; 95%, CI, 0.56 to 1.41) or specificity (odds ratio=0.94; 95% CI, 0.57 to 1.54).

One 2015 RCT compared the effectiveness of a telemedicine screening program for diabetic retinopathy with traditional surveillance with an eye care professional. The trial randomized 567 adults with diabetes to a telemedicine program (n=296) or traditional surveillance (n=271). After two years of enrollment, those randomized to the traditional surveillance program were offered the opportunity to cross over to telemedicine screening. At 0- to 6-month follow-up, those randomized to the telemedicine program were more likely to undergo retinopathy screening (94.6%) compared with those randomized to traditional surveillance (43.9%; risk difference, 50.7%; 95% CI, 46.6% to 54.8%; p<0.001).

Section Summary: Optometrist or Ophthalmologist Image Interpretation

Data from systematic reviews have demonstrated there is concordance between direct ophthalmoscopy and grading by mydriatic or nonmydriatic photography and remote evaluation. An RCT that compared a telemedicine screening program with traditional surveillance found that patients who were randomized to the telemedicine arm were more likely to undergo screening (95% vs 44%). There is limited direct evidence related to visual outcomes for patients evaluated with a strategy of retinal telescreening. However, given evidence from the EDTRS that early retinopathy treatment improves outcomes, coupled with studies showing high concordance between the screening methods used in ETDRS, and a randomized controlled trial demonstrating higher uptake of screening with a telescreening strategy, a strong chain of evidence can be made that telescreening is associated with improved health outcomes. Digital imaging systems have the additional advantages of short examination time and the ability to perform the test in the primary care physician setting. For individuals who cannot or would not be able to access an eye care professional at the recommended screening intervals, the use of telescreening has a low risk and is very likely to increase the likelihood of retinopathy detection.

Automated Image Interpretation

Clinical Context and Test Purpose

The purpose of digital retinal imaging with automated image interpretationin patients who have diabetes is to inform a decision whether to refer to an ophthalmologist.The telemedicine screening programs (described above) rely on image interpretation by a trained ophthalmologist. A number of automated scoring systems are being evaluated for diabetic retinopathy screening.

The question addressed in this evidence review is: Does digital retinal imaging with automated image interpretation improve the net health outcome?

The following PICOTS were used to select literature to inform this review.

Patients

The relevant population of interestare patients with diabetes who are undergoing screening for diabetic retinopathy.

Interventions

The test being considered isdigital retinal imaging with automated image interpretation. Algorithms for retinal imaging analysis are undergoing rapid evolution. In 2018, the U.S. Food and Drug Administration gave the first marketing clearance for an automated analysis system with artificial intelligence (AI)(IDx-DR)through the De Novo classification process. The IDx-DR was previously known as theIowa Detection Program for Referable Diabetic Retinopathy.

Comparators

Seven-field fundus photography with expert evaluation of images is considered the criterion standard for the detection of diabetic retinopathy.

Outcomes

The general outcomes of interest are the sensitivity, specificity, positive predictive value (PPV) and negative predictive value to detect retinopathy in order to facilitate early treatment and prevent a loss of visual function.

The beneficial outcome of a true-positive test is the early detection of diabetic retinopathy with treatment and preservation of vision. The beneficial outcome of a true-negative test is assurance with scheduling follow-up for oneyear.

The harmful outcome of a false-positive test is unnecessary referral to an ophthalmologist. The harmful outcome of a a false-negative test is delay in treatment potentially resulting in vision loss.

Timing

Comparison with 7-field fundus photography would be immediate. A change in retinopathy can be observed over the period of a year, while a change in vision would occur over several years.

Setting

The setting is outpatient care by a primary care physician or specialist in diabetes.

Study Selection Criteria

For the evaluation of clinical validity of the test, studies that meet the following eligibility criteria were considered:

  • Reported on the accuracy of the marketed version of the technology (including any algorithms used to calculate scores)
  • Included a suitable reference standard

Review of Evidence

The pivotal study of the IDx-DRAI image analysis system was published by Abramoff et al (2018). This was a non-inferiority trial that compared the AI analysis system with expert mydriatic photography and centralized reading of images (see Table 2). Nine hundred patients with diabetes and no history of diabetic retinopathy were enrolled at primary care centers. The primary care staff received four hours of training in image capture and use of the system. The system includes an image quality algorithm, which recommended pupil dilation in 23.6% of patients when 3 attempts at nonmydriatic image capture had failed. Compared to expert mydriatic photography and centralized image assessment, the AI system had sensitivity of 87.2%, specificity of 90.7%,PPV of 74.9% and negative predictive value of 95.7% (see Table 3).

