Abstract：
To evaluate sociodemographic and medical predictors of patient return to a neurofibromatosis subspecialty clinic.
Data were collected from the Washington University Neurofibromatosis Clinical Program electronic medical records. A total of 713 subjects with initial visits to the Washington University Neurofibromatosis Clinical Program between July 1, 2005 and December 18, 2020 were included. Variables collected included sex, race, ethnicity, age, date of first visit, place of residence, diagnosis, insurance payer, physician recommendation for return, and subject return. Return rates for each demographic group were calculated. Bivariate analyses were performed to inform variable inclusion in the model, and a binary logistic regression model was calculated to predict subject return.
The overall return rate was 76%. The binary logistic regression model was statistically significant (χ29 = 131.094; P < .001) and showed that subjects who self-identified as Black and/or African American, presented with or received a diagnosis of café-au-lait macules at their initial visit, were from a rural area, were older, or who lived farther from the Washington University Neurofibromatosis Clinical Program were less likely to return to clinic.
These findings support the implementation of tailored communication and monitoring interventions to improve the care for children with neurofibromatosis type 1.
Data were collected from the Washington University Neurofibromatosis Clinical Program electronic medical records. A total of 713 subjects with initial visits to the Washington University Neurofibromatosis Clinical Program between July 1, 2005 and December 18, 2020 were included. Variables collected included sex, race, ethnicity, age, date of first visit, place of residence, diagnosis, insurance payer, physician recommendation for return, and subject return. Return rates for each demographic group were calculated. Bivariate analyses were performed to inform variable inclusion in the model, and a binary logistic regression model was calculated to predict subject return.
The overall return rate was 76%. The binary logistic regression model was statistically significant (χ29 = 131.094; P < .001) and showed that subjects who self-identified as Black and/or African American, presented with or received a diagnosis of café-au-lait macules at their initial visit, were from a rural area, were older, or who lived farther from the Washington University Neurofibromatosis Clinical Program were less likely to return to clinic.
These findings support the implementation of tailored communication and monitoring interventions to improve the care for children with neurofibromatosis type 1.
摘要：
评估患者重返神经纤维瘤病亚专科诊所的社会人口统计学和医学预测因素。
数据来自华盛顿大学神经纤维瘤病临床项目电子病历。包括在2005年7月1日至2020年12月18日期间初次访问华盛顿大学神经纤维瘤病临床计划的总共713名受试者。收集的变量包括性别，种族,种族,年龄,第一次访问的日期,居住地,诊断,保险付款人,医生建议返回，主题返回。计算每个人口统计组的回报率。进行了双变量分析，以告知模型中的变量包含，并计算二元逻辑回归模型来预测受试者的回报。
总回报率为76%。二元logistic回归模型具有统计学意义(χ29=131.094;P<.001)，表明自我识别为黑人和/或非洲裔美国人的受试者，在初次就诊时被诊断出或被诊断为咖啡斑，来自农村地区，年纪大了,或者住在离华盛顿大学神经纤维瘤病临床项目更远的人不太可能回到诊所。
这些发现支持实施量身定制的沟通和监测干预措施，以改善对1型神经纤维瘤病患儿的护理。
数据来自华盛顿大学神经纤维瘤病临床项目电子病历。包括在2005年7月1日至2020年12月18日期间初次访问华盛顿大学神经纤维瘤病临床计划的总共713名受试者。收集的变量包括性别，种族,种族,年龄,第一次访问的日期,居住地,诊断,保险付款人,医生建议返回，主题返回。计算每个人口统计组的回报率。进行了双变量分析，以告知模型中的变量包含，并计算二元逻辑回归模型来预测受试者的回报。
总回报率为76%。二元logistic回归模型具有统计学意义(χ29=131.094;P<.001)，表明自我识别为黑人和/或非洲裔美国人的受试者，在初次就诊时被诊断出或被诊断为咖啡斑，来自农村地区，年纪大了,或者住在离华盛顿大学神经纤维瘤病临床项目更远的人不太可能回到诊所。
这些发现支持实施量身定制的沟通和监测干预措施，以改善对1型神经纤维瘤病患儿的护理。
