June 2021
Volume 62, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2021
Demographic Characteristics and Clinic No Shows in Patients with Chronic Eye Disease
Author Affiliations & Notes
  • Eugenia Custo Greig
    Ophthalmology, Yale University School of Medicine, New Haven, Connecticut, United States
  • Rosana Gonzalez-Colaso
    Ophthalmology, Yale University School of Medicine, New Haven, Connecticut, United States
  • Kristen Harris Nwanyanwu
    Ophthalmology, Yale University School of Medicine, New Haven, Connecticut, United States
  • Footnotes
    Commercial Relationships   Eugenia Custo Greig, None; Rosana Gonzalez-Colaso, None; Kristen Nwanyanwu, None
  • Footnotes
    Support  Yale University School of Medicine Grant
Investigative Ophthalmology & Visual Science June 2021, Vol.62, 1721. doi:
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      Eugenia Custo Greig, Rosana Gonzalez-Colaso, Kristen Harris Nwanyanwu; Demographic Characteristics and Clinic No Shows in Patients with Chronic Eye Disease. Invest. Ophthalmol. Vis. Sci. 2021;62(8):1721.

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

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Abstract

Purpose : Patient no shows reduce ophthalmologic clinic efficiency and effective resource allocation. We performed a retrospective cohort study to determine the effect of demographic characteristics on appointment no shows among patients with chronic eye disease.

Methods : A chart abstraction was performed for encounters of patients 18 and older with a diagnosis of glaucoma, diabetic retinopathy (DR), or age-related macular degeneration (AMD) seen in the Yale Ophthalmology Department between January 2013 and December 2018. Only encounters with comprehensive ophthalmologists, retina specialists, and glaucoma specialists were considered in this analysis. Demographic characteristics recorded for each encounter included age, gender, race, ethnicity, language preference, and zip code. Zip code information was utilized to determine median household income according to 2010 census data. Medical diagnostic information included history of diabetes mellitus, hypertension, and history of mental illness. No show encounters were defined as all encounters where the patient failed to cancel their visit and did not sign-in to their scheduled appointment. A multivariate mixed logistic regression model—which clusters data to account for random effects driven by intra-patient correlation—was utilized to determine demographic factors affecting odds of visit no show.

Results : The current study analyzed 90,698 visits for 6,167 unique patients. Demographic characteristics that increased the odds of no show included: Hispanic ethnicity (OR 1.58/p < 0.0001), Black race (OR 1.87/p < 0.0001), and preferred language other than English (OR 1.31/p = 0.0004). Financial factors that increased the odds of no show included Medicare (OR 1.19/p = 0.0006) or Medicaid (OR 1.66/p < 0.0001) as primary insurance and residing in a zip code with reduced median household income (OR 1.68/p < 0.0001). Medical characteristics that increased the odds of no show included a diagnosis of mental illness (OR 1.44/p < 0.0001) or DR (OR 1.21/p = 0.01). Results are displayed in Table 1.

Conclusions : Our results highlight the influence of demographic, ethnic, and racial disparities on proper health care utilization among patients with sight threatening disease. Future interventions aimed at reducing appointment no shows could channel resources to the at risk-populations identified in this analysis, improving access to care and clinic efficiency.

This is a 2021 ARVO Annual Meeting abstract.

 

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