Table 2. Study Characteristics of Clinical Validity

Study

Study Population

Design

Reference Standard

Threshold for Positive Index Test

Timing of Reference and Index Tests

Blinding of Assessors

Comment

Abramoff et al (2018)

900 Patients with diabetes and no history of DR seen at primary care sites

Multicenter prospective non-inferiority design with intent-to-screen

Expert mydriatic photography and centralized image assessment

Diagnostic algorithm based on multiple detectors

Not specifically stated but images appear to be taken at the same time

Yes

23.6% required pupil dilation for adequate image quality

DR: diabetic retinopathy; NR: not reported

Table 3. Clinical Validity

Study

Initial N

Final N

Excluded Samples

Prevalence of Condition

Clinical Validity
(95% Confidence Interval)

Sensitivity

Specificity

PPV

NPV

Abramoff et al (2018)

900

819

33 not evaluable by AI

24.2%

87.2%

(81.8% to 91.2%)

90.7% (88.3% to 92.7%)

74.9% (NR)

95.7% (NR

AI: artificial intelligence; NPV: negative predictive value; NR: not reported; PPV: positive predictive value

Table 4. Study Design and Conduct Gaps

Study

Selectiona

Blindingb

Delivery of Testc

Selective Reportingd

Data Completenesse

Statisticalf

Abramoff et al (2018)

1. confidence intervals for PPV and NPV not reported

PPV: positive predictive value: NPV: negative predictive value.

The evidence gaps stated in this table are those notable in the current review; this is not a comprehensive gaps assessment.

aSelection key: 1. Selection not described; 2. Selection not random or consecutive (i.e., convenience).

bBlinding key: 1. Not blinded to results of reference or other comparator tests.

cTest Delivery key: 1.Timingof delivery of index or reference test not described; 2.Timing of index and comparator tests not same; 3. Procedure for interpreting tests not described; 4.Expertiseof evaluators not described.

dSelective Reporting key: 1. Not registered; 2. Evidence of selective reporting; 3. Evidence of selective publication.

eData Completeness key: 1. Inadequate description of indeterminate and missing samples; 2.Highnumber of samples excluded; 3. High loss to follow-up or missing data.

fStatistical key: 1. Confidence intervalsand/orp values not reported; 2. Comparison to other tests not reported.

 

Section Summary: Automated Image Interpretation

One automated AI system for evaluating diabetic retinopathy in primary care has received De Novo marketing clearance from the U.S. Food and Drug Administration. The pivotal study for this system met its non-inferiority margin compared to expert photography and image evaluation from a centralized site with sensitivity of 87.2% and specificity of 90.7%. ThePPV, which would be an important determinant of the value of a screening method to refer to an ophthalmologist, was not included in the published report, but could be calculated at 74.9%. Further study as the AI system evolves is needed to determine whether the PPV can approach that of an expert evaluator.

Summary of Evidence

For individuals who have diabetes without known diabetic retinopathy who receive digital retinal imaging with optometrist or ophthalmologist image interpretation, the evidence includes systematic reviews and an RCT. The relevant outcomes include test validity, change in disease status, and functional outcomes. Data from systematic reviews have demonstrated there is concordance between direct ophthalmoscopy and grading by mydriatic or nonmydriatic photography and remote evaluation. An RCT that compared a telemedicine screening program with traditional surveillance found that patients who were randomized to the telemedicine arm were more likely to undergo screening (95% vs 44%). There is limited direct evidence related to visual outcomes for patients evaluated with a strategy of retinal telescreening. However, given evidence from the ETDRS that early retinopathy treatment improves outcomes, coupled with studies showing high concordance between the screening methods used in ETDRS, and an RCT demonstrating higher uptake of screening with a telescreening strategy, a strong chain of evidence can be made that telescreening is associated with improved health outcomes. Digital imaging systems have the additional advantages of short examination time and the ability to perform the test in the primary care physician setting. For individuals who cannot or would not be able to access an eye care professional at the recommended screening intervals, the use of telescreening has a low risk and is very likely to increase the likelihood of retinopathy detection. The evidence is sufficient to determine that the technology results in a meaningful improvement in the net health outcome.

