TY - JOUR
T1 - Self-scheduling of Screening Mammograms Using an Online Patient Portal
T2 - Initial 8-year Experience at a Multisite Academic Institution
AU - Ambinder, Emily B.
AU - Wang, Annie
AU - Oluyemi, Eniola
AU - Myers, Kelly S.
AU - Mullen, Lisa A.
N1 - Publisher Copyright:
© 2023 American College of Radiology
PY - 2024/1
Y1 - 2024/1
N2 - Objective: The goal of this study was to determine patient factors associated with the use of self-scheduling of screening mammograms (SMs) using an online portal. Methods: All SMs scheduled at our multisite academic institution from January 1, 2015, to December 31, 2022, were included. The frequency of self-scheduling via an online portal was calculated per year. Univariate and multivariate logistic regression models with generalized estimating equation were used to estimate associations between patient characteristics and scheduling format after accounting for correlations between mammograms performed on the same woman. Results: During the study period, 250,369 SMs were performed in 74,860 unique patients (mean age 59 ± 12 years). Of these, 36,200 (14.5%) were self-scheduled via the online portal. Self-scheduling increased each year, from 3.7% in 2015 to 36.9% in 2022. Younger age, non-Black race, being an English speaker, and being from a nondisadvantaged zip code were significant predictors of self-scheduling on univariate and multivariate logistic regression. Age <50 years versus age ≥70 years was the patient characteristic that most strongly predicted the likelihood of self-scheduling (adjusted odds ratio 5.4, 95% confidence interval 5.2-5.6). Conclusions: Over 8 years (2015-2022), utilization of self-scheduling for screening mammography using an online patient portal increased from 3.7% to 36.9%. Age < 50 years was the patient characteristic that most strongly predicted likelihood of self-scheduling.
AB - Objective: The goal of this study was to determine patient factors associated with the use of self-scheduling of screening mammograms (SMs) using an online portal. Methods: All SMs scheduled at our multisite academic institution from January 1, 2015, to December 31, 2022, were included. The frequency of self-scheduling via an online portal was calculated per year. Univariate and multivariate logistic regression models with generalized estimating equation were used to estimate associations between patient characteristics and scheduling format after accounting for correlations between mammograms performed on the same woman. Results: During the study period, 250,369 SMs were performed in 74,860 unique patients (mean age 59 ± 12 years). Of these, 36,200 (14.5%) were self-scheduled via the online portal. Self-scheduling increased each year, from 3.7% in 2015 to 36.9% in 2022. Younger age, non-Black race, being an English speaker, and being from a nondisadvantaged zip code were significant predictors of self-scheduling on univariate and multivariate logistic regression. Age <50 years versus age ≥70 years was the patient characteristic that most strongly predicted the likelihood of self-scheduling (adjusted odds ratio 5.4, 95% confidence interval 5.2-5.6). Conclusions: Over 8 years (2015-2022), utilization of self-scheduling for screening mammography using an online patient portal increased from 3.7% to 36.9%. Age < 50 years was the patient characteristic that most strongly predicted likelihood of self-scheduling.
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U2 - 10.1016/j.jacr.2023.06.040
DO - 10.1016/j.jacr.2023.06.040
M3 - Article
C2 - 37634791
AN - SCOPUS:85180923949
SN - 1546-1440
VL - 21
SP - 141
EP - 146
JO - Journal of the American College of Radiology
JF - Journal of the American College of Radiology
IS - 1
ER -