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Original Investigation |

Eye Care Availability and Access Among Individuals With Diabetes, Diabetic Retinopathy, or Age-Related Macular Degeneration FREE

Diane M. Gibson, PhD1
[+] Author Affiliations
1School of Public Affairs, Baruch College—City University of New York, New York, New York
JAMA Ophthalmol. 2014;132(4):471-477. doi:10.1001/jamaophthalmol.2013.7682.
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Published online

Importance  Understanding whether differences in the local availability of eye care professionals are related to differences in realized access to eye care is important for assessing whether and where public health efforts are needed to increase access to eye care professionals.

Objective  To examine whether the county-level availability of ophthalmologists and optometrists is associated with measures of realized access to eye care for individuals with diabetes mellitus, diabetic retinopathy, or age-related macular degeneration (ARMD).

Design, Setting, and Participants  We studied a cross-sectional sample of US adults 40 years and older (1098 individuals with diabetes, 345 with diabetic retinopathy, and 498 with ARMD) from the 2005-2008 National Health and Nutrition Examination Survey.

Main Outcomes and Measures  Outcomes were whether diabetic individuals reported undergoing a dilated eye examination in the past year, whether individuals were unaware they had diabetic retinopathy, whether diabetic individuals had vision-threatening diabetic retinopathy, and whether individuals were unaware they had ARMD.

Results  In logistic regression models that also included individual characteristics, individuals who lived in a county in the highest ophthalmologist availability quartile were less likely to be unaware they had diabetic retinopathy (predictive margin [PM], 66.1%; 90% CI, 48.8%-83.4%; vs PM, 84.1%; 90% CI, 78.7%-89.6%) and were less likely to have vision-threatening diabetic retinopathy (PM, 1.4%; 90% CI, 0.9%-1.9%; vs PM, 2.6%; 90% CI, 1.8%-3.4%) than individuals who lived in a county in the lower 3 ophthalmologist availability quartiles. Individuals who lived in a county in the lowest ophthalmologist availability quartile were more likely to be unaware they had ARMD (PM, 93.8%; 90% CI, 90.6%-97.0%; vs PM, 88.3%; 90% CI, 84.7%-91.9%) than individuals who lived a county in the higher 3 ophthalmologist availability quartiles. Optometrist availability quartiles were not significantly related to any of the outcomes.

Conclusions and Relevance  The results suggest that efforts to increase access to ophthalmologists to improve outcomes related to diabetic retinopathy or to increase awareness of ARMD should focus on improving access for diabetic individuals who live in counties in the lowest 3 quartiles of ophthalmologist availability and on individuals at risk of ARMD who live in counties in the lowest quartile of ophthalmologist availability.

Realized access to eye care has been defined as the use of eye care services and the visual health outcomes and patient satisfaction that result from the use of care.1 Understanding whether differences in the local availability of eye care professionals are related to differences in realized access to eye care is important for assessing whether and where public health efforts are needed to increase access to eye care professionals.1 This article examines whether the county-level availability of ophthalmologists and optometrists is associated with measures of realized access to eye care for individuals with diabetes mellitus, diabetic retinopathy, or age-related macular degeneration (ARMD).

Diabetic retinopathy and ARMD are 2 of the most common eye diseases in the United States, and both conditions can progress to cause severe visual impairment.26 Estimates for US individuals aged 40 years or older are that 28% to 40% of individuals with diabetes have diabetic retinopathy, 6.5% of individuals have ARMD, and 73% of individuals with diabetic retinopathy and 84% of individuals with ARMD are not aware that they have the condition.3,4,7,8 Effective treatments exist for some stages of these diseases, making it important that individuals at risk of these conditions or who already have these conditions receive regular eye care.918

The conceptual model of access to eye care developed by Zhang et al1 assumes that the use of eye care services is influenced by an individual’s “predisposing,” “enabling,” and “need” characteristics and by contextual characteristics, such as the local availability of eye care professionals. Knowledge of a vision condition and disease severity may also be related to the local availability of eye care professionals. For example, it may be more difficult to find eye care professionals with expertise in the diagnosis of retinal diseases or to receive expert treatment promptly in areas with a more limited availability of eye care professionals.

Previous research on the association between the local availability of eye care professionals and realized access to care has used Medicare claims data.19,20 Sloan et al19 found that the combined number of ophthalmologists and optometrists per capita in the metropolitan area or county in which an individual resided was associated with significantly increased odds that an individual with ARMD had an eye examination during a 15-month period but was not significantly related to the likelihood an individual with diabetes had an eye examination during a 15-month period. Wang and Javitt20 found that the number of ophthalmologists per capita but not the number of optometrists per capita in an individual’s county of residence was associated with significantly increased odds that diabetic individuals visited a physician for any kind of eye care during a 2-year period.

This article builds on the previous research by considering the association between the local availability of eye care professionals and a set of outcomes that measure various dimensions of realized access to eye care. These outcomes include the frequency of dilated eye examinations for diabetic individuals with and without retinopathy, the likelihood an individual with diabetic retinopathy or ARMD is unaware of the condition, and the severity of diabetic retinopathy. In addition, this article uses a sample of individuals 40 years and older rather than a sample limited to Medicare beneficiaries.

