Journal Article

0965 No-show Rates To A Sleep Clinic: Drivers And Determinants

Omeni, Alvan, Espiritu, Joseph, Cheung, David, Sahrmann, Julie

2019

Overview

Introduction Attendance to sleep clinic appointments is imperative to accurately diagnose sleep-related disorders and offer appropriate treatment. As part of our quality assurance program, we assessed predictors of no-show rates at our sleep clinic. We hypothesize that no-show rates can be predicted by appointment type (new vs. established), insurance status, age, sex, appointment time, day of the week, and season. Methods We performed a 10-month, retrospective chart review of patients scheduled at Saint Louis University’s SLUCare Sleep Disorders Center. Multivariable logistic regression was used to determine which factors were independently associated with no-show rates. Results 2,532 patient charts were reviewed and the overall no-show rate was 21.2%. Factors that were associated with a higher incidence of no-show rates included appointment type (new 39.1% vs. established 28.8%, p<.0001) and insurance status (no insurance 47.5% vs. public 28.3% vs private 24.2%, p<.0001). Multivariable logistic regression confirmed associations between no-show rates and new patient status (adjusted OR=2.96, 95%CI: 2.18-4.03) and the absence of health insurance (adjusted OR=1.74, 95%CI: 1.33, 2.27). Age, sex, appointment time, day of the week, and season did not significantly influence no-show rates. Conclusion Independent predictors of no-show appointments included new patient status and lack of health insurance. Our findings will aid future efforts to identify patients with high predictors of nonadherence. Further studies are needed to develop methods to decrease no-show rates once high risk appointments have been identified. Support (If Any) Other studies have described factors that influence no show rates, although none have specifically addressed no-shows for sleep medicine appointments. Knolhoff et al found that patients with limited health literacy and cigarette smoking had higher no-show rates (1). Drewek et al found that appointments scheduled for 30 days or greater had a higher chance of no-show (2). No-show rates increase the cost of healthcare. Kheirkhah et al analyzed no-show data and found that increased no-show rates occurred at subspecialty clinics, equaling a cost of approximately $196 per no-show (3). Reducing no-show rates can improve quality outcomes by maximizing access to care and reducing overall healthcare spending.

• Publisher: Oxford University Press
• Subject: Health care access / Health insurance / Sleep / Therapist patient relationships / Voir dire