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Original Investigation |

Effect of a Teleretinal Screening Program on Eye Care Use and Resources FREE

Joel E. Chasan, MD1; Bill Delaune, PhD2; April Y. Maa, MD1,3; Mary G. Lynch, MD1,3
[+] Author Affiliations
1Department of Ophthalmology, Emory University School of Medicine, Atlanta, Georgia
2Center for Visual and Neurocognitive Rehabilitation, Atlanta, Georgia
3Ophthalmology Section, Atlanta Veterans Affairs Medical Center, Decatur, Georgia
JAMA Ophthalmol. 2014;132(9):1045-1051. doi:10.1001/jamaophthalmol.2014.1051.
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Published online

Importance  Telemedicine is a useful clinical method to extend health care to patients with limited access. Minimal information exists on the subsequent effect of telemedicine activities on eye care resources.

Objective  To evaluate the effect of a community-based diabetic teleretinal screening program on eye care use and resources.

Design, Setting, and Participants  The current study was a retrospective medical record review of patients who underwent diabetic teleretinal screening in the community-based clinics of the Atlanta Veterans Affairs Medical Center from October 1, 2008, through March 31, 2009, and who were referred for an ophthalmic examination in the eye clinic.

Exposures  Clinical medical records were reviewed for a 2-year period after patients were referred from teleretinal screening. The following information was collected for analysis: patient demographics, referral and confirmatory diagnoses, ophthalmology clinic visits, diagnostic procedures, surgical procedures, medications, and spectacle prescriptions.

Main Outcomes and Measures  The accuracy between referring and final diagnoses and the eye care resources that were used in the care of referred patients.

Results  The most common referral diagnoses were nonmacular diabetic retinopathy (43.2%), nerve-related disease (30.8%), lens or media opacity (19.1%), age-related macular degeneration (12.9%), and diabetic macular edema (5.6%). The percentage of agreement among these 5 visually significant diagnoses was 90.4%, with a total sensitivity of 73.6%. Diabetic macular edema required the greatest number of ophthalmology clinic visits, diagnostic tests, and surgical procedures. Using Medicare cost data estimates, the mean cost incurred during a 2-year period per patient seen in the eye clinic was approximately $1000.

Conclusions and Relevance  Although a teleretinal screening program can be accurate and sensitive for multiple visually significant diagnoses, measurable resource burdens should be anticipated to adequately prepare for the associated increase in clinical care.

Figures in this Article

The Veterans Health Administration is the largest integrated health care system in the United States. It serves more than 5.5 million veterans, including more than 97 million outpatient visits.1 To improve access to health care for veterans, a diabetic teleretinal screening program was established in 2006 to screen veterans for diabetic retinopathy within community-based primary care clinics. Retinal cameras are used to capture images, which are remotely interpreted by an eye care professional in a centralized reading center. Patients with findings suggestive of ocular disease are referred for an ophthalmic evaluation in the eye clinic. The diabetic teleretinal screening program has improved the provision of preventive screening care to veterans, with approximately 90% of patients with diabetes mellitus evaluated on a regular basis nationally.1

The ophthalmic care of patients who are referred by a diabetic screening program uses resources at medical centers that include clinic appointments, diagnostic procedures, spectacles, medications, vision rehabilitation, and surgery. Consequently, the establishment of a teleretinal imaging service significantly increases specialty workload in the affiliated eye clinic because, without this service, many veterans might forgo ophthalmic care. To our knowledge, the effect of additional referrals on medical center resources has not been evaluated, and this will be important information as the US Department of Veterans Affairs (VA) contemplates expanding the teleretinal screening program. In addition, teleophthalmology is becoming an important method of health care provision outside the VA. Data on clinical access and resources will be crucial for future planning on a national level. Therefore, this study aimed to evaluate the effect of a community-based diabetic teleretinal screening program on eye care use and resources.

