Chiam Mckenzee, Kunselman Allen R, Chen Michael C
From the Department of Ophthalmology (MC, MCC), Pennsylvania State College of Medicine, Hershey, Pennsylvania, USA.
Department of Public Health Sciences (ARK), Pennsylvania State College of Medicine, Hershey, Pennsylvania, USA.
Am J Ophthalmol. 2021 Sep;229:210-219. doi: 10.1016/j.ajo.2021.02.020. Epub 2021 Feb 21.
This study aimed to identify patient and appointment characteristics associated with no-shows to new patient appointments at a US academic ophthalmology department.
Cross-sectional study.
This was a study of all adult patients with new patient appointments scheduled with an attending ophthalmologist at Penn State Eye Center between January 1 and December 31 of 2019. A multiple logistic regression model was used to assess the association between characteristics and no-show status.
Of 4,628 patients, 759 (16.4%) were no-shows. From the multiple logistic regression model, characteristics associated with no-shows were age (Odds Ratio (OR) for 18-40 years vs. >60 years: 3.41, 95% Confidence Interval (CI) 2.57, 4.51, p <0.001 and OR for 41-60 years vs. >60 years: 2.14, 95% CI 1.67, 2.74, p<0.001), median household income (OR for <$35,667 vs. >$59,445: 1.59, 95% CI 1.08, 2.34, p<0.001), insurance (OR for None vs. Medicare: 6.92, 95% CI 4.41, 10.86, p<0.001 and OR for Medicaid vs. Medicare: 1.54, 95% CI 1.18, 2.01, p=0.002), race (OR for Black vs. White: 2.62, 95% CI 2.00, 3.43, p<0.001 and OR for Other vs. White: 2.02, 95% CI 1.58, 2.59, p<0.001), and commute distance (OR for 5-10 mi vs. ≤5 mi: 1.73, 95% CI 1.17, 2.55, p=0.006). Appointments with longer lead times and scheduled with glaucoma or retina specialists were also significantly associated with greater no-shows.
Certain patient and appointment characteristics were associated with no-show status. These findings may assist in the development of targeted interventions at the patient, practice, and health system levels to improve appointment attendance.
本研究旨在确定与美国一家学术眼科部门新患者预约未就诊相关的患者及预约特征。
横断面研究。
本研究纳入了2019年1月1日至12月31日期间在宾夕法尼亚州立大学眼科中心预约了主治眼科医生新患者就诊的所有成年患者。使用多元逻辑回归模型评估特征与未就诊状态之间的关联。
在4628名患者中，759名（16.4%）未就诊。从多元逻辑回归模型来看，与未就诊相关的特征包括年龄（18 - 40岁与>60岁相比的优势比（OR）：3.41，95%置信区间（CI）2.57，4.51，p<0.001；41 - 60岁与>60岁相比的OR：2.14，95%CI 1.67，2.74，p<0.001）、家庭收入中位数（<$35,667与>$59,445相比的OR：1.59，95%CI 1.08，2.34，p<0.001）、保险类型（无保险与医疗保险相比的OR：6.92，95%CI 4.41，10.86，p<0.001；医疗补助与医疗保险相比的OR：1.54，95%CI 1.18，2.01，p = 0.002）、种族（黑人与白人相比的OR：2.62，95%CI 2.00，3.43，p<0.001；其他种族与白人相比的OR：2.02，95%CI 1.58，2.59，p<0.001）以及通勤距离（5 - 10英里与≤5英里相比的OR：1.73，95%CI 1.17，2.55，p = 0.006）。提前预约时间更长以及预约青光眼或视网膜专科医生的预约也与更高的未就诊率显著相关。
某些患者及预约特征与未就诊状态相关。这些发现可能有助于在患者、医疗机构和卫生系统层面制定有针对性的干预措施，以提高预约就诊率。