Sample

The City University of New York institutional review board determined that this investigation was exempt from institutional review board approval. Data from the 2005-2008 National Health and Nutrition Examination Survey (NHANES) on individuals 40 years and older were used in the empirical analyses. The NHANES collects data through interviews, physical examinations, and laboratory tests. The samples are designed to be nationally representative of the US noninstitutionalized civilian population.21

The physical examination component of the 2005-2008 NHANES included retinal imaging for individuals 40 years and older. Two nonmydriatic digital images per eye were taken. The images were graded at the University of Wisconsin using standard protocols for diabetic retinopathy and ARMD.2224 Of the 5828 individuals who participated in the retinal examination, there was information on the retinopathy status of 5704 individuals and the ARMD status of 5604 individuals. Zhang et al4 and Klein et al7 describe reasons for missing diabetic retinopathy or ARMD status.

Sample of Diabetic Individuals

Individuals were asked in the NHANES interview, “Other than during pregnancy, have you ever been told by a doctor or health professional that you have diabetes or sugar diabetes?” Individuals who responded yes to this question or who had a hemoglobin A1c level greater than 6.5% (to convert to proportion of total hemoglobin, multiply by 0.01) were defined as having diabetes.4,25 The sample of diabetic individuals was composed of 1098 individuals with diabetes with information on diabetic retinopathy status.

Samples of Diabetic Individuals and Sample of Individuals With ARMD

The sample of individuals with diabetes was divided into 2 subsamples: those with signs of retinopathy in one or both eyes (n = 345) and those without retinopathy (n = 753).4,25 Gibson8 describes the clinical findings used to define diabetic retinopathy and ARMD. The stage of diabetic retinopathy was categorized as mild nonproliferative, moderate nonproliferative, or vision-threatening.4,2628 The ARMD sample was composed of 498 individuals who had signs of ARMD in one or both eyes. The stage of ARMD was categorized as early or late.7

Outcomes
Dilated Eye Examination in the Past Year

Annual dilated eye examinations are recommended for all diabetic individuals.9 Self-reported diabetic individuals were asked, “When was the last time you had an eye exam in which the pupils were dilated? This would have made you temporarily sensitive to bright light.” An indicator variable was created for reporting undergoing a dilated eye examination in the past year. This variable was set equal to zero for respondents who were unaware of their diabetes status.

Unawareness of Diabetic Retinopathy and ARMD

Self-reported diabetic individuals were asked, “Has a doctor ever told you that diabetes has affected your eyes or that you had retinopathy?” Individuals with diabetic retinopathy were defined as being unaware of their diabetic retinopathy if they responded no or don’t know to this question or if they were unaware of their diabetes.

Individuals 40 years and older were asked in the interview, “Have you ever been told by a doctor that you have age-related macular degeneration?” Individuals with ARMD were defined as being unaware of their ARMD if they responded no or don’t know to this question.

Vision-Threatening Diabetic Retinopathy

An indicator variable was created for whether an individual with diabetes had vision-threatening diabetic retinopathy.

Explanatory Variables
Measurement of the Local Availability of Eye Care Professionals

Information on the number of ophthalmologists and optometrists in each US county is available from the Area Health Resource Files.29 A respondent’s ophthalmologist availability was defined using the number of “patient care” ophthalmologists in the respondent’s county of residence in the year corresponding to the NHANES survey year. A respondent’s optometrist availability was defined using the number of optometrists in the respondent’s county of residence in 2009, the closest year of optometrist data available in the Area Health Resource Files to the 2005-2008 NHANES survey years. Separate county-level variables were created for the number of ophthalmologists per 100 000 county residents and the number of optometrists per 100 000 county residents. County population was drawn from the 2005-2009 American Community Survey 5-year estimates.

Population-weighted quartiles of county-level ophthalmologist and optometrist availability were defined using data on all of the counties in the United States. To create the quartile definitions, ophthalmologist numbers were drawn from 2008 and optometrist numbers were drawn from 2009. Quartiles were defined so that each quartile contained 25% of the US population. The quartile definitions for ophthalmologists per 100 000 county residents are as follows: low, 3.0 or less; medium-low, greater than 3.0 to 5.4; medium-high, greater than 5.4 to 7.5; and high, greater than 7.5. The quartile definitions for optometrists per 100 000 county residents are as follows: low, 10.8 or less; medium-low, greater than 10.8 to 14.0; medium-high, greater than 14.0 to 17.2; and high, greater than 17.2. Indicator variables were created for each of the ophthalmologist and optometrist quartiles.

Other Explanatory Variables

A large set of variables was used to measure an individual’s predisposing, enabling, and need characteristics, including measures of socioeconomic status and race/ethnicity.1,8 These variables include age (40-64 years, 65-79 years, or ≥80 years), sex, race/ethnicity (white non-Hispanic, black non-Hispanic, Hispanic, or other race/ethnicity), family size, educational attainment (less than high school, high school or general equivalency diploma, or more than high school), marital status (married or unmarried), whether a language other than English was the primary language spoken at home, total family income in the previous calendar year divided by the poverty threshold appropriate to the individual’s family size (lower income, <1.5; middle income, ≥1.5 and <3; higher income, ≥3; or missing), whether the individual had health insurance, and whether the individual received routine health care from a physician or a health maintenance organization.

