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Predicting Patient No-show Behavior: a Study in a Bariatric Clinic
Leila F Dantas1, Silvio Hamacher1, Fernando L Cyrino Oliveira1
1Department of Industrial Engineering, Pontifical Catholic University of Rio de Janeiro, Rua Marquês de São Vicente, 225, Rio de Janeiro, RJ, 22451-900, Brazil.
Obesity Surgery
|September 14, 2018
Summary
Patient no-shows in bariatric surgery clinics are linked to appointment timing, history, and distance. Understanding these factors can improve clinic scheduling and reduce costs.
Area of Science:
- Health Services Research
- Clinical Management
- Healthcare Operations
Background:
- Patient no-shows significantly impact healthcare efficiency and increase costs.
- Bariatric surgery clinics face unique challenges with appointment adherence.
Purpose of the Study:
- To identify factors associated with patient no-shows in a bariatric surgery setting.
- To develop a predictive model for patient no-shows.
Main Methods:
- Retrospective study of 13,230 patient records over 17 months.
- Logistic regression analysis to identify significant predictors of no-shows.
- Development of a predictive model stratified by medical specialty.
Main Results:
- Overall no-show rate was 21.9%.
- Key predictors included later appointment times, non-summer months, post-surgery status, high lead time, prior no-show history, fewer previous appointments, distance from clinic, and non-bariatric appointments.
- Predictive models achieved 71% accuracy.
Conclusions:
- Understanding patient no-show characteristics is crucial for improving clinic management.
- Predictive models can inform dynamic scheduling and new appointment policies based on individual no-show probability.
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