PURPOSE: To understand why patients "no-show" for imaging appointments, and to provide new insights for improving resource utilization. MATERIALS AND METHODS: We conducted a retrospective analysis of nearly 2.9 million outpatient examinations in our radiology information system from 2000 to 2015 at our multihospital academic institution. No-show visits were identified by the "reason code" entry "NOSHOW" in our radiology information system. We restricted data to radiography, CT, mammography, MRI, ultrasound, and nuclear medicine examinations that included all studied variables. These variables included modality, patient age, appointment time, day of week, and scheduling lead time. Multivariate logistic regression was used to identify factors associated with no-show visits. RESULTS: Out of 2,893,626 patient visits that met our inclusion criteria, there were 94,096 no-shows during the 16-year period. Rates of no-show visits varied from 3.36% in 2000 to 2.26% in 2015. The effect size for no-shows was strongest for modality and scheduling lead time. Mammography had the highest modality no-show visit rate of 6.99% (odds ratio [OR] 5.38, P < .001) compared with the lowest modality rate of 1.25% in radiography. Scheduling lead time greater than 6 months was associated with more no-show visits than scheduling within 1 week (OR 3.18, P < .001). Patients 60 years and older were less likely to miss imaging appointments than patients under 40 (OR 0.70, P < .001). Mondays and Saturdays had significantly higher rates of no-show than Sundays (OR 1.52 and 1.51, P < .001). CONCLUSION: Modality type and scheduling lead time were the most predictive factors of no-show. This may be used to guide new interventions such as targeted reminders and flexible scheduling.
PURPOSE: To understand why patients "no-show" for imaging appointments, and to provide new insights for improving resource utilization. MATERIALS AND METHODS: We conducted a retrospective analysis of nearly 2.9 million outpatient examinations in our radiology information system from 2000 to 2015 at our multihospital academic institution. No-show visits were identified by the "reason code" entry "NOSHOW" in our radiology information system. We restricted data to radiography, CT, mammography, MRI, ultrasound, and nuclear medicine examinations that included all studied variables. These variables included modality, patient age, appointment time, day of week, and scheduling lead time. Multivariate logistic regression was used to identify factors associated with no-show visits. RESULTS: Out of 2,893,626 patient visits that met our inclusion criteria, there were 94,096 no-shows during the 16-year period. Rates of no-show visits varied from 3.36% in 2000 to 2.26% in 2015. The effect size for no-shows was strongest for modality and scheduling lead time. Mammography had the highest modality no-show visit rate of 6.99% (odds ratio [OR] 5.38, P < .001) compared with the lowest modality rate of 1.25% in radiography. Scheduling lead time greater than 6 months was associated with more no-show visits than scheduling within 1 week (OR 3.18, P < .001). Patients 60 years and older were less likely to miss imaging appointments than patients under 40 (OR 0.70, P < .001). Mondays and Saturdays had significantly higher rates of no-show than Sundays (OR 1.52 and 1.51, P < .001). CONCLUSION: Modality type and scheduling lead time were the most predictive factors of no-show. This may be used to guide new interventions such as targeted reminders and flexible scheduling.
Authors: Edgar Y Chou; Kari Moore; Yuzhe Zhao; Steven Melly; Lily Payvandi; James W Buehler Journal: J Gen Intern Med Date: 2021-06-22 Impact factor: 5.128
Authors: Whitney L Hensing; Steven P Poplack; Cheryl R Herman; Siobhan Sutcliffe; Graham A Colditz; Foluso O Ademuyiwa Journal: Cancer Date: 2021-04-01 Impact factor: 6.921
Authors: Frederick North; Elissa M Nelson; Rebecca J Buss; Rebecca J Majerus; Matthew C Thompson; Brian A Crum Journal: JMIR Med Inform Date: 2021-12-07