Statistical Analysis

Descriptive statistics and logistic regression models were estimated taking into account the complex design features of the NHANES. As in previous research using 2005-2008 NHANES retinal examination data, unadjusted NHANES physical examination weights were used in the analyses.4,7,8 Taylor series linearization was used for variance estimation.30

A recent article by Ioannidis et al31 reports that the optimal choice of type I and type II errors varies with sample size and plausible effect size. Taking the sample sizes of the current study and assuming modest effect sizes, Ioannidis et al31 found that the optimal value of α ranges from .072 to .180, with corresponding values of β ranging from .087 to .260 under their additive model. An α value of .10 was used in this article because it falls in the range suggested by Ioannidis et al,31 and it is a commonly used significance level. Accordingly, associations were considered to be significant at P ≤ .10.

Descriptive statistics for the outcome and eye care professional variables were calculated for the 4 samples. Zhang et al4 and Gibson8 report descriptive statistics for each sample for the individual characteristics used in the analyses. Descriptive statistics were calculated within the samples by whether diabetic individuals with and without retinopathy reported undergoing a dilated eye examination in the past year, whether individuals with diabetic retinopathy were aware of the condition, whether diabetic individuals had vision-threatening diabetic retinopathy, and whether individuals with ARMD were aware of the condition. Differences in characteristics among the groups were tested using Pearson design-based F statistics for percentages and t tests for means.

Logistic regression models of undergoing an eye examination in the past year were estimated using the diabetic retinopathy sample and separately using the sample of diabetic individuals without retinopathy. Logistic regression models of unawareness of diabetic retinopathy and unawareness of ARMD were estimated using the diabetic retinopathy and the ARMD samples, respectively. Logistic regression models of having vision-threatening diabetic retinopathy were estimated using the sample of diabetic individuals. Three main models were estimated for each outcome. Model 1 included the number of ophthalmologists and the number of optometrists per capita in the respondent’s county. To test for nonlinearities in the association between eye care professional availability and the outcomes, model 2 included indicator variables for the highest ophthalmologist availability quartile and the highest optometrist availability quartile, and model 3 included indicator variables for the lowest ophthalmologist availability quartile and the lowest optometrist availability quartile. All the models included the individual predisposing, enabling, and need variables described above. Indicator variables for moderate nonproliferative diabetic retinopathy and vision-threatening diabetic retinopathy were included in the models of dilated eye examination receipt for the diabetic retinopathy sample and unawareness of diabetic retinopathy. An indicator variable for late ARMD was included in the model of unawareness of ARMD. Measures of diabetes duration and current insulin use were also included in the models of diabetic retinopathy–related outcomes. Predictive margins (PMs), odds ratios (ORs), and 90% CIs were calculated.

Descriptive Statistics

Table 1 presents descriptive statistics for the outcome and eye care professional variables for the 4 samples. A total of 61.8% of individuals with diabetic retinopathy and 47.0% of diabetic individuals without retinopathy reported undergoing a dilated eye examination in the past year. A total of 73.1% of the diabetic retinopathy sample was unaware of their diabetic retinopathy, and 83.8% of the ARMD sample was unaware of their ARMD. A total of 4.9% of the sample of diabetic individuals had vision-threatening diabetic retinopathy. Across the 4 samples, the mean number of ophthalmologists per 100 000 county residents ranged from 4.0 to 4.3, and the mean number of optometrists per 100 000 county residents ranged from 13.7 to 13.9.

Table Graphic Jump LocationTable 1.  Measures of Realized Access to Eye Care and Eye Care Professional Availability for Diabetic Individuals With and Without Diabetic Retinopathy and Individuals With ARMD, NHANES, 2005-2008

The only significant differences in eye care professional variables by differences in outcome variables were for the sample of diabetic individuals (results not shown). Differences were found by vision-threatening diabetic retinopathy status (yes or no) in the percentage of the subsample who lived in a county in the lowest optometrist availability quartile (38.0 vs 25.0, P = .048) and the percentage who lived in a county in the medium-high optometrist availability quartile (18.0 vs 30.0, P = .07).

Regression Analyses

Table 2 presents the results of model 1. The number of ophthalmologists per 100 000 county residents was associated with significantly higher odds of undergoing a dilated eye examination in the past year for diabetic individuals without retinopathy (OR, 1.05; 90% CI, 1.01-1.10), significantly lower odds of unawareness of diabetic retinopathy (OR, 0.92; 90% CI, 0.84-0.99), and significantly lower odds of unawareness of ARMD (OR, 0.94; 90% CI, 0.88-0.99). The number of ophthalmologists was not significantly related to the likelihood of having vision-threatening diabetic retinopathy. The number of optometrists per 100 000 county residents was not significantly related to any of the outcomes.