The current study was a retrospective medical record review of patients who underwent diabetic teleretinal screening in the community-based clinics of the Atlanta VA Medical Center from October 1, 2008, through March 31, 2009, and who were referred for an ophthalmic examination in the eye clinic. The data were used to determine the following: (1) the reasons for referral, (2) the agreement between teleretinal reads and face-to-face visits, (3) the resource burden per patient referral for the 2 years after teleretinal imaging, and (4) possible barriers to patient care. Informed consent was not obtained because the project was a retrospective medical record review. All data were collected and stored in a password-protected file on a secure research-only server stored in the VA Medical Center.

Inclusion Criteria

This study received institutional review board approval from the Atlanta VA Medical Center and Emory University and conformed to the requirements of the US Health Insurance Portability and Privacy Act. The Veterans Health Information Systems and Technology Architecture database was used to identify patients who underwent teleretinal imaging from October 1, 2008, through March 31, 2009, to screen for diabetic retinopathy. For those patients who had ocular findings that resulted in a referral to the eye clinic for an ophthalmic examination, the Computerized Patient Record System (CPRS) was retrospectively reviewed.

Demographics

Patient age, sex, race, and home zip code were recorded. Teleretinal imaging notes were reviewed for the referring diagnoses, which were categorized as nonmacular diabetic retinopathy, diabetic macular edema, nerve-related disease, age-related macular degeneration, lens or media opacity, and other. Patients were included in multiple categories if the imaging notes contained more than one referring diagnosis. The CPRS notes were reviewed for patients who were seen in the eye clinic during the subsequent 2 years. Diagnoses were grouped in the same manner as the reason for referral.

Only visually significant and/or sight-threatening diagnoses were included in the study. For example, dry eye without corneal changes and dermatochalasis were excluded. Cataract was included only in cases in which it was a referral diagnosis or in which the patient subsequently underwent cataract surgery.

Accuracy

Teleretinal screening accuracy was determined by the percentage of agreement and sensitivity. The percentage of agreement of the teleretinal imaging program was calculated by comparing the referral diagnosis to the confirmation diagnosis by disease category.2 The percentage of agreement was measured as the number of diagnosis pairs that matched divided by the total number of diagnosis pairs. Sensitivity was calculated for each category by dividing the total number of referral diagnoses confirmed by ophthalmic examination by the number of diagnoses detected on ophthalmic examination. Patients were included in multiple categories if appropriate.

Not all patients who were referred for an ophthalmic examination kept their clinic appointment. For those patients who were not seen at the Atlanta VA Medical Center during the study period, the CPRS was searched for the presence of VA notes outside the study range or non-VA (community) notes. If such notes were available, the diagnoses (eg, long-standing age-related macular degeneration) were collected and added to the final diagnosis list. Study images were marked as unreadable if each set was not adequate to determine the presence or absence of disease. Whether an ocular diagnosis was first detected through the teleretinal screening program was recorded on the basis of clinic notes and patient history.

Resource Burden

We recorded the medical center resources that were used during the 2-year period after referral from teleretinal screening. These resources included the total numbers of clinic visits, diagnostic procedures, spectacles ordered, medications prescribed, and surgical procedures.

Eye evaluation and management codes were estimated by allocating the total number of visits in the following manner: the first visit was considered a new comprehensive eye visit, the second visit was considered an intermediate established eye visit, the third visit was considered an established comprehensive visit, and subsequent visits were considered intermediate established visits.

Resource data were converted to present-day VA monetary cost and relative value units (RVUs) using the standard 2012 Medicare reimbursement and conversion tables and physician fee schedule search tool (http://www.cms.gov/apps/physician-fee-schedule/overview.aspx). The mean cost and RVU workload were then calculated for the number of patients seen in the eye clinic and the number of patients who underwent imaging during primary care. Medication and spectacles were not included in the cost calculations.

Barriers to Care

Data were collected from the Veterans Health Information Systems and Technology Architecture database scheduling menu to identify possible reasons that a patient would fail to keep the ophthalmology clinic appointment. The total number of VA outpatient appointments in the 2 years before teleretinal screening and the total number of times the patient failed to keep an appointment during that same period were collected for all patients referred from a teleretinal screening program. The ratio of outpatient visit no-shows to total outpatient appointments was then calculated. The shortest driving distance between each patient’s home and the medical center was calculated using an online trip calculator (Google Maps) and recorded in miles.

