June 2013
Volume 54, Issue 15
Free
ARVO Annual Meeting Abstract  |   June 2013
Despite Possessing Health Insurance, Large Disparities Exist in Likelihood of Visits to Eye Care Providers Across U.S. Sociodemographic Groups
Author Affiliations & Notes
  • Patricia Ple-plakon
    Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI
  • Chris Andrews
    Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI
  • David Musch
    Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI
    Epidemiology, University of Michigan, Ann Arbor, MI
  • Paul Lee
    Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI
  • Joshua Stein
    Ophthalmology and Visual Sciences, University of Michigan, Ann Arbor, MI
  • Footnotes
    Commercial Relationships Patricia Ple-plakon, None; Chris Andrews, None; David Musch, Glaukos (C), AqueSys (C), InnFocus (C), Pfizer (F), DigiSight Technologies (C); Paul Lee, Genentech (C), University of Michigan (E), Duke University (E), Pfizer (C), Pfizer (I), Glaxo (I), Merck (I), Allergan (C), Duke University (P); Joshua Stein, University of Michigan - time to next glaucoma test algorithm patent (P)
  • Footnotes
    Support None
Investigative Ophthalmology & Visual Science June 2013, Vol.54, 4544. doi:
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    • Get Citation

      Patricia Ple-plakon, Chris Andrews, David Musch, Paul Lee, Joshua Stein; Despite Possessing Health Insurance, Large Disparities Exist in Likelihood of Visits to Eye Care Providers Across U.S. Sociodemographic Groups. Invest. Ophthalmol. Vis. Sci. 2013;54(15):4544.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract
 
Purpose
 

To determine whether race, education, and income impact the likelihood of visiting an eye care provider among a nationwide sample of enrollees in a U.S. managed care plan.

 
Methods
 

Reviewed claims data of all enrollees ≥21 years old in a U.S. managed care network who had eye care from 2001-2011 to determine the proportion visiting eye care providers yearly. Performed logistic regression to determine the impact of sociodemographic factors on the likelihood of visits to various eye care providers.

 
Results
 

Among 9.8 million enrollees, those with racial data included 80.6% white, 6.1% black, 8.7% Latino, 3.5% Asian American and 1.1% other; 30.4% had ≤ high school(HS) diploma and 20.3% had ≥college degree; 5.5% had income <$30K and 6.6% had income >$125K. Adjusting for other factors, the odds of visiting an ophthalmologist were 3% lower among blacks (OR=0.97) and 9% higher among Asian Americans (OR=1.09) relative to whites. Racial minorities were less likely to visit an optometrist relative to whites (ORblack=0.80,ORlatino=0.71,ORasian=0.80). Compared to those with HS diploma, enrollees with college degrees had 35% higher odds of visiting an ophthalmologist (OR=1.35) and equal odds of visiting an optometrist (OR=1.01). Compared to those earning <$30K, those earning >$125K had 19% higher odds of visiting an ophthalmologist (OR=1.19) and 23% lower odds of visiting an optometrist (OR=0.77). Controlling for major ocular comorbidities, the most affluent and well-educated whites, relative to the least affluent and less-educated blacks, had 120% higher odds of visiting an ophthalmologist (OR=2.2) and 24% lower odds of visiting an optometrist (OR=0.76). All SEs of ORs ≤0.02. Further analyses compared probabilities of visits to eye care providers among the most affluent and educated whites versus the least affluent and educated blacks with glaucoma, cataract, ARMD, and diabetic retinopathy.

 
Conclusions
 

Race, education, and wealth dramatically impact the probability of seeking eye care by ophthalmologists and optometrists, despite all enrollees having health insurance. Income and education had a greater effect than race. This pattern of eye care utilization puts racial minorities and people of lower socioeconomic status at higher risk for many sight-threatening ocular diseases, thus creating important implications for policy-making and future resource allocation.

 
Keywords: 460 clinical (human) or epidemiologic studies: health care delivery/economics/manpower • 464 clinical (human) or epidemiologic studies: risk factor assessment  
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