Table Graphic Jump LocationTable 2.  Multiple Logistic Regression Models of Measures of Realized Access to Eye Care, NHANES, 2005-2008a

Table 2 also presents the results of models 2 and 3. Individuals who lived in a county in the highest ophthalmologist availability quartile were significantly less likely to be unaware they had diabetic retinopathy (PM, 66.1%; 90% CI, 48.8%-83.4%; vs PM, 84.1%; 90% CI, 78.7%-89.6%) and were significantly less likely to have vision-threatening diabetic retinopathy (PM, 1.4%; 90% CI, 0.9%-1.9%; vs PM, 2.6%; 90% CI, 1.8%-3.4%) than individuals who lived in a county in the lower 3 ophthalmologist availability quartiles. Individuals who lived in a county in the lowest ophthalmologist availability quartile were significantly more likely to be unaware they had ARMD (PM, 93.8%; 90% CI, 90.6%-97.0%; vs PM, 88.3%; 90% CI, 84.7%-91.9%) than individuals who lived a county in the higher 3 ophthalmologist availability quartiles. Optometrist availability quartiles were not significantly related to any of the outcomes.

This study found that the local availability of ophthalmologists was positively associated with measures of realized access to eye care for individuals with diabetes, diabetic retinopathy, and ARMD. These associations were significant in models that included a large set of individual characteristics, including measures of socioeconomic status and race/ethnicity. No significant associations were found between the local availability of optometrists and the measures of realized access to eye care. Similarly, Wang and Javitt20 found that the county-level availability of ophthalmologists but not optometrists was associated with increased odds of receiving eye care among diabetic individuals.

In a survey of primary care physicians in Indiana, Lazaridis et al32 found that 89.8% of the physicians referred their patients with diabetes mainly to ophthalmologists rather than optometrists. Guidelines for primary care physicians focus on referring patients with signs of ARMD to ophthalmologists.33 Data from a workforce survey conducted in 1999 indicated that approximately 10% of optometric visits (11 million visits) were devoted to disease management or treatment.34 These findings suggest that most optometrists devote a small fraction of their practice to the care of patients with diabetes or ARMD, which may explain the lack of an association between optometrist availability and the outcomes considered in this article.

The results suggest that public health efforts to increase access to ophthalmologists to improve outcomes related to diabetic retinopathy or to increase awareness of ARMD should focus on improving access for diabetic individuals who live in counties in the lowest 3 quartiles of ophthalmologist availability and on individuals at risk of ARMD who live in counties in the lowest quartile of ophthalmologist availability. The next issue to discuss is how access to ophthalmologists could be increased in target areas. Lee et al35 conclude that increasing the number of ophthalmology training positions is not an effective short-term solution for increasing the supply of ophthalmologists. They estimate that it would take more than 20 years for a 20% increase in ophthalmology training positions to result in a 10% increase in the number of ophthalmologists in practice. In addition, this approach would not address the uneven distribution of ophthalmologists across the country.

Finding new ways to use existing excess ophthalmologist capacity is likely to be a more promising approach. Lee et al35 reported that 52% of ophthalmologists in a representative sample of US ophthalmologists indicated that they were interested in increasing their patient volume by 33% or more. Telemedicine could be used to connect potential patients in underserved areas with ophthalmologists. Telemedicine using digital retinal images that are evaluated remotely by ophthalmologists has been found to be an effective tool for screening for both diabetic retinopathy and ARMD.27,3639 Screening for diabetic retinopathy via telemedicine has also been found to be cost-effective.28,36,37 The cost-effectiveness of screening for ARMD via telemedicine has not been evaluated.38 Whether telemedicine could be used successfully as a tool in the management of these conditions has not been investigated extensively, although early research suggests that it holds promise.40,41

The mean county-level density of optometrists was greater than that of ophthalmologists, and previous research indicates that many optometrists have excess capacity.34 Increasing the use of a “shared care” model where chronic eye diseases are managed jointly by ophthalmologists and optometrists in at-risk areas could potentially take advantage of excess optometrist capacity and relieve some of the need for ophthalmologists.42,43

This study is subject to several limitations. First, it was not possible to obtain information on the number of ophthalmologists and optometrists located in a geographic area smaller than a county. The county-level density of eye care professionals may not represent accurately a given individual’s experience of the availability of eye care professionals. Second, data on optometrist availability were drawn from 2009. This means that the optometrist availability of NHANES respondents could be measured with error. Third, although appropriately weighted NHANES data are demographically nationally representative of the US noninstitutionalized civilian population, the sample is not geographically representative of the entire country. It is possible that the associations found between eye care professional availability and visual health outcomes would differ with a geographically representative sample.

It has been estimated that in the United States there are 25.6 million individuals 20 years and older with diabetes, 4.2 million individuals 40 years and older with diabetic retinopathy, and 7.2 million individuals 40 years and older with ARMD.4,7,44 Adequate access to ophthalmologists is necessary to ensure that this large number of individuals at high risk of and already affected by diabetic retinopathy or ARMD have the best visual health outcomes possible. Using telemedicine to take advantage of existing excess ophthalmologist capacity and increasing shared-care partnerships between ophthalmologists and optometrists may provide a way to improve realized access to eye care in areas with limited local availability of ophthalmologists.

Submitted for Publication: July 26, 2013; final revision received October 2, 2013; accepted October 14, 2013.