Teleretinal Imaging Protocol

Teleretinal images were obtained using nonmydriatic retinal cameras operated by trained licensed practical nurses in primary care clinics. Most patients had pupillary dilation with a drop each of phenylephrine hydrochloride, 2.5%, and tropicamide, 1%. The screening protocol consisted of 3 wide-angle views of the retina and 1 external photograph. The first retinal photograph was centered on the disc and macula, the second along the superotemporal arcade, and the third over the nasal retina. Photographs were remotely read by eye care professionals, and a report was generated in the CPRS. Patients with an abnormal finding were referred to the local eye clinic for further treatment. The eye care professionals followed a protocol of referral guidelines based on the preferred practice patterns of the American Academy of Ophthalmology.3

Statistical Analysis

Statistical analysis was performed using SPSS statistical software (SPSS Inc).4 Most of the information was summarized descriptively, although some basic exploratory analyses were undertaken to estimate effect size associations among variables.

From October 1, 2008, through March 31, 2009, a total of 1935 veterans underwent diabetic teleretinal screening in the primary care community-based clinics of the Atlanta VA Medical Center (Table 1). Of those screened, 465 (24.0%) were referred to the eye clinic for an ophthalmic examination. Of those referred, 260 (55.9%) underwent an ophthalmic examination within 2 years of the teleretinal screening. Most of the patients were male (98.1%); approximately half of the patients were white and half were black. Ophthalmic notes were available for an additional 66 patients who were not seen at the VA during the study period. These notes were reviewed to document a confirmatory diagnosis but were not included in the resource allocation data collection. Thus, a confirmatory diagnosis was available for 326 (70.1%) of the referred patients.

Table Graphic Jump LocationTable 1.  Patient Demographics and Referral Diagnoses

The most common reasons for referral were nonmacular diabetic retinopathy (43.2%), nerve-related disease (30.8%), lens or media opacity (19.1%), age-related macular degeneration (12.9%), and diabetic macular edema (5.6%). Fifty-five patients (16.9%) had 2 or more concurrent problems that put them at high risk for permanent visual loss (glaucoma, diabetic retinopathy, diabetic macular edema, and age-related macular degeneration).

Two categories showed wide racial disparity: 82.2% of patients with nerve-related disease were African American, and 91.7% of patients with age-related macular degeneration were white. A visually significant condition was detected for the first time through teleretinal screening in 142 patients (43.6%).

Among the 260 patients evaluated in the eye clinic, 42 (16.2%) had visual acuity of 20/70 or worse in at least 1 eye. Five patients (1.9%) were legally blind (visual acuity, <20/200) in both eyes.

The percentage of agreement for all diagnoses was 90.4%, and total sensitivity was 73.6% (Table 2). Images were unreadable for 45 patients referred from teleretinal screening.

Table Graphic Jump LocationTable 2.  Accuracy of Teleretinal Screening in Detecting Diagnosis Categories

Figure 1 shows the mean resource use per patient by primary diagnosis category for the 260 patients who had an ophthalmic examination in the eye clinic during a 2-year period after teleretinal imaging. Overall, 109 patients (41.9%) required only 1 clinic visit, 57 patients (21.9%) required 2 visits, and 94 patients (36.2%) had 3 or more visits. The treatment of diabetic macular edema had the highest resource use. Patients with diabetic macular edema had a mean of 4.96 clinic visits, 5.88 diagnostic procedures, and 2.04 surgical procedures during the 2-year follow-up period.

Place holder to copy figure label and caption
Figure 1.
Eye Care Resource Use by Diagnostic Category for 2 Years After Teleretinal Screening

The bar graph shows the mean resource use per patient by primary diagnosis category for the 260 patients who underwent an ophthalmic examination in the eye clinic during a 2-year period after teleretinal imaging.