For individuals who have diabetes without known diabetic retinopathy who receive digital retinal imaging with automated image interpretation, the evidence includes a prospective study comparing the validity of automated scoring of digital images to remote interpretation. The relevant outcomes include test validity, change in disease status, and functional outcomes. One automated AI system for evaluating diabetic retinopathy in primary care has received De Novo marketing clearance from the U.S. Food and Drug Administration. The pivotal study for this system met its non-inferiority margin compared to expert photography and image evaluation from a centralized site with sensitivity of 87.2% and specificity of 90.7%. ThePPV, which would be an important determinant of the value of a screening method to refer to an ophthalmologist, was not included in the published report, but could be calculated at 74.9%. Further development of this algorithm is needed to increase the clinical validity The evidence is insufficient to determine the effects of the technology on health outcomes.

 

Practice Guidelines and Position Statements

American Diabetes Association

The American Diabetes Association (2017) updated its position statements on standards of medical care for diabetes. Included in the guidelines were specific recommendations for initial and subsequent screening examinations for retinopathy:

  • "Adults with Type 1 diabetes should have an initial eye examination by an ophthalmologist or optometrist within 5 years after the onset of diabetes. (B)"
  • "Patients with Type 2 diabetes should have an initial dilated and comprehensive eye examination by an ophthalmologist or optometrist at the time of the diabetes diagnosis. (B)"
  • "Eye examinations should occur before pregnancy or in the first trimester in patients with preexisting Type 1 or Type 2 diabetes, and then these patients should be monitored every trimester and for 1 year postpartum as indicated by the degree of retinopathy. (B)"
  • "While retinal photography may serve as a screening tool for retinopathy, it is not a substitute for a comprehensive eye exam, which shouldbe performed at least initially and at intervals thereafter as recommended by an eye care professional.(E)"

The American Diabetes Association noted that "Retinal photography, with remote reading by experts, has great potential to provide screening services in areas where qualified eye care professionals are not readily available."

American Academy of Ophthalmology

A preferred practice pattern from the American Academy of Ophthalmology (2017) has provided the following on screening for diabetic retinopathy:

“The purpose of an effective screening program for diabetic retinopathy is to determine who needs to be referred to an ophthalmologist for close follow-up and possible treatment and who may simply be screened annually. Some studies have shown that screening programs using digital retinal images taken with or without dilation may enable early detection of diabetic retinopathy along with an appropriate referral.”

American Telemedicine Association

The American Telemedicine Association (2011) published guidelines on the clinical, technical, and operational performance standards for diabetic retinopathy screening. Recommendations were based on reviews of current evidence, medical literature, and clinical practice. The Association stated that Early Treatment Diabetic Retinopathy Study 30°, stereo 7-standard field, color 35-mm slides are an accepted standard for evaluating diabetic retinopathy. Although no standard criteria have been widely accepted as performance measurements of digital imagery used for diabetic retinopathy evaluation, clinical trials sponsored by the National Eye Institute have transitioned to digital images for diabetic retinopathy assessment. Telehealth programs for diabetic retinopathy should demonstrate an ability to compare favorably with Early Treatment Diabetic Retinopathy Study film or digital photography as reflected in κ values for agreement of diagnosis, false-positive and false-negative readings, positive predictive value, negative predictive value, sensitivity and specificity of diagnosing levels of retinopathy, and macular edema. Inability to obtain or read images should be considered a positive finding, and patients with unobtainable or unreadable images should be promptly reimaged or referred for evaluation by an eye care specialist.

U.S. Preventive Services Task Force Recommendations

The U.S. Preventive Services Task Force (USPSTF) has not addressed screening for retinopathy in patients with diabetes.

Key Words:

Diabetic Retinopathy Detection and Tracking System, DigiScope, Fundus AutoImager, ImageNet Digital Imaging System, Inoveon, IRIS Intelligent Retinal Imaging System, iScan, Visual Pathways, VISUPAC Digital Imaging System.