Corresponding Author: Diane M. Gibson, PhD, School of Public Affairs, Baruch College—City University of New York, 17 Lexington Ave, PO Box D-901, New York, NY 10010 (diane.gibson@baruch.cuny.edu).

Published Online: January 23, 2014. doi:10.1001/jamaophthalmol.2013.7682.

Author Contributions: Dr Gibson had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Gibson.

Acquisition of data: Gibson.

Analysis and interpretation of data: Gibson.

Drafting of the manuscript: Gibson.

Critical revision of the manuscript for important intellectual content: Gibson.

Statistical analysis: Gibson.

Obtained funding: Gibson.

Conflict of Interest Disclosures: None reported.

Funding/Support: This research was supported by grant 64099-00 42 from The City University of New York Professional Staff Congress–City University of New York Research Award Program (Dr Gibson).

Role of the Sponsor: The funding source had no role in the design and conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Disclaimer: The findings and conclusions in this article are those of the author and do not necessarily represent the views of the NCHS, Centers for Disease Control and Prevention.

Additional Information: The use of restricted-access data for this project was approved by the National Center for Health Statistics (NCHS), Centers for Disease Control and Prevention. All results presented in the article have been cleared for release by the NCHS Research Data Center.

Additional Contributions: Gerald Cubbin, PhD, provided helpful suggestions for improving the article.

