Department of Epidemiology, Gillings School of Global Public Health, The University of North Carolina at Chapel Hill, 2101 McGavran-Greenberg Hall, Chapel Hill, NC, 27599, USA.
Department of Epidemiology, Brown University, Providence, RI, USA.
AIDS Behav. 2019 Feb;23(2):418-426. doi: 10.1007/s10461-018-2215-1.
Missed HIV medical visits predict poor clinical outcomes. We sought to identify patients at high risk of missing visits. We analyzed 2002-2014 data from six large US HIV clinics. At each visit, we predicted the likelihood of missing the next scheduled visit using demographic, clinical, and patient-reported psychosocial variables. Overall, 10,374 participants contributed 105,628 HIV visits. For 17% of visits, the next scheduled appointment was missed. The strongest predictor of a future missed visit was past-year missed visits. A model with only this predictor had area under the receiver operator curve = 0.65; defining "high risk" as those with any past-year missed visits had 73% sensitivity and 51% specificity in correctly identifying a future missed visit. Inclusion of other clinical and psychosocial predictors only slightly improved performance. Past visit attendance can identify those at increased risk for future missed visits, allowing for proactive allocation of resources to those at greatest risk.
错过艾滋病病毒医疗随访会导致不良临床结局。我们试图确定高风险的失访患者。我们分析了来自 6 家美国大型艾滋病病毒诊所的 2002-2014 年数据。在每次就诊时，我们使用人口统计学、临床和患者报告的心理社会变量预测下一次预约就诊的可能性。总体而言，10374 名参与者贡献了 105628 次艾滋病病毒就诊。17%的就诊预约被错过。未来错过就诊的最强预测因素是过去一年的就诊失约。仅包含此预测因素的模型，其受试者工作特征曲线下面积为 0.65；将过去一年有任何失约就诊记录的患者定义为“高风险”，则在正确识别未来失约就诊方面的敏感性为 73%，特异性为 51%。纳入其他临床和心理社会预测因素仅略微提高了性能。过去的就诊出勤率可以识别出未来失访风险较高的患者，从而可以为风险最高的患者主动分配资源。
