Remote health assessments that gather real-world data (RWD) outside clinic settings require a clear understanding of appropriate methods for data collection, quality assessment, analysis and interpretation. Here we examine the performance and limitations of smartphones in collecting RWD in the remote mPower observational study of Parkinson’s disease (PD). Within the first 6 months of study commencement, 960 participants had enrolled and performed at least five self-administered active PD symptom assessments (speeded tapping, gait/balance, phonation or memory). Task performance, especially speeded tapping, was predictive of self-reported PD status (area under the receiver operating characteristic curve (AUC) = 0.8) and correlated with in-clinic evaluation of disease severity (r = 0.71; P < 1.8 × 10⁻⁶) when compared with motor Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). Although remote assessment requires careful consideration for accurate interpretation of RWD, our results support the use of smartphones and wearables in objective and personalized disease assessments.

在诊所环境之外收集真实世界数据 (RWD) 的远程健康评估需要清楚地了解数据收集、质量评估、分析和解释的适当方法。在这里，我们检查了智能手机在帕金森病 (PD) 的远程 mPower 观察研究中收集 RWD 的性能和局限性。在研究开始的前 6 个月内，960 名参与者注册并进行了至少五次自我管理的主动 PD 症状评估（加速敲击、步态/平衡、发声或记忆）。任务表现，尤其是快速敲击，可预测自我报告的 PD 状态（受试者工作特征曲线下面积 (AUC) = 0.8），并与疾病严重程度的临床评估相关（r  = 0.71；P < 1.8 × 10 ^-6）与运动障碍协会-统一帕金森病评定量表（MDS-UPDRS）相比。尽管远程评估需要仔细考虑对 RWD 的准确解释，但我们的结果支持在客观和个性化的疾病评估中使用智能手机和可穿戴设备。