Zhang  X, Andersen  R, Saaddine  JB, Beckles  GL, Duenas  MR, Lee  PP.  Measuring access to eye care. Ophthalmic Epidemiol. 2008;15(6):418-425.
PubMed   |  Link to Article
Congdon  N, O’Colmain  B, Klaver  CC,  et al; Eye Diseases Prevalence Research Group.  Causes and prevalence of visual impairment among adults in the United States. Arch Ophthalmol. 2004;122(4):477-485.
PubMed   |  Link to Article
Kempen  JH, O’Colmain  BJ, Leske  MC,  et al; Eye Diseases Prevalence Research Group.  The prevalence of diabetic retinopathy among adults in the United States. Arch Ophthalmol. 2004;122(4):552-563.
PubMed   |  Link to Article
Zhang  X, Saaddine  JB, Chou  CF,  et al.  Prevalence of diabetic retinopathy in the United States, 2005-2008. JAMA. 2010;304(6):649-656.
PubMed   |  Link to Article
Klein  R, Klein  B. Vision disorders in diabetes. In: National Diabetes Data Group, ed. Diabetes in America.2nd ed. Bethesda, MD: National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases; 1995:293-297.
Friedman  DS, O’Colmain  BJ, Muñoz  B,  et al; Eye Diseases Prevalence Research Group.  Prevalence of age-related macular degeneration in the United States. Arch Ophthalmol. 2004;122(4):564-572.
PubMed   |  Link to Article
Klein  R, Chou  CF, Klein  BE, Zhang  X, Meuer  SM, Saaddine  JB.  Prevalence of age-related macular degeneration in the US population. Arch Ophthalmol. 2011;129(1):75-80.
PubMed   |  Link to Article
Gibson  DM.  Diabetic retinopathy and age-related macular degeneration in the U.S. Am J Prev Med. 2012;43(1):48-54.
PubMed   |  Link to Article
American Academy of Ophthalmology. Preferred Practice Pattern: Diabetic Retinopathy. San Francisco, CA: American Academy of Ophthalmology; 2008.
American Academy of Ophthalmology. Preferred Practice Pattern: Age-Related Macular Degeneration. San Francisco, CA: American Academy of Ophthalmology; 2008.
The Diabetes Control and Complications Trial Research Group.  The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993;329(14):977-986.
PubMed   |  Link to Article
UK Prospective Diabetes Study Group.  Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38. BMJ. 1998;317(7160):703-713.
PubMed   |  Link to Article
Avery  RF, Pearlman  J, Pieramici  DJ,  et al.  Intravitreal bevacizumab (Avastin) in the treatment of proliferative diabetic retinopathy .Ophthalmology. 2006;113(10):1695.e1-1695.15.
PubMed
Bressler  NM, Edwards  AR, Beck  RW,  et al; Diabetic Retinopathy Clinical Research Network.  Exploratory analysis of diabetic retinopathy progression through 3 years in a randomized clinical trial that compares intravitreal triamcinolone acetonide with focal/grid photocoagulation. Arch Ophthalmol. 2009;127(12):1566-1571.
PubMed   |  Link to Article
Age-Related Eye Disease Study Research Group.  A randomized, placebo-controlled, clinical trial of high-dose supplementation with vitamins C and E, beta carotene, and zinc for age-related macular degeneration and vision loss: AREDS report no. 8. Arch Ophthalmol. 2001;119(10):1417-1436.
PubMed   |  Link to Article
Rosenfeld  PJ, Brown  DM, Heier  JS,  et al; MARINA Study Group.  Ranibizumab for neovascular age-related macular degeneration. N Engl J Med. 2006;355(14):1419-1431.
PubMed   |  Link to Article
Brown  DM, Kaiser  PK, Michels  M,  et al; ANCHOR Study Group.  Ranibizumab versus verteporfin for neovascular age-related macular degeneration. N Engl J Med. 2006;355(14):1432-1444.
PubMed   |  Link to Article
Coleman  HR, Chan  CC, Ferris  FL  III, Chew  EY.  Age-related macular degeneration. Lancet. 2008;372(9652):1835-1845.
PubMed   |  Link to Article
Sloan  FA, Brown  DS, Carlisle  ES, Picone  GA, Lee  PP.  Monitoring visual status. Health Serv Res. 2004;39(5):1429-1448.
PubMed   |  Link to Article
Wang  F, Javitt  JC.  Eye care for elderly Americans with diabetes mellitus. Ophthalmology. 1996;103(11):1744-1750.
PubMed   |  Link to Article
Centers for Disease Control and Prevention; National Center for Health Statistics. Analytic and Reporting Guidelines: National Health and Nutrition Examination Survey.2005. www.cdc.gov/nchs/.../nhanes_analytic_guidelines_dec_2005.pdf. Accessed August 18, 2010.
National Health and Nutrition Examination Survey. Ophthalmology – Retinal Imaging: Data Documentation, Codebook, Frequencies. Centers for Disease Control and Prevention. 2010. http://www.cdc.gov/nchs/nhanes/nhanes2007-2008/OPXRET_E.htm. Accessed August 13, 2010.
Early Treatment Diabetic Retinopathy Study Research Group.  Grading diabetic retinopathy from stereoscopic color fundus photographs. Ophthalmology. 1991;98(5)(suppl):786-806.
PubMed   |  Link to Article
Klein  R, Davis  MD, Magli  YL, Segal  P, Klein  BE, Hubbard  L.  The Wisconsin age-related maculopathy grading system. Ophthalmology. 1991;98(7):1128-1134.
PubMed   |  Link to Article
American Diabetes Association.  Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33(suppl 1):S62-S69.
PubMed   |  Link to Article
Wilkinson  CP, Ferris  FL  III, Klein  RE,  et al; Global Diabetic Retinopathy Project Group.  Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scales. Ophthalmology. 2003;110(9):1677-1682.
PubMed   |  Link to Article
Rein  DB, Wittenborn  JS, Zhang  X,  et al; Vision Cost-Effectiveness Study Group.  The cost-effectiveness of three screening alternatives for people with diabetes with no or early diabetic retinopathy. Health Serv Res. 2011;46(5):1534-1561.
PubMed   |  Link to Article
National Diabetes Data Group. Diabetes in America.2nd ed. Bethesda, MD: National Institutes of Health, National Institutes of Diabetes and Digestive and Kidney Diseases; 1995.
US Department of Health and Human Services. Area Health Resource Files (AHRF). Rockville, MD: Health Resources and Services Administration, Bureau of Health Professions; 2012-2013.
Korn  EL, Graubard  BI. Analysis of Health Surveys. New York, NY: Wiley; 1999.
Ioannidis  JP, Hozo  I, Djulbegovic  B.  Optimal type I and type II error pairs when the available sample size is fixed. J Clin Epidemiol. 2013;66(8):903-910, e2.
PubMed   |  Link to Article
Lazaridis  EN, Qiu  C, Kraft  SK, Marrero  DG.  Same eyes, different doctors. Diabetes Care. 1997;20(7):1073-1077.
PubMed   |  Link to Article
Bressler  NM.  Early detection and treatment of neovascular age-related macular degeneration. J Am Board Fam Pract. 2002;15(2):142-152.
PubMed
White  AJ, Doksum  T, White  C.  Workforce projections for optometry. Optometry. 2000;71(5):284-300.
PubMed
Lee  PP, Hoskins  HD  Jr, Parke  DW  III.  Access to care. Arch Ophthalmol. 2007;125(3):406-410.
PubMed   |  Link to Article
Jones  S, Edwards  RT.  Diabetic retinopathy screening. Diabet Med. 2010;27(3):249-256.
PubMed   |  Link to Article
Taylor  CR, Merin  LM, Salunga  AM,  et al.  Improving diabetic retinopathy screening ratios using telemedicine-based digital retinal imaging technology. Diabetes Care. 2007;30(3):574-578.
PubMed   |  Link to Article
Au  A, Gupta  O.  The economics of telemedicine for vitreoretinal diseases. Curr Opin Ophthalmol. 2011;22(3):194-198.
PubMed   |  Link to Article
Zhang  X, Norris  SL, Saadine  J,  et al.  Effectiveness of interventions to promote screening for diabetic retinopathy. Am J Prev Med. 2007;33(4):318-335.
PubMed   |  Link to Article
Kelly  SP, Wallwork  I, Haider  D, Qureshi  K.  Teleophthalmology with optical coherence tomography imaging in community optometry. Clin Ophthalmol. 2011;5:1673-1678.
PubMed   |  Link to Article
Hanson  C, Tennant  MT, Rudnisky  CJ.  Optometric referrals to retina specialists. Telemed J E Health. 2008;14(5):441-445.
PubMed   |  Link to Article
Lee  PP, Hoskins  HD  Jr, Smith  RE, Hutchinson  BT, Wong  BA.  Access to eye care. Arch Ophthalmol. 2007;125(3):403-405.
PubMed   |  Link to Article
Liu  L, Swanson  M.  Improving patient outcomes. Clin Optom. 2013;5:1-12.
Link to Article
Centers for Disease Control and Prevention. National Diabetes Fact Sheet: National Estimates and General Information on Diabetes and Prediabetes in the United States, 2011. Atlanta, GA: US Dept of Health and Human Services, Centers for Disease Control and Prevention; 2011.

