Pills & Patient Behavior:Smarter Experience Tracking

描述(由申请人提供)：在药学研究中，药物不依从性是非常有问题的。在没有直接观察服药模式的情况下，研究人员--很像临床医生--经常被报告的依从性所误导，导致对方案真正有效性的错误解释。药片计数未能揭示服药时间、遗失或囤积的药物，以及预约前的“白大褂”依从性。应用研究人员依靠回忆问卷来收集自我报告的总结数据，并使用简单的纸和笔日记来自我监控自然主义背景下的摄入量。这种回溯捕获的数据存在自传性和回忆偏差；测量频率较低，这可能导致可靠性较差；以及无法捕获可能随时间转移和变化的细粒度、过程数据。对于制药来说，数据质量的提高可以加快新疗法的上市时间，从而节省成本和减轻痛苦。更可靠的数据收集方法可以减少药物在商业化之前需要接受评估的时间、数字化时间和专业人员数量。已经出现了各种电子工具，它们提供了部分解决方案，但没有一种工具可以同时测量多种药物在时间背景下的服药量。这项提案要求建立一个集成系统，在自然环境中提供被动监控的实时数据捕获，并收集对研究问题的反应，同时还跟踪药物的实时摄入量。药物依从性在药学研究中是有问题的。这项提案涉及一个集成系统，该系统在自然环境下被动监控实时用药，收集对研究问题的回应，通过自动拨号电话上传交流使用数据，并与远程生物传感器无线连接并每天上传其健康状态数据。

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.