DOI: 10.4103/jfmpc.jfmpc_1115_26 ISSN: 2249-4863

Appointment lead time and prior no-show history predict outpatient non-attendance: A large-scale EMR study

Ruba A. Alahaideb, Mohammed A. Alrowaily
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BSTRACT

Background:

Outpatient no-show remains a major source of inefficiency in healthcare, with global rates around 23%, yet large-scale electronic medical record (EMR)-based evidence from the Middle East is limited.

Objective:

To identify independent predictors of outpatient non-attendance using EMR data from a Saudi Arabian tertiary care center.

Methods:

This retrospective observational study used EMR data from January 2023 to July 2025, comprising 4,999,925 raw appointment records. Canceled appointments ( n = 1,041,472; 22.0%) were excluded from the regression analysis. After exclusions and complete-case filtering, 3,685,929 appointments were included in a generalized estimating equations logistic regression model.

Results:

The overall no-show rate was 17.8%. Appointment lead time showed the largest overall effect size, while prior no-show history was the strongest patient-level predictor [odds ratio (OR), 4.26; 95% confidence interval, 4.18–4.33]. Appointment lead time showed a pronounced dose–response relationship, with odds increasing from 3.69 to 8.17 relative to same-day visits. Ramadan was independently associated with higher non-attendance (OR, 1.30) after adjustment for primary covariates.

Conclusion:

Prior no-show history and appointment lead time may support scalable EMR-based risk stratification in high-volume outpatient settings, with context-specific factors such as Ramadan warranting consideration in scheduling and capacity planning.

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