Figures

Tables

Table Graphic Jump LocationTable 1.  Measures of Realized Access to Eye Care and Eye Care Professional Availability for Diabetic Individuals With and Without Diabetic Retinopathy and Individuals With ARMD, NHANES, 2005-2008
Table Graphic Jump LocationTable 2.  Multiple Logistic Regression Models of Measures of Realized Access to Eye Care, NHANES, 2005-2008a

References

Zhang  X, Andersen  R, Saaddine  JB, Beckles  GL, Duenas  MR, Lee  PP.  Measuring access to eye care. Ophthalmic Epidemiol. 2008;15(6):418-425.
PubMed   |  Link to Article
Congdon  N, O’Colmain  B, Klaver  CC,  et al; Eye Diseases Prevalence Research Group.  Causes and prevalence of visual impairment among adults in the United States. Arch Ophthalmol. 2004;122(4):477-485.
PubMed   |  Link to Article
Kempen  JH, O’Colmain  BJ, Leske  MC,  et al; Eye Diseases Prevalence Research Group.  The prevalence of diabetic retinopathy among adults in the United States. Arch Ophthalmol. 2004;122(4):552-563.
PubMed   |  Link to Article
Zhang  X, Saaddine  JB, Chou  CF,  et al.  Prevalence of diabetic retinopathy in the United States, 2005-2008. JAMA. 2010;304(6):649-656.
PubMed   |  Link to Article
Klein  R, Klein  B. Vision disorders in diabetes. In: National Diabetes Data Group, ed. Diabetes in America.2nd ed. Bethesda, MD: National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases; 1995:293-297.
Friedman  DS, O’Colmain  BJ, Muñoz  B,  et al; Eye Diseases Prevalence Research Group.  Prevalence of age-related macular degeneration in the United States. Arch Ophthalmol. 2004;122(4):564-572.
PubMed   |  Link to Article
Klein  R, Chou  CF, Klein  BE, Zhang  X, Meuer  SM, Saaddine  JB.  Prevalence of age-related macular degeneration in the US population. Arch Ophthalmol. 2011;129(1):75-80.
PubMed   |  Link to Article
Gibson  DM.  Diabetic retinopathy and age-related macular degeneration in the U.S. Am J Prev Med. 2012;43(1):48-54.
PubMed   |  Link to Article
American Academy of Ophthalmology. Preferred Practice Pattern: Diabetic Retinopathy. San Francisco, CA: American Academy of Ophthalmology; 2008.
American Academy of Ophthalmology. Preferred Practice Pattern: Age-Related Macular Degeneration. San Francisco, CA: American Academy of Ophthalmology; 2008.
The Diabetes Control and Complications Trial Research Group.  The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993;329(14):977-986.
PubMed   |  Link to Article
UK Prospective Diabetes Study Group.  Tight blood pressure control and risk of macrovascular and microvascular complications in type 2 diabetes: UKPDS 38. BMJ. 1998;317(7160):703-713.
PubMed   |  Link to Article
Avery  RF, Pearlman  J, Pieramici  DJ,  et al.  Intravitreal bevacizumab (Avastin) in the treatment of proliferative diabetic retinopathy .Ophthalmology. 2006;113(10):1695.e1-1695.15.
PubMed
Bressler  NM, Edwards  AR, Beck  RW,  et al; Diabetic Retinopathy Clinical Research Network.  Exploratory analysis of diabetic retinopathy progression through 3 years in a randomized clinical trial that compares intravitreal triamcinolone acetonide with focal/grid photocoagulation. Arch Ophthalmol. 2009;127(12):1566-1571.
PubMed   |  Link to Article
Age-Related Eye Disease Study Research Group.  A randomized, placebo-controlled, clinical trial of high-dose supplementation with vitamins C and E, beta carotene, and zinc for age-related macular degeneration and vision loss: AREDS report no. 8. Arch Ophthalmol. 2001;119(10):1417-1436.
PubMed   |  Link to Article
Rosenfeld  PJ, Brown  DM, Heier  JS,  et al; MARINA Study Group.  Ranibizumab for neovascular age-related macular degeneration. N Engl J Med. 2006;355(14):1419-1431.
PubMed   |  Link to Article
Brown  DM, Kaiser  PK, Michels  M,  et al; ANCHOR Study Group.  Ranibizumab versus verteporfin for neovascular age-related macular degeneration. N Engl J Med. 2006;355(14):1432-1444.
PubMed   |  Link to Article
Coleman  HR, Chan  CC, Ferris  FL  III, Chew  EY.  Age-related macular degeneration. Lancet. 2008;372(9652):1835-1845.
PubMed   |  Link to Article
Sloan  FA, Brown  DS, Carlisle  ES, Picone  GA, Lee  PP.  Monitoring visual status. Health Serv Res. 2004;39(5):1429-1448.
PubMed   |  Link to Article
Wang  F, Javitt  JC.  Eye care for elderly Americans with diabetes mellitus. Ophthalmology. 1996;103(11):1744-1750.