Approved by Governing Bodies:

Several digital camera and transmission systems (see Table 5 for examples) have been cleared for marketing by the U.S. Food and Drug Administration (FDA) through the 510(k) process and are currently available. In 2018, the FDA gave De Novo clearance for the automated retinal analysis system (IDx-DR) that uses artificial intelligence.

Table 5. Digital Camera and Transmission Systems Cleared by FDA for Retinal Telescreening

Camera and Transmission Systems

Manufacturer

FDA Clearance

Approved

Welch Allyn RetinaVue 100 Imager (RV100)

Welch Allyn

Exempt

IRIS Intelligent Retinal Imaging System™

Ora Inc.

2015

CenterVue Digital Retinography System (DRS)

Welch Allyn

K101935

2010

ImageNet™ Digital Imaging System

Topcon Medical Systems

2008

The Fundus AutoImagerä

Visual Pathways

2002

Zeiss FF450 Fundus Camera and the VISUPACâ Digital Imaging System

Carl Zeiss Meditec

2001

DigiScope®

Eye Tel Imaging with Johns Hopkins Medicine

1999

FDA: Food and Drug Administration.

Table 6. Automated Analysis Systems

Automated Analysis Systems

Manufacturer

Clearance

Approved

IDx-DR Artificial Intelligence Analyzer for the Topcon NW400

IDx, LLC

FDA De Novo

2018

EyeArt(TM)

Eyenuk(TM)

CE

Retmarker

Retmarker

CE

iGradingM

EMIS Health

CE

CE: Conformite Europeenne; FDA: Food and Drug Administration.

Benefit Application:

Coverage is subject to member’s specific benefits. Group specific policy will supersede this policy when applicable.

ITS: Home Policy provisions apply.

FEP: Special benefit consideration may apply. Refer to member’s benefit plan. FEP does not consider investigational if FDA approved and will be reviewed for medical necessity.

Current Coding:

CPT Codes:

92227

Remote imaging for detection of retinal disease (e.g., retinopathy in a patient with diabetes) with analysis and report under physician supervision, unilateral or bilateral

92228

Remote imaging for monitoring and management of active retinal disease (e.g., diabetic retinopathy) with physician review, interpretation and report, unilateral or bilateral

92250

Fundus photography with interpretation and report

92499

Unlisted ophthalmological service or procedure

 

Previous Coding:

0380T Computer-aided animation and analysis of time series retinal images for the monitoring of disease progression, unilateral or bilateral, with interpretation and report (Deleted 12/31/19)

 

References:

  1. Abramoff MD, Folk JC, Han DP et al. Automated analysis of retinal images for detection of referable diabetic retinopathy. JAMA Ophthalmol 2013; 131(3):351-7.

  2. Abramoff, MD, Lavin, PT, Birch, M, Shah, N, Folk, JC. Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary. npj Digital Medicine (2018) 1:39 ; doi:10.1038/s41746-018-0040-6.

  3. Abramoff MD, Lou Y, Erginay A, et al. Improved automated detection of diabetic retinopathy on a publicly available dataset through integration of deep learning. Invest Ophthalmol Vis Sci. Oct 01 2016; 57(13):5200-5206.

  4. American Academy of Ophthalmology Retina Panel. Preferred Practice Pattern® Guidelines. Diabetic Retinopathy. 2008. Available online at: //www.aao.org/ppp.

  5. American Academy of Ophthalmology. American Academy of Ophthalmology Clinical Statement. Screening for diabetic retinopathy. 2006. Available online at: one.aao.org/CE/PracticeGuidelines/ClinicalStatements_Content.aspx?cid=ed55ed3c-b34b-4f10-ae13-09e063d8d773.

  6. American Academy of Ophthalmology. American Academy of Ophthalmology Clinical Statement: Screening for Retinopathy in the Pediatric Patient with Type 1 Diabetes Mellitus. 2008. Available online at: one.aao.org/CE/PracticeGuidelines/ClinicalStatements.aspx.

  7. American Academy of Ophthalmology. Diabetic Retinopathy, Preferred Practice Pattern. September 2008. Available online at: one.aao.org/CE/PracticeGuidelines/PPP_Content.aspx?cid=d0c853d3-219f-487b-a524-326ab3cecd9a.

  8. American Diabetes Association. 9. Microvascular Complications and Foot Care. Diabetes Care. Jan 2016; 39 Suppl 1:S72-80.