Graphic Jump Location

Diagnostic and surgical procedures were further analyzed to determine the specific rate of use for individual procedures as 2 distinct ratios: per patient seen in the eye clinic and per patient undergoing imaging in primary care (Table 3). Other than refraction, the most common diagnostic procedures were visual field testing and macular optical coherence tomography. The most common surgical procedures were cataract extraction with intraocular lens insertion, focal laser, panretinal photocoagulation, and intravitreal injection.

Table Graphic Jump LocationTable 3.  Diagnostic and Surgical Use Ratios

The approximate cost to provide ophthalmic care to this cohort of patients was estimated through Medicare physician fee schedules. The total cost was $251 874.94, with a mean of $968.75 per patient seen in the clinic and $130.17 per patient undergoing imaging in primary care. Diabetic macular edema was the most costly condition to treat (Figure 2). The total workload entailed for ophthalmic care was 4190.48 RVUs, which equaled 16.12 RVUs per patient seen in the clinic.

Place holder to copy figure label and caption
Figure 2.
Mean 2-Year Cost per Patient Seen in the Eye Clinic

The bar graph shows the mean approximate cost to provide ophthalmic care to patients referred from diabetic teleretinal screening as estimated through Medicare physician fee schedules. Diabetic macular edema was the most costly condition to treat.

Graphic Jump Location

Of the 465 patients referred from a teleretinal screening program for an eye examination, 205 (44.1%) were not evaluated in the clinic. Of the referred patients, 101 (21.7%) did not show for the scheduled appointment.

There was a statistically significant difference in the historical no-show rate between patients who kept their appointment and those who did not (F2,462 = 5.369, P = .005, I2 = 0.023, 1-way analysis of variance). A patient who historically missed 26% of their scheduled combined outpatient clinic visits had a nearly 57.7% chance of not showing for the eye clinic visit. There was no statistically significant difference in the age or the mean driving distance for patients who kept their eye clinic appointment vs patients who did not show.

Telehealth technology has been advocated as a method to extend clinical care to remote patient communities. Teleretinal screening has been at the forefront of this initiative. The current study has provided valuable information regarding resource allocation that can be used to prepare for teleretinal expansion. Although previous studies57 have reported that teleretinal screening is generally cost-effective, these studies were based on economic modeling to determine whether a program was monetarily responsible. Our study instead collected information on actual resources used to predict the future burden on a health care system. The mean 2-year cost in Medicare reimbursement fees to care for a patient with an abnormal teleretinal screening result who was seen in the eye clinic was approximately $1000.

The cost of medication and spectacles was not included in the resource burden analyses, which likely led to an underestimation of the total cost burden. With medication and spectacles, the actual cost varies among VA medical centers depending on local policy and contracts. Some medication is considered over the counter in the community and not covered by insurance but might be covered by the VA pharmacy. Similarly, spectacles often are not covered by insurance, but a basic style of spectacles is covered by the VA. Thus, the raw numbers for medication and spectacles were included to allow for some predictive estimates of these important resources.

Other costs inherent in and paid for by the VA health care system, such as parking, security, and information technology, are shared by the entire enterprise and could not be included in this analysis. In addition, the costs incurred by implementing a teleretinal program (eg, cameras, computers, imagers, and readers) were not considered in this analysis of resources needed after a screening visit. Consequently, the total estimate of care determined by the Medicare physician fee schedules does not reflect the total cost to the VA.

Use ratios generated by this study can be used to predict the number of appointment slots, diagnostic tests, and surgical procedures that will be needed to care for patients who are referred for an ophthalmic examination. For example, placing a teleretinal camera in a primary care clinic that serves a population that includes 5000 diabetic patients may generate approximately 1200 referrals to an eye clinic. Assuming that all patients are evaluated with an ophthalmic examination, these referrals might require approximately 544 visual fields, 516 optical coherence tomography images, and 143 cataract extractions during the next 2 years. A sizeable appointment no-show rate for these referrals might adjust these estimates down.

