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Racial, Ethnic, and Socioeconomic Disparities Drive Appointment No-Show in Patients with Chronic Eye Disease

Journal of Racial and Ethnic Health Disparities volume 10, pages 1790–1797 (2023)Cite this article

Abstract

Background

Visit no-shows (NS) reduce clinic efficiency and effective resource allocation. Inadequate follow-up among patients with chronic eye disease increases risk of disease progression. Our study identifies demographic, medical, and socioeconomic characteristics that increase odds of NS among patients with chronic eye conditions at high risk of vision-threatening complications.

Methods

This is a retrospective case–control study of data abstracted over a 5-year period (January 2013–December 2018) in an urban academic ophthalmology practice. Follow-up appointments of patients ≥ 18 years of age with a diagnosis of glaucoma, diabetic retinopathy, or age-related macular degeneration were included. Age, sex, race, ethnicity, language preference, zip code, and relevant medical history were recorded. A multivariate mixed logistic regression model was utilized to determine any association between demographic factors and visit NS.

Results

A total of 106,652 visits for 4,598 unique patients were included in this study. Of these, 13,240 (12.4%) visits were NS. Patient characteristics that increased the odds of NS included Hispanic ethnicity (p < 0.0001), Black race (p < 0.0001), and a history of mental illness (p < 0.0001). Socioeconomic factors that increased the odds of NS included median household income < $40,000 (p = 0.002), Medicare insurance (p < 0.0001), and Medicaid insurance (p < 0.0001).

Conclusions

Our results highlight the influence of ethnic, racial, medical, and socioeconomic characteristics on appointment NS among patients with chronic eye disease. Future interventions aimed at reducing appointment NS could channel resources to the at-risk populations identified in this analysis to improve access to care for those who need it most.

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References

  1. McMullen MJ, Netland PA. Lead time for appointment and the no-show rate in an ophthalmology clinic. Clin Ophthalmol. 2015;9:513–6.

    PubMed  PubMed Central  Google Scholar 

  2. Paterson BL, Charlton P, Richard S. Non-attendance in chronic disease clinics: a matter of non-compliance? J Nurs Healthc Chronic Illn. 2010;2(1):63–74.

    Article  Google Scholar 

  3. Virk R, et al. How is the risk of being diagnosed with referable diabetic retinopathy affected by failure to attend diabetes eye screening appointments? Eye (Lond). 2021;35(2):477–83.

    Article  PubMed  Google Scholar 

  4. Kiruparan P, Kiruparan N, Debnath D. Impact of pre-appointment contact and short message service alerts in reducing “Did Not Attend” (DNA) rate on rapid access new patient breast clinics: a DGH perspective. BMC Health Serv Res. 2020;20(1):757.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Lin H, et al. Effectiveness of a short message reminder in increasing compliance with pediatric cataract treatment: a randomized trial. Ophthalmology. 2012;119(12):2463–70.

    Article  PubMed  Google Scholar 

  6. Chiam M, Kunselman AR, Chen MC. Characteristics associated with new patient appointment no-shows at an academic ophthalmology department in the United States. Am J Ophthalmol. 2021;229:210–9.

    Article  PubMed  Google Scholar 

  7. U.S. Census Bureau QuickFacts: Connecticut; United States. Available from: https://www.census.gov/quickfacts/fact/table/CT,US/INC110219. Accessed 19 May 2021.

  8. Eppley SE, et al. Characteristics associated with adherence to annual dilated eye examinations among US patients with diagnosed diabetes. Ophthalmology. 2019;126(11):1492–9.

    Article  PubMed  Google Scholar 

  9. Chen EM, et al. Ophthalmic emergency department visits: factors associated with loss to follow-up. Am J Ophthalmol. 2020;222:126–36.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Green M, Tien T, Ness S. Predictors of lost to follow-up in patients being treated for proliferative diabetic retinopathy. Am J Ophthalmol. 2020;216:18–27.

    Article  PubMed  Google Scholar 

  11. Jansen ME, et al. Appointment compliance in patients with diabetic macular edema and exudative macular degeneration. Ophthalmic Surg Lasers Imaging Retina. 2018;49(3):186–90.