  9. American Diabetes Association. Standards of medical care in diabetes--2010. Diabetes Care 2010; 33(Suppl 1):S11-61. Available online at: care.diabetesjournals.org/content/33/Supplement_1/S11.full.pdf+html.

  10. American Telemedicine Association. Telehealth practice recommendations for diabetic retinopathy. 2011. Available online at: www.americantelemed.org/practice/standards/ata-standards-guidelines/telehealth-practice-recommendations-for-diabetic-retinopathy.

  11. An, JJ, Niu, FF, Turpcu, AA, Rajput, YY, Cheetham, TT. Adherence to the American Diabetes Association retinal screening guidelines for population with diabetes in the United States.. Ophthalmic Epidemiol, 2018 Jan 16;25(3).

  12. Bawankar P, Shanbhag N, Smitha KS, et al. Sensitivity and specificity of automated analysis of single-field non-mydriatic fundus photographs by Bosch DR Algorithm-Comparison with mydriatic fundus photography (ETDRS) for screening in undiagnosed diabetic retinopathy. PLoS One. Dec 27 2017; 12(12):e0189854.

  13. Bragge P, Gruen RL, Chau M et al. Screening for Presence or Absence of Diabetic Retinopathy: A Meta-analysis. Arch Ophthalmol 2011; 129(4):435-44.

  14. Cunha, LL, Figueiredo, EE, Araújo, HH, Costa-Cunha, LL, Costa, CC, Neto, JJ, Matos, AA, de Oliveira, MM, Bastos, MM, Monteiro, MM. Non-Mydriatic Fundus Retinography in Screening for Diabetic Retinopathy: Agreement Between Family Physicians, General Ophthalmologists, and a Retinal Specialist.. Front Endocrinol (Lausanne), 2018 Jun 6;9:251.

  15. Delori FC, Gragoudas ES, Francisco R et al. Monochromatic ophthalmoscopy and fundus photography. The normal fundus. Arch Ophthalmol 1977; 95(5):861-8.

  16. Early Treatment Diabetic Retinopathy Study Research Group. Fundus photographic risk factors for progression of diabetic retinopathy. ETDRS report number 12. Ophthalmology 1991; 98(5 Suppl):823-33.

  17. Early Treatment Diabetic Retinopathy Study Research Group. Grading diabetic retinopathy from stereoscopic color fundus photographs--an extension of the modified Airlie House classification. ETDRS report number 10. Early Treatment Diabetic Retinopathy Study Research Group. Ophthalmology 1991; 98(5 Suppl):786-806.

  18. Fenner, BB, Wong, RR, Lam, WW, Tan, GG, Cheung, GG. Advances in Retinal Imaging and Applications in Diabetic Retinopathy Screening: A Review.. Ophthalmol Ther, 2018 Nov 12;7(2).

  19. Fong DS, Aiello L, Gardner TW et al. American Diabetes Association position statement: retinopathy in diabetes. Diabetes Care 2004; 27:S84-S87.

  20. Fransen SR, Leonard-Martin TC, Feuer WJ et al. Clinical evaluation of patients with diabetic retinopathy: accuracy of the Inoveon diabetic retinopathy-3DT system. Ophthalmology 2002; 109(3):595-601.

  21. Garg S, Davis RM. Diabetic retinopathy screening update. Clinical Diabetes 2009; 27(4):140-5. Available online at: clinical.diabetesjournals.org/content/27/4/140.full.

  22. Handelsman Y, Mechanick JI, Blonde L et al. American Association of Clinical Endocrinologists Medical Guidelines for Clinical Practice for developing a diabetes mellitus comprehensive care plan. Endocr Pract 2011; 17 Suppl 2:1-53.

  23. Heaven CJ, Cansfield J, Shaw KM. The quality of photographs produced by the non-mydriatic fundus camera in a screening programme for diabetic retinopathy: a 1 year prospective study. Eye (Lond) 1993; 7 (Pt 6):787-90.

  24. Kinyoun JL, Martin DC, Fujimoto WY et al. Ophthalmoscopy versus fundus photographs for detecting and grading diabetic retinopathy. Invest Ophthalmol Vis Sci 1992; 33(6):1888-93.

  25. Li HK, Horton M, Bursell SE, et al. Telehealth practice recommendations for diabetic retinopathy, second edition. Telemed J E Health. Dec 2011;17(10):814-837.

