17 Reducing No-Show Rates in Inflammatory Bowel Disease Clinics Using Patient Education and Appointment Confirmation
Background: No show rates in specialty clinics, such as those treating inflammatory bowel disease (IBD), disrupt care continuity and reduce efficiency. This study examined the impact of patient education and live appointment confirmation in reducing no-show rates in an adult IBD clinic. Methods: Over a 7-month period, data was collected on the number of appointments resulting in no-shows. The intervention was then implemented including 2 components. First clinic secretaries called patients to confirm appointments. Secondly, education was provided to patients by the IBD nurse practitioner on the importance of attending follow-up visits. Finally, a survey was administered to the patients who received the intervention, evaluating their intention to attend future appointments and identifying which intervention was more impactful. Results: Prior to the intervention, the no show rate was 24% (454/597 appointments). Following implementation, the rate decreased steadily, reaching 7% (572/615 appointments) in the final month. Patient feedback suggested both interventions were impactful, with many reporting increased awareness and accountability of their care. Conclusions: No-show rates are detrimental both to patients and clinics. Reducing no-show rates is critical for optimizing resource use and improving patient outcomes. This study demonstrates that simple, cost-effective strategies such as live appointment confirmations and patient education can significantly reduce no-show rates. Engaging both clinic staff and providers in patient communication reinforced the importance of follow-up visits in managing chronic conditions such as IBD.
Authors
- Mailenys Ortega
Institutions
- University of Miami (US)
Publication Details
- Journal
- The American Journal of Gastroenterology
- Published
- 2025-12-01
- DOI
- https://doi.org/10.14309/01.ajg.0001172492.31042.55
- Primary Topic
- Healthcare Operations and Scheduling Optimization
- Type
- article
- Field-Weighted Citation Impact
- 0.00