From the Department of Orthopaedic Surgery, Boston Medical Center (Ms. Curry, Ms. Pevear, Ms. Cipriani, and Dr. Smith), the Department of Public Health & Community Medicine (Dr. Tybor and Mr. Jonas), Department of Orthopaedic Surgery, Tufts University School of Medicine, and the Tufts University School of Medicine (Mr. Mason), Boston, MA.
J Am Acad Orthop Surg. 2020 Nov 15;28(22):e1006-e1013. doi: 10.5435/JAAOS-D-19-00550.
Patient physical health and provider financial health are both affected when patients are unable to attend scheduled clinic appointments. The purpose of this study is to identify risk factors for patients missing appointments to better target interventions to improve appointment attendance.
We reviewed scheduled arthroplasty appointments at an urban academic orthopaedic clinic over a 3-year period. We collected information including sex, race, distance to clinic, language, insurance, median income of home zip code, appointment day, time, precipitation, and temperature. Mixed-level multiple logistic regression was used to model the odds of missing appointments in Stata v14.
Overall, 8,185 visits for 3,081 unique patients were reviewed and 90.7% of appointments were attended. After controlling for time and day of appointment, distance from the clinic, and the primary language spoken, patients with government insurance were two times as likely to miss an appointment compared with privately insured patients. White patients were two times as likely to attend scheduled appointments compared with black/Hispanic patients. Younger patients (<50 years) and older patients (>73 years) were 2.7 times and 1.8 times, respectively, more likely to miss appointments compared with those aged between 65 and 72 years. Appointments on the most temperate days were more likely to be missed, and those on the coldest days (14°F to 36°F) and warmest days (69°F to 89°F) were less likely to be missed.
Appointment no shows are associated with sociodemographic and environmental factors. This information is valuable to help better delineate novel ways to better serve these patient populations.
当患者无法按时参加预约门诊时，会同时影响患者的身体健康和医务人员的经济收入。本研究旨在确定导致患者失约的风险因素，以便更好地针对改善预约就诊率的干预措施进行目标定位。
我们回顾了 3 年内某城市学术骨科诊所的关节置换预约情况。我们收集了包括性别、种族、与诊所的距离、语言、保险类型、家庭邮政编码所在地区的中位数收入、预约日期、时间、降水量和温度等信息。我们使用 Stata v14 中的混合水平多项逻辑回归模型来分析失约的可能性。
总体而言，我们共分析了 3081 名患者的 8185 次就诊记录，其中 90.7%的预约得到了遵守。在控制了预约时间和日期、距离诊所的远近以及主要使用语言等因素后，与私人保险患者相比，拥有政府保险的患者失约的可能性是其两倍。与黑人和/或西班牙裔患者相比，白人患者按时参加预约的可能性是其两倍。与 65 至 72 岁之间的患者相比，年龄较小（<50 岁）和较大（>73 岁）的患者失约的可能性分别增加了 2.7 倍和 1.8 倍。在天气最温和的日子里，预约更有可能被取消，而在天气最冷（14°F 至 36°F）和最暖和（69°F 至 89°F）的日子里，预约被取消的可能性较小。
预约失约与社会人口学和环境因素有关。这些信息对于帮助更好地确定服务这些患者群体的新方法非常有价值。