  26. Liesenfeld B, Kohner E, Piehlmeier W et al. A tele-medical approach to the screening of diabetic retinopathy: digital fundus photography. Diabetes Care 2000; 23(3):345-8.

  27. Mansberger SL, Sheppler C, Barker G, et al. Long-term comparative effectiveness of telemedicine in providing diabetic retinopathy screening examinations: a randomized clinical trial. JAMA Ophthalmol. May 2015; 133(5):518-525.

  28. Mizrachi Y, Knyazer B, Guigui S, et al. Evaluation of diabetic retinopathy screening using a non-mydriatic retinal digital camera in primary care settings in south Israel. Int Ophthalmol. Aug 2014; 34(4):831-837.

  29. Moss SE, Klein R, Kessler SD et al. Comparison between ophthalmoscopy and fundus photography in determining severity of diabetic retinopathy. Ophthalmology 1985; 92(1):62-7.

  30. Murgatroyd H, Ellingford A, Cox A et al. Effect of mydriasis and different field strategies on digital image screening of diabetic eye disease. Br J Ophthalmol 2004; 88(7):920-4.

  31. Oliveira CM, Cristovao LM, Ribeiro ML, et al. Improved automated screening of diabetic retinopathy. Ophthalmologica. 2011; 226(4):191-197.

  32. Peters AL, Davidson MB, Ziel FH. Cost-effective screening for diabetic retinopathy using a nonmydriatic retinal camera in a prepaid health-care setting. Diabetes Care 1993; 16(8):1193-5.

  33. Piyasena, MM, Murthy, GG, Yip, JJ, Gilbert, CC, Peto, TT, Gordon, II, Hewage, SS, Kamalakannan, SS. Systematic review and meta-analysis of diagnostic accuracy of detection of any level of diabetic retinopathy using digital retinal imaging.. Syst Rev, 2018 Nov 9;7(1).

  34. Rajalakshmi, RR, Subashini, RR, Anjana, RR, Mohan, VV. Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence.. Eye (Lond), 2018 Mar 10;32(6).

  35. Rasmussen ML, Broe R, Frydkjaer-Olsen U, et al. Comparison between Early Treatment Diabetic Retinopathy Study 7-field retinal photos and non-mydriatic, mydriatic and mydriatic steered widefield scanning laser ophthalmoscopy for assessment of diabetic retinopathy. J Diabetes Complications. Jan-Feb 2015; 29(1):99-104.

  36. Rudnisky CJ, Hinz BJ, Tennant MT et al. High-resolution stereoscopic digital fundus photography versus contact lens biomicroscopy for the detection of clinically significant macular edema. Ophthalmology 2002; 109(2):267-74.

  37. Sanchez CI, Niemeijer M, Dumitrescu AV, et al. Evaluation of a computer-aided diagnosis system for diabetic retinopathy screening on public data. Invest Ophthalmol Vis Sci. Jun 2011; 52(7):4866-4871.

  38. Scanlon PH, Malhotra R, Thomas G et al. The effectiveness of screening for diabetic retinopathy by digital imaging photography and technician ophthalmoscopy. Diabet Med 2003; 20(6):467-74.

  39. Shi L, Wu H, Dong J, et al. Telemedicine for detecting diabetic retinopathy: a systematic review and meta-analysis. Br J Ophthalmol. Jun 2015; 99(6):823-831.

  40. Solomon, SS, Chew, EE, Duh, EE, Sobrin, LL, Sun, JJ, VanderBeek, BB, Wykoff, CC, Gardner, TT. Diabetic Retinopathy: A Position Statement by the American Diabetes Association.. Diabetes Care, 2017 Feb 23;40(3).

  41. Tennant MT, Greve MD, Rudnisky CJ et al. Identification of diabetic retinopathy by stereoscopic digital imaging via tele-ophthalmology: a comparison to slide film. Can J Ophthalmol 2001; 36(4):187-96.

  42. Tufail A, Kapetanakis VV, Salas-Vega S, et al. An observational study to assess if automated diabetic retinopathy image assessment software can replace one or more steps of manual imaging grading and to determine their cost-effectiveness. Health Technol Assess. Dec 2016; 20(92):1-72.

