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. 2025 Jul 30;13(15):1869.
doi: 10.3390/healthcare13151869.

Understanding No-Show Patterns in Healthcare: A Retrospective Study from Northern Italy

Affiliations

Understanding No-Show Patterns in Healthcare: A Retrospective Study from Northern Italy

Antonino Russotto et al. Healthcare (Basel). .

Abstract

Objectives: The aim of this study was to analyse no-show patterns in healthcare appointments, identify associated factors, and explore key determinants influencing non-attendance. Study Design: This was a retrospective observational study. Methods: We analysed 120,405 healthcare appointments from 2022-2023 in Turin, Northern Italy. Data included demographics, appointment characteristics, and attendance records. Logistic regression identified significant predictors of no-shows, adjusting for confounders. Results: A 5.1% (n = 6198) no-show percentage was observed. Younger patients (<18 years) and adults (18-65 years) had significantly higher odds of missing appointments than elderly patients (>65 years) (OR = 2.32, 95% CI: 2.17-2.47; OR = 2.46, 95% CI: 2.20-2.74; p < 0.001). First-time visits had a higher no-show risk compared to follow-up visits and diagnostics (OR = 1.11, 95% CI: 1.04-1.18; p < 0.001). Each additional day of waiting increased the likelihood of no-show by 1% (OR = 1.01, 95% CI: 1.01-1.01; p < 0.001). Conclusions: No-show percentages are influenced by demographic and service-related factors. Strategies targeting younger patients, longer waiting times, and non-urgent appointments could reduce no-show percentages.

Keywords: efficiency; no-show patients; organizational; patient appointments; utilization review; waiting lists.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Scatter plot: on the X-axis, the age of the patients; on the Y-axis, the no-show percentage in percentage in the left and the no-show total number in the right.

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