    Article  PubMed  Google Scholar 

  12. Briggs M, et al. Predictive factors for patients’ failure to show for initial outpatient physical therapist evaluation. Phys Ther. 2021;101(5). https://doi.org/10.1093/PTJ/PZAB047.

  13. Miller AJ, et al. Predictors of repeated “no-showing” to clinic appointments. Am J Otolaryngol. 2015;36(3):411–4.

    Article  PubMed  Google Scholar 

  14. Cohen AD, et al. Nonattendance of adult otolaryngology patients for scheduled appointments. J Laryngol Otol. 2007;121(3):258–61.

    Article  CAS  PubMed  Google Scholar 

  15. Kaplan-Lewis E, Percac-Lima S. No-show to primary care appointments: why patients do not come. J Prim Care Community Health. 2013;4(4):251–5.

    Article  PubMed  Google Scholar 

  16. Hamilton W, Round A, Sharp D. Patient, hospital, and general practitioner characteristics associated with non-attendance: a cohort study. Br J Gen Pract. 2002;52(477):317–9.

    PubMed  PubMed Central  Google Scholar 

  17. Rutledge MS, et al. What explains the widening gap in retirement ages by education. Center for Retirement Research Issue Brief, 2018: p. 18–10.

  18. Ayanian JZ, et al. Unmet health needs of uninsured adults in the United States. JAMA. 2000;284(16):2061–9.

    Article  CAS  PubMed  Google Scholar 

  19. Murakami Y, et al. Racial and ethnic disparities in adherence to glaucoma follow-up visits in a county hospital population. Arch Ophthalmol. 2011;129(7):872–8.

    Article  PubMed  Google Scholar 

  20. Bertakis KD, et al. Gender differences in the utilization of health care services. J Fam Pract. 2000;49(2):147–52.

    CAS  PubMed  Google Scholar 

  21. Bertakis KD. The influence of gender on the doctor-patient interaction. Patient Educ Couns. 2009;76(3):356–60.

    Article  PubMed  Google Scholar 

  22. Fathy C, et al. Disparities in adherence to screening guidelines for diabetic retinopathy in the United States: a comprehensive review and guide for future directions. Semin Ophthalmol. 2016;31(4):364–77.

    Article  PubMed  Google Scholar 

  23. Shi Q, et al. Racial disparity of eye examinations among the U.S. working-age population with diabetes: 2002–2009. Diabetes Care. 2014;37(5):1321–8.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Lu Y, et al. Disparities in diabetic retinopathy screening rates within minority populations: differences in reported screening rates among African American and Hispanic patients. Diabetes Care. 2016;39(3):e31–2.

    Article  PubMed  Google Scholar 

  25. Baker RS, et al. Access to vision care in an urban low-income multiethnic population. Ophthalmic Epidemiol. 2005;12(1):1–12.

    Article  PubMed  Google Scholar 

  26. Fairless E, Nwanyanwu K. Barriers to and facilitators of diabetic retinopathy screening utilization in a high-risk population. J Racial Ethn Health Disparities. 2019;6(6):1244–9.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Odonkor CA, et al. Factors associated with missed appointments at an academic pain treatment center: a prospective year-long longitudinal study. Anesth Analg. 2017;125(2):562–70.

    Article  PubMed  Google Scholar 

  28. Suresh R, et al. Loss to follow-up among patients with proliferative diabetic retinopathy in clinical practice. Am J Ophthalmol. 2020;215:66–71.

    Article  PubMed  Google Scholar 

  29. Curry EJ, et al. An Evaluation of risk factors for patient “no shows” at an urban joint arthroplasty clinic. J Am Acad Orthop Surg. 2020;28(22):e1006–13.

    Article  PubMed  Google Scholar 

  30. Policy, A.C.o.M.a.C. Racial and ethnic disparities in Medicaid: an annotated bibliography. 2021, MACPAC.

  31. College, C.f.R.R.a.B. Average retirement age for men and women, 1962–2016. 2017.

  32. Yusuf R, et al. Risk Factors for underutilization of eye care in the evaluation of diabetic retinopathy. Investig Ophthalmol Vis Sci. 2019;60(9):1080–1080.

    Google Scholar 

  33. Navabi S, et al. Influences and impact of anxiety and depression in the setting of inflammatory bowel disease. Inflamm Bowel Dis. 2018;24(11):2303–8.