  43. Tufail A, Rudisill C, Egan C, et al. Automated diabetic retinopathy image assessment software: diagnostic accuracy and cost-effectiveness compared with human graders. Ophthalmology. Dec 23 2016.

  44. Walton OBt, Garoon RB, Weng CY, et al. Evaluation of automated teleretinal screening program for diabetic retinopathy. JAMA Ophthalmol. Dec 17 2015:1-6.

  45. Wong, TT, Sun, JJ, Kawasaki, RR, Ruamviboonsuk, PP, Gupta, NN, Lansingh, VV, Maia, MM, Mathenge, WW, Moreker, SS, Muqit, MM, Resnikoff, SS, Verdaguer, JJ, Zhao, PP, Ferris, FF, Aiello, LL, Taylor, HH. Guidelines on Diabetic Eye Care: The International Council of Ophthalmology Recommendations for Screening, Follow-up, Referral, and Treatment Based on Resource Settings.. Ophthalmology, 2018 May 20;125(10).

Policy History:

Medical Policy Group, October, 2012 (4)

Medical Policy Administration Committee, October 2012

Available for comment October 24 through December 10, 2012

Medical Policy Group, October, 2013 (4): Updated Key Points, added Practice and Position statement, updated References. No changes to the policy statement at this time.

Medical Policy Panel October 2014

Medical Policy Group, October 2014 (1): Update to Key Points and References. No changes in Policy.

Medical Policy Group, November 2015: 2015 Annual Coding update. Added code 0380T to Current Coding.

Medical Policy Panel, April 2016

Medical Policy Group, April 2016 (6): Update to Description, Key Points, Key Words, Approved by Governing Bodies, & References. No change in policy statement.

Medical Policy Panel March 2017

Medical Policy Group, March 2017 (6): Updates to Key points, Governing Bodies, Practice Guidelines and References.

Medical Policy Panel, March 2019

Medical Policy Group, April 2019 (6): Updates to Key Points, Practice Guidelines, Approved by Governing Bodies and References. No change to policy statement.

Medical Policy Group, December 2019 (6): Annual Coding Update, 0380T deleted, added 92499.

This medical policy is not an authorization, certification, explanation of benefits, or a contract. Eligibility and benefits are determined on a case-by-case basis according to the terms of the member’s plan in effect as of the date services are rendered. All medical policies are based on (i) research of current medical literature and (ii) review of common medical practices in the treatment and diagnosis of disease as of the date hereof. Physicians and other providers are solely responsible for all aspects of medical care and treatment, including the type, quality, and levels of care and treatment.

This policy is intended to be used for adjudication of claims (including pre-admission certification, pre-determinations, and pre-procedure review) in Blue Cross and Blue Shield’s administration of plan contracts.

The plan does not approve or deny procedures, services, testing, or equipment for our members. Our decisions concern coverage only. The decision of whether or not to have a certain test, treatment or procedure is one made between the physician and his/her patient. The plan administers benefits based on the member’s contract and corporate medical policies. Physicians should always exercise their best medical judgment in providing the care they feel is most appropriate for their patients. Needed care should not be delayed or refused because of a coverage determination.

As a general rule, benefits are payable under health plans only in cases of medical necessity and only if services or supplies are not investigational, provided the customer group contracts have such coverage.

The following Association Technology Evaluation Criteria must be met for a service/supply to be considered for coverage:

1. The technology must have final approval from the appropriate government regulatory bodies;

2. The scientific evidence must permit conclusions concerning the effect of the technology on health outcomes;

3. The technology must improve the net health outcome;

4. The technology must be as beneficial as any established alternatives;

5. The improvement must be attainable outside the investigational setting.

Medical Necessity means that health care services (e.g., procedures, treatments, supplies, devices, equipment, facilities or drugs) that a physician, exercising prudent clinical judgment, would provide to a patient for the purpose of preventing, evaluating, diagnosing or treating an illness, injury or disease or its symptoms, and that are:

1. In accordance with generally accepted standards of medical practice; and

2. Clinically appropriate in terms of type, frequency, extent, site and duration and considered effective for the patient’s illness, injury or disease; and

3. Not primarily for the convenience of the patient, physician or other health care provider; and

4. Not more costly than an alternative service or sequence of services at least as likely to produce equivalent therapeutic or diagnostic results as to the diagnosis or treatment of that patient’s illness, injury or disease.