Pills & Patient Behavior:Smarter Experience Tracking

描述（由申请人提供）：药物不依从性在药物研究中是一个很大的问题。由于没有对服药模式的直接观察，研究人员--就像临床医生一样--经常被报告的依从性所误导，导致对方案真实疗效的错误解释。药丸计数无法揭示摄入时间，丢失或囤积的药物，以及预约前的"白色外套"依从性。应用研究者依靠回忆问卷来收集自我报告的汇总数据，并使用简单的纸笔日记来自我监测自然环境中的摄入量。这种回顾性捕获的数据遭受自传和回忆偏差;测量频率低，这可能导致可靠性差;以及无法捕获细粒度的过程数据，这些数据可能会随着时间的推移而转移和变化。对于制药公司来说，提高数据质量可以加快新疗法的上市时间，从而节省成本并减轻痛苦。更可靠的数据收集方法可以减少药物在商业化之前需要进行评估的时间，数字化时间和专业人员的数量。各种电子工具已经出现，提供了部分解决方案，但没有一个可以同时测量多种药物的时间背景下的服药情况。该提案要求建立一个集成系统，在自然环境中提供被动监测的实时数据捕获，并收集对研究问题的响应，同时还跟踪药物的实时摄入。药物依从性在药学研究中是个问题。该提案提出了一种集成系统，该系统被动地监测自然环境中的实时药物摄入，收集对研究问题的响应，通过自动拨号电话上传来传达使用数据，并与远程生物传感器无线连接并每天上传其健康状况数据。

DESCRIPTION (provided by applicant): Medication noncompliance is highly problematic in pharmaceutical studies. Without direct observation of pill-taking patterns, investigators - much like clinicians - are often misled by reported adherence, resulting in false interpretation of a protocol's true efficacy. Pill counts fail to reveal timing of intake, lost or hoarded medications, and "white coat" compliance before appointments. Applied researchers have relied on recall questionnaires for collecting self-reported summary data and the use of simple paper and pencil diaries for self-monitoring intake in naturalistic contexts. Such retrospectively captured data suffer from autobiographical and recall biases; low frequency of measurement, which may result in poor reliability; and inability to capture fine-grained, process data that may shift and change over time. For pharmaceuticals, improved data quality can lead to rapid time to market for a new therapy, and with it, cost savings and alleviation of suffering. More reliable data collection methods can reduce the period a drug needs to be under evaluation, its digitalization time, and number of specialized personnel before it can be commercialized. Various electronic tools have emerged that provide part of the solution, but none that measure pill-taking in its temporal context for multiple medications at once. This proposal calls for an integrated system that provides passively monitored, real-time data capture in naturalistic settings, and collects responses to study questions, while it also tracks real-time intake of medications. Medication adherence is problematic in pharmaceutical studies. This proposal addresses an integrated system that passively monitors real-time meds-taking in naturalistic settings, collects responses to study questions, communicates usage data via auto-dialed telephone uploads, and wirelessly connects with remote biosensors and uploads their health status data daily.