No-Show Propensity and Loss to Follow-Up Among Glaucoma Patients: A Retrospective Cohort Study
PURPOSE: To identify risk factors for high first-year no-show propensity among glaucoma patients and assess its association with subsequent LTFU. METHODS: This retrospective cohort study included patients with a glaucoma diagnosis documented from 2013-2023 at a tertiary academic eye institute. Demographic, clinical, and appointment status data were extracted from the electronic health record. LTFU was defined as an interval of >365 days without an attended visit after the first-year observation window. No-show propensity factor (NSPF), a metric of appointment nonattendance that considers the total number of appointments and average no-show rate of the cohort, was calculated for each patient for their first year. Poisson regression models were used to identify risk factors for high NSPF (≥75th percentile). Cox proportional hazards models were used to evaluate the association between high NSPF and risk of subsequent LTFU. RESULTS: The 7087 glaucoma patients had 37,249 scheduled appointments in their first year, 2778 (7.5%) of which were no-show. Risk factors for high NSPF included age < 60 years (relative risk [RR]=1.10, 95% confidence interval [CI]: 1.07-1.12), Black race (RR = 1.23, 95% CI: 1.21-1.25), Medicaid insurance (RR = 1.23, 95% CI: 1.19-1.28), and visual acuity 20/200 or worse in the better-seeing eye (RR = 1.09, 95% CI: 1.06-1.11). Three-quarters (72.0%) experienced at least one LTFU event. In an adjusted model, high NSPF predicted higher risk of subsequent LTFU (hazard ratio = 1.15, 95% CI: 1.08-1.22). CONCLUSION: Demographic and clinical factors underlie risk of no-show propensity among glaucoma patients. Patients with a high propensity to no-show in their first year had greater risk of subsequent LTFU.
Authors
- Andrew M. Williams (ORCID: https://orcid.org/0000-0001-9789-0748)
- Hai-Wei Liang
Institutions
- University of Pittsburgh (US)
Publication Details
- Journal
- Ophthalmic Epidemiology
- Published
- 2026-09-14
- DOI
- https://doi.org/10.1080/09286586.2026.2729054
- Primary Topic
- Healthcare Operations and Scheduling Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00