The ratio data obtained from this study may be further expanded using existing actuarial data for populations not screened currently. Combining our data on resource burden with population size and diabetes prevalence should allow decision makers to appropriately expand eye clinic appointments, hire additional personnel, and purchase equipment in anticipation of an increasing patient population.

The findings of the present study add further support to the effectiveness of teleretinal screening for diabetic eye disease.811 Although teleretinal screening has yet to be validated for macula and optic nerve disease, diabetic patients with nondiabetic findings currently are being referred for a clinical examination, and teleretinal screening may be a useful method to detect other ocular conditions. The value of diabetic teleretinal imaging conducted in a primary care setting is high. Of the 326 patients for whom a note was available, 142 patients (43.6%) had an ocular condition detected for the first time through teleretinal screening. Fifty-five of 326 patients (16.9%) had 2 or more concurrent problems that put them at high risk for visual loss (glaucoma, diabetic retinopathy, diabetic macular edema, and age-related macular degeneration). Because many ocular conditions are both progressive and treatable, this form of screening can be effective in identifying patients with ocular disease in order to initiate sight-saving care.

Unfortunately, a high percentage of patients (44.1%) referred for ophthalmic examinations were not evaluated in the eye clinic. Of the 465 patients who were referred for evaluation, 101 (21.7%) failed to show for the scheduled appointment. Failing to show for the appointment puts the patient at risk for delay in care and wastes valuable medical center resources. The current study found that age and travel distance were not significant factors that contributed to the no-show rate. Rather, the patient’s historical no-show rate was the best predictor of whether the patient would keep the eye clinic appointment.

Predictive modeling for eye care will be an important strategy in the management of health care disparity. A major contributor to increased eye care workload in any health care system is the care of a patient with diabetic retinopathy, which is one of the leading causes of preventable blindness.12 The veteran population has a diabetes prevalence of approximately 20%.13 Early detection and treatment of diabetic eye disease lead to a reduction in moderate to severe visual loss14 and may save the federal government hundreds of millions of dollars.7 Our study suggests that teleretinal imaging may also be used to detect other sight-threatening conditions, and the ophthalmic community should be prepared for increased workload and resource use.

The study had a number of limitations. First, all patients were from the Southeastern United States, an area with a high prevalence of diabetes. Second, patients were elderly, with a mean age of 65 years, and male, typical of the VA patient population. It is likely that a younger cohort of patients with diabetes would have a lower prevalence of ocular findings. Consequently, the referral rate from a teleretinal imaging program that involved younger and healthier patients might be lower. However, once the referral rate for that population was established, the resource use rates for referred patients would likely be equivalent to those measured in this study. Third, the study was conducted at a time when the eye clinic at the VA was transitioning from fluorescein angiography to optical coherence tomography as the primary means of following up patients with suspected macular edema. In addition, the surgical care of macular disease was transitioning from primarily laser based to include more intravitreal injections. Consequently, the current rate of optical coherence tomography use and intravitreal injections would likely be higher than what was measured by the study.

Finally, the office visit burden was estimated based on the number of eye clinic visits a patient had during a 2-year period rather than by using specific evaluation and management codes. During the time of teleretinal screening and the subsequent clinical care, all visit codes in the VA system were manually logged and entered into the code capture system by clerks. The electronic health record for eye care with automatic code capture that is now being implemented at the VA was not in use. Thus, at the time of this study, the evaluation and management coding data were not as reliable at the VA as they are now. Visit burden was estimated based on the number of visits for each patient.

Diabetic teleretinal imaging is an effective method to screen patients for sight-threatening conditions. In addition, there are measureable resource burdens that can be anticipated to adequately prepare for the associated increase in clinical care.

Submitted for Publication: August 2, 2013; final revision received September 5, 2013; accepted January 31, 2014.

Corresponding Author: Mary G. Lynch, MD, Ophthalmology Section (112), Atlanta VA Medical Center, 1670 Clairmont Rd, Decatur, GA 30033 (mary.lynch4@va.gov).

Published Online: May 29, 2014. doi:10.1001/jamaophthalmol.2014.1051.

