Predicting No Show in Voice therapy: Avoiding the Missed Appointment Cycle

Autor: Rebecca J. Howell, Ryan M. Collar, John Paul Giliberto, Katelyn Reid, Renee L. Gustin, Kathryn C. Pielage, Meredith E. Tabangin, Mekibib Altaye, Sid Khosla, Briana E. Vamosi, Lauren Mikhail
Rok vydání: 2021
Předmět:
Zdroj: Journal of Voice. 35:604-608
ISSN: 0892-1997
Popis: Summary Introduction Voice therapy plays a critical role in the treatment of voice disorders. Despite positive outcomes in patients who attend voice therapy, otolaryngologists, and speech-language pathologists continue to struggle with patient compliance. Previous studies evaluating the multidisciplinary clinic model have shown better completion, VHI-10 scores, and fewer cancelation and no-shows (NS). We sought to review our own patient experience to better identify factors that predict NS rates in voice therapy. Methods A retrospective chart review of patients at a tertiary medical center were included if they had a scheduled appointment during a 6-month period that was cancelled or a NS. Charts were reviewed for age, gender, race, diagnosis, number of sessions attended, reason for discharge, and attending physician. NS percentage is calculated as a ratio of number cancellations to total number sessions scheduled. A multivariable general linear model was used to examine the association between NS and the listed covariates. Findings The study included 146 patients mean (SD) age 52.7 (16.6), where 62% were female and 72.6% were white. There is evidence that not being seen in a multidisciplinary clinic is significantly associated with NS rates in voice therapy (χ2 = 4.09, P = 0.0431). There is also evidence that non-white race is significantly associated with NS rates in voice therapy (χ2 = 11.76, P = 0.0006). Conclusions Data presented in this study further support the use of a multidisciplinary model to improve NS rates in voice therapy. The relationship between nonwhite patients and lower NS suggests another determining factor in nonadherence to voice therapy.
Databáze: OpenAIRE