PubMed   |  Link to Article
Centers for Disease Control and Prevention; National Center for Health Statistics. Analytic and Reporting Guidelines: National Health and Nutrition Examination Survey.2005. www.cdc.gov/nchs/.../nhanes_analytic_guidelines_dec_2005.pdf. Accessed August 18, 2010.
National Health and Nutrition Examination Survey. Ophthalmology – Retinal Imaging: Data Documentation, Codebook, Frequencies. Centers for Disease Control and Prevention. 2010. http://www.cdc.gov/nchs/nhanes/nhanes2007-2008/OPXRET_E.htm. Accessed August 13, 2010.
Early Treatment Diabetic Retinopathy Study Research Group.  Grading diabetic retinopathy from stereoscopic color fundus photographs. Ophthalmology. 1991;98(5)(suppl):786-806.
PubMed   |  Link to Article
Klein  R, Davis  MD, Magli  YL, Segal  P, Klein  BE, Hubbard  L.  The Wisconsin age-related maculopathy grading system. Ophthalmology. 1991;98(7):1128-1134.
PubMed   |  Link to Article
American Diabetes Association.  Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010;33(suppl 1):S62-S69.
PubMed   |  Link to Article
Wilkinson  CP, Ferris  FL  III, Klein  RE,  et al; Global Diabetic Retinopathy Project Group.  Proposed international clinical diabetic retinopathy and diabetic macular edema disease severity scales. Ophthalmology. 2003;110(9):1677-1682.
PubMed   |  Link to Article
Rein  DB, Wittenborn  JS, Zhang  X,  et al; Vision Cost-Effectiveness Study Group.  The cost-effectiveness of three screening alternatives for people with diabetes with no or early diabetic retinopathy. Health Serv Res. 2011;46(5):1534-1561.
PubMed   |  Link to Article
National Diabetes Data Group. Diabetes in America.2nd ed. Bethesda, MD: National Institutes of Health, National Institutes of Diabetes and Digestive and Kidney Diseases; 1995.
US Department of Health and Human Services. Area Health Resource Files (AHRF). Rockville, MD: Health Resources and Services Administration, Bureau of Health Professions; 2012-2013.
Korn  EL, Graubard  BI. Analysis of Health Surveys. New York, NY: Wiley; 1999.
Ioannidis  JP, Hozo  I, Djulbegovic  B.  Optimal type I and type II error pairs when the available sample size is fixed. J Clin Epidemiol. 2013;66(8):903-910, e2.
PubMed   |  Link to Article
Lazaridis  EN, Qiu  C, Kraft  SK, Marrero  DG.  Same eyes, different doctors. Diabetes Care. 1997;20(7):1073-1077.
PubMed   |  Link to Article
Bressler  NM.  Early detection and treatment of neovascular age-related macular degeneration. J Am Board Fam Pract. 2002;15(2):142-152.
PubMed
White  AJ, Doksum  T, White  C.  Workforce projections for optometry. Optometry. 2000;71(5):284-300.
PubMed
Lee  PP, Hoskins  HD  Jr, Parke  DW  III.  Access to care. Arch Ophthalmol. 2007;125(3):406-410.
PubMed   |  Link to Article
Jones  S, Edwards  RT.  Diabetic retinopathy screening. Diabet Med. 2010;27(3):249-256.
PubMed   |  Link to Article
Taylor  CR, Merin  LM, Salunga  AM,  et al.  Improving diabetic retinopathy screening ratios using telemedicine-based digital retinal imaging technology. Diabetes Care. 2007;30(3):574-578.
PubMed   |  Link to Article
Au  A, Gupta  O.  The economics of telemedicine for vitreoretinal diseases. Curr Opin Ophthalmol. 2011;22(3):194-198.
PubMed   |  Link to Article
Zhang  X, Norris  SL, Saadine  J,  et al.  Effectiveness of interventions to promote screening for diabetic retinopathy. Am J Prev Med. 2007;33(4):318-335.
PubMed   |  Link to Article
Kelly  SP, Wallwork  I, Haider  D, Qureshi  K.  Teleophthalmology with optical coherence tomography imaging in community optometry. Clin Ophthalmol. 2011;5:1673-1678.
PubMed   |  Link to Article
Hanson  C, Tennant  MT, Rudnisky  CJ.  Optometric referrals to retina specialists. Telemed J E Health. 2008;14(5):441-445.
PubMed   |  Link to Article
Lee  PP, Hoskins  HD  Jr, Smith  RE, Hutchinson  BT, Wong  BA.  Access to eye care. Arch Ophthalmol. 2007;125(3):403-405.
PubMed   |  Link to Article
Liu  L, Swanson  M.  Improving patient outcomes. Clin Optom. 2013;5:1-12.
Link to Article
Centers for Disease Control and Prevention. National Diabetes Fact Sheet: National Estimates and General Information on Diabetes and Prediabetes in the United States, 2011. Atlanta, GA: US Dept of Health and Human Services, Centers for Disease Control and Prevention; 2011.

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