Author Contributions: Drs Lynch and Chasan had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: All authors.

Acquisition, analysis, or interpretation of data: Chasan, Delaune, Lynch.

Drafting of the manuscript: Chasan, Lynch.

Critical revision of the manuscript for important intellectual content: All authors.

Statistical analysis: Chasan, Delaune.

Administrative, technical, or material support: Chasan, Lynch.

Study supervision: Maa, Lynch.

Conflict of Interest Disclosures: None reported.

Disclaimer: The views expressed here are those of the authors and do not necessarily reflect the position or policy of the US Department of Veterans Affairs or the US government.

Additional Contributions: Paul B. Greenberg, MD, Department of Surgery (Ophthalmology), Alpert Medical School of Brown University, and Providence Veterans Affairs Medical Center, Providence, Rhode Island, provided editorial assistance.

Veterans Health Administration. VHA Support Service Center [database online]. Austin, TX: Veterans Health Administration. http://vssc.med.va.gov. Accessed December 12, 2012.
Hunt  RJ.  Percent agreement, Pearson’s correlation, and kappa as measures of inter-examiner reliability. J Dent Res. 1986;65(2):128-130.
PubMed   |  Link to Article
American Academy of Ophthalmology Retina Panel. Preferred Practice Pattern® Guidelines: Diabetic Retinopathy. San Francisco, CA: American Academy of Ophthalmology; 2008.
IBM Corp. IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp; 2012.
Jones  S, Edwards  RT.  Diabetic retinopathy screening: a systematic review of the economic evidence. Diabet Med. 2010;27(3):249-256.
PubMed   |  Link to Article
Whited  JD, Datta  SK, Aiello  LM,  et al.  A modeled economic analysis of a digital tele-ophthalmology system as used by three federal health care agencies for detecting proliferative diabetic retinopathy. Telemed J E Health. 2005;11(6):641-651.
PubMed   |  Link to Article
Javitt  JC, Aiello  LP, Chiang  Y, Ferris  FL  III, Canner  JK, Greenfield  S.  Preventive eye care in people with diabetes is cost-saving to the federal government: implications for health-care reform. Diabetes Care. 1994;17(8):909-917.
PubMed   |  Link to Article
Cavallerano  AA, Cavallerano  JD, Katalinic  P, Tolson  AM, Aiello  LP, Aiello  LM; Joslin Vision Network Clinical Team.  Use of Joslin Vision Network digital-video nonmydriatic retinal imaging to assess diabetic retinopathy in a clinical program. Retina. 2003;23(2):215-223.
PubMed   |  Link to Article
Gómez-Ulla  F, Fernandez  MI, Gonzalez  F,  et al.  Digital retinal images and teleophthalmology for detecting and grading diabetic retinopathy. Diabetes Care. 2002;25(8):1384-1389.
PubMed   |  Link to Article
Kerr  D, Cavan  DA, Jennings  B, Dunnington  C, Gold  D, Crick  M.  Beyond retinal screening: digital imaging in the assessment and follow-up of patients with diabetic retinopathy. Diabet Med. 1998;15(10):878-882.
PubMed   |  Link to Article
Bragge  P, Gruen  RL, Chau  M, Forbes  A, Taylor  HR.  Screening for presence or absence of diabetic retinopathy: a meta-analysis. Arch Ophthalmol. 2011;129(4):435-444.
PubMed   |  Link to Article
Aiello  LP, Gardner  TW, King  GL,  et al.  Diabetic retinopathy. Diabetes Care. 1998;21(1):143-156.
PubMed
Orcutt  J, Avakian  A, Koepsell  TD, Maynard  C.  Eye disease in veterans with diabetes. Diabetes Care. 2004;27(suppl 2):B50-B53.
PubMed   |  Link to Article
Early Treatment Diabetic Retinopathy Study Research Group.  Early photocoagulation for diabetic retinopathy. ETDRS report number 9. Ophthalmology. 1991;98(5)(suppl):766-785.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.
Eye Care Resource Use by Diagnostic Category for 2 Years After Teleretinal Screening

