Racial and ethnic disparities in adherence to glaucoma follow-up visits in a county hospital population

Arch Ophthalmol. 2011 Jul;129(7):872-8. doi: 10.1001/archophthalmol.2011.163.

Abstract

Objectives: To identify predictors of inconsistent attendance at glaucoma follow-up visits in a county hospital population.

Methods: Prospective recruitment from August 1, 2008, through January 31, 2009, of 152 individuals with glaucoma, with 1-to-1 matching of patients (those with inconsistent follow-up) and controls (those with consistent follow-up). Data were collected via oral questionnaire. Survey results were correlated with attendance at follow-up examinations, using the t test, χ(2) test, and multivariate stepwise logistic regression analysis to calculate the odds ratios (ORs) and 95% confidence intervals.

Results: After adjusting for covariates in the logistic regression analysis, factors independently associated with inconsistent follow-up included black race (adjusted OR, 7.16; 95% confidence interval, 1.64-31.24), Latino ethnicity (adjusted OR, 4.77; 1.12-20.29), unfamiliarity with necessary treatment duration (adjusted OR, 3.54; 1.26-9.94), lack of knowledge of the permanency of glaucoma-induced vision loss (adjusted OR, 3.09; 1.18-8.04), and perception that it is not important to attend all follow-up visits (adjusted OR, 3.54; 1.26-9.94).

Conclusions: Demographic factors, including race and ethnicity, may directly or indirectly affect adherence to recommended glaucoma follow-up visits. Lack of information regarding irreversible vision loss from glaucoma, need for lifelong treatment, and lack of visual symptoms may be significant barriers to follow-up in this population. Targeted glaucoma education by physicians may improve follow-up, thereby decreasing the morbidity associated with glaucomatous disease.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Case-Control Studies
  • Continuity of Patient Care
  • Ethnicity / statistics & numerical data*
  • Female
  • Glaucoma / ethnology*
  • Healthcare Disparities / ethnology*
  • Healthcare Disparities / statistics & numerical data
  • Hospitals, County / statistics & numerical data*
  • Humans
  • Male
  • Middle Aged
  • Office Visits / statistics & numerical data*
  • Patient Compliance / statistics & numerical data*
  • Prospective Studies
  • Racial Groups / statistics & numerical data*
  • San Francisco