TY - JOUR AU - Piette, John D AU - Sussman, Jeremy B AU - Pfeiffer, Paul N AU - Silveira, Maria J AU - Singh, Satinder AU - Lavieri, Mariel S PY - 2013 DA - 2013/07/05 TI -通过避免重复患者报告最大化移动健康监测的价值:自动健康评估服务中抑郁相关症状和依从性问题的预测JO - J Med Internet Res SP - e118 VL - 15 IS - 7 KW -蜂窝电话KW -远程医疗KW -抑郁KW -自我保健AB -背景:交互式语音应答(IVR)呼叫增强了卫生系统识别健康风险因素的能力，从而实现了有针对性的临床随访。然而，重复的评估可能会增加患者退出，并代表失去了收集更多临床有用数据的机会。目的:我们确定了之前的IVR评估在多大程度上预测了抑郁症诊断患者的后续反应，潜在地避免了重复收集相同信息的需要。我们还评估了频繁(即每周)的IVR评估尝试是否比每两周或每月收集的信息更能预测患者的后续报告。方法:使用来自208名抑郁症诊断患者的1050次IVR评估数据，我们检查了四种IVR报告结果的可预测性:中度/重度抑郁症状(PHQ-9得分≥10)，一般健康状况一般/较差，抗抑郁药物依从性差，以及由于精神健康状况不佳而卧床的天数。我们使用训练和测试样本的逻辑模型来预测患者的IVR反应，基于他们最近的五次每周、两周和每月的评估尝试。根据接收算子特征(ROC)曲线和曲线下面积(AUC)的统计比较，评估更频繁评估的边际效益。结果:基于先前的评估反应，患者对其抑郁症状和感知健康状况的报告具有高度可预测性。对于预测中度/重度抑郁症的模型，假设每周评估一次的AUC为0.91 (95% CI 0.89-0.93)，假设每两周评估一次的AUC略低(AUC: 0.89; CI 0.87-0.91) or monthly attempts (AUC: 0.89; CI 0.86-0.91). The AUC for models predicting reports of fair/poor health status was similar when weekly assessments were compared with those occurring biweekly (P value for the difference=.11) or monthly (P=.81). Reports of medication adherence problems and days in bed were somewhat less predictable but also showed small differences between assessments attempted weekly, biweekly, and monthly. Conclusions: The technical feasibility of gathering high frequency health data via IVR may in some instances exceed the clinical benefit of doing so. Predictive analytics could make data gathering more efficient with negligible loss in effectiveness. In particular, weekly or biweekly depressive symptom reports may provide little marginal information regarding how the person is doing relative to collecting that information monthly. The next generation of automated health assessment services should use data mining techniques to avoid redundant assessments and should gather data at the frequency that maximizes the value of the information collected. SN - 14388871 UR - //www.mybigtv.com/2013/7/e118/ UR - https://doi.org/10.2196/jmir.2582 UR - http://www.ncbi.nlm.nih.gov/pubmed/23832021 DO - 10.2196/jmir.2582 ID - info:doi/10.2196/jmir.2582 ER -