The bar graph shows the mean resource use per patient by primary diagnosis category for the 260 patients who underwent an ophthalmic examination in the eye clinic during a 2-year period after teleretinal imaging.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Mean 2-Year Cost per Patient Seen in the Eye Clinic

The bar graph shows the mean approximate cost to provide ophthalmic care to patients referred from diabetic teleretinal screening as estimated through Medicare physician fee schedules. Diabetic macular edema was the most costly condition to treat.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1.  Patient Demographics and Referral Diagnoses
Table Graphic Jump LocationTable 2.  Accuracy of Teleretinal Screening in Detecting Diagnosis Categories
Table Graphic Jump LocationTable 3.  Diagnostic and Surgical Use Ratios

References

Veterans Health Administration. VHA Support Service Center [database online]. Austin, TX: Veterans Health Administration. http://vssc.med.va.gov. Accessed December 12, 2012.
Hunt  RJ.  Percent agreement, Pearson’s correlation, and kappa as measures of inter-examiner reliability. J Dent Res. 1986;65(2):128-130.
PubMed   |  Link to Article
American Academy of Ophthalmology Retina Panel. Preferred Practice Pattern® Guidelines: Diabetic Retinopathy. San Francisco, CA: American Academy of Ophthalmology; 2008.
IBM Corp. IBM SPSS Statistics for Windows, Version 21.0. Armonk, NY: IBM Corp; 2012.
Jones  S, Edwards  RT.  Diabetic retinopathy screening: a systematic review of the economic evidence. Diabet Med. 2010;27(3):249-256.
PubMed   |  Link to Article
Whited  JD, Datta  SK, Aiello  LM,  et al.  A modeled economic analysis of a digital tele-ophthalmology system as used by three federal health care agencies for detecting proliferative diabetic retinopathy. Telemed J E Health. 2005;11(6):641-651.
PubMed   |  Link to Article
Javitt  JC, Aiello  LP, Chiang  Y, Ferris  FL  III, Canner  JK, Greenfield  S.  Preventive eye care in people with diabetes is cost-saving to the federal government: implications for health-care reform. Diabetes Care. 1994;17(8):909-917.
PubMed   |  Link to Article
Cavallerano  AA, Cavallerano  JD, Katalinic  P, Tolson  AM, Aiello  LP, Aiello  LM; Joslin Vision Network Clinical Team.  Use of Joslin Vision Network digital-video nonmydriatic retinal imaging to assess diabetic retinopathy in a clinical program. Retina. 2003;23(2):215-223.
PubMed   |  Link to Article
Gómez-Ulla  F, Fernandez  MI, Gonzalez  F,  et al.  Digital retinal images and teleophthalmology for detecting and grading diabetic retinopathy. Diabetes Care. 2002;25(8):1384-1389.
PubMed   |  Link to Article
Kerr  D, Cavan  DA, Jennings  B, Dunnington  C, Gold  D, Crick  M.  Beyond retinal screening: digital imaging in the assessment and follow-up of patients with diabetic retinopathy. Diabet Med. 1998;15(10):878-882.
PubMed   |  Link to Article
Bragge  P, Gruen  RL, Chau  M, Forbes  A, Taylor  HR.  Screening for presence or absence of diabetic retinopathy: a meta-analysis. Arch Ophthalmol. 2011;129(4):435-444.
PubMed   |  Link to Article
Aiello  LP, Gardner  TW, King  GL,  et al.  Diabetic retinopathy. Diabetes Care. 1998;21(1):143-156.
PubMed
Orcutt  J, Avakian  A, Koepsell  TD, Maynard  C.  Eye disease in veterans with diabetes. Diabetes Care. 2004;27(suppl 2):B50-B53.
PubMed   |  Link to Article
Early Treatment Diabetic Retinopathy Study Research Group.  Early photocoagulation for diabetic retinopathy. ETDRS report number 9. Ophthalmology. 1991;98(5)(suppl):766-785.
PubMed   |  Link to Article

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