    Article  PubMed  Google Scholar 

  34. Cradock-O’Leary J, et al. Use of general medical services by VA patients with psychiatric disorders. Psychiatr Serv. 2002;53(7):874–8.

    Article  PubMed  Google Scholar 

  35. Goldman LS. Medical illness in patients with schizophrenia. J Clin Psychiatry. 1999;60(Suppl 21):10–5.

    PubMed  Google Scholar 

  36. Lieberman AA, Coburn AF. The health of the chronically mentally ill: a review of the literature. Community Ment Health J. 1986;22(2):104–16.

    Article  CAS  PubMed  Google Scholar 

  37. Massad PM, West AN, Friedman MJ. Relationship between utilization of mental health and medical services in a VA hospital. Am J Psychiatry. 1990;147(4):465–9.

    Article  CAS  PubMed  Google Scholar 

  38. Feng PW, et al. National trends in the United States eye care workforce from 1995 to 2017. Am J Ophthalmol. 2020;218:128–35.

    Article  PubMed  Google Scholar 

  39. Eades C, Alexander H. A mixed-methods exploration of non-attendance at diabetes appointments using peer researchers. Health Expect. 2019;22(6):1260–71.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Margham T, et al. Reducing missed appointments in general practice: evaluation of a quality improvement programme in East London. Br J Gen Pract. 2021;71(702):e31–8.

    Article  PubMed  Google Scholar 

  41. Andreae MH, et al. The effect of initiatives to overcome language barriers and improve attendance: a cross-sectional analysis of adherence in an inner city chronic pain clinic. Pain Med. 2017;18(2):265–74.

    Article  PubMed  Google Scholar 

  42. Atkinson-Briggs S, et al. Integrating diabetic retinopathy screening within diabetes education services in Australia’s diabetes and indigenous primary care clinics. Intern Med J. 2019;49(6):797–800.

    Article  PubMed  Google Scholar 

  43. Chaiyachati KH, Moore K, Adelberg M. Too early to cut transportation benefits from medicaid enrollees. Health Services Insights. 2018;11:1178632918804817.

    Article  Google Scholar 

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Funding

This publication was made possible by Grant Number 1 K23 EY030530-01 from the National Eye Institute, Yale Diabetes Center Grant P30 DK045735, and the Doris Duke Fund to Retain Clinical Scientists. This work has been supported in part by an unrestricted/challenge award to Yale Eye Center from the Research to Prevent Blindness (RPB), Inc., as well as the Yale School of Medicine Medical Student Research Fellowship.

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Authors and Affiliations

  1. Yale School of Medicine, 40 Temple Street, New Haven, CT, 06511, USA

    Eugenia C. Greig, Rosana Gonzalez-Colaso & Kristen Nwanyanwu

  2. University of California San Francisco, San Francisco, CA, USA

    Eugenia C. Greig

Authors
  1. Eugenia C. Greig
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  2. Rosana Gonzalez-Colaso
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  3. Kristen Nwanyanwu
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Contributions

All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by Eugenia Custo Greig. The first draft of the manuscript was written by Eugenia Custo Greig, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Kristen Nwanyanwu.

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Ethics Approval

This study was approved by Yale University’s institutional review board and was carried out in accordance with the Declaration of Helsinki and the Health Insurance Portability and Accountability Act.

Consent to Participate

Given the retrospective, chart review nature of this study the Yale University institutional review board found that informed consent could be waived for this study under federal regulation 45 CFR 46.116(d). This part of the regulations states that (1) this research involves no more than minimal risk to the subjects, (2) the waiver or alteration will not adversely affect the rights and welfare of the subjects, (3) the research could not practicably be carried out without the waiver, and (4) whenever appropriate, the subjects will be provided with additional pertinent information after participation.

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Our manuscript does not contain any individual person’s data in any form and therefore consent for publication was not obtained.

Competing Interests

The authors declare no competing interests.

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Greig, E.C., Gonzalez-Colaso, R. & Nwanyanwu, K. Racial, Ethnic, and Socioeconomic Disparities Drive Appointment No-Show in Patients with Chronic Eye Disease. J. Racial and Ethnic Health Disparities 10, 1790–1797 (2023). https://doi.org/10.1007/s40615-022-01363-x

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