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。在没有直接观察掠夺模式的情况下，调查人员--很像临床医生--经常被报告的依从性所误导，导致对方案真实效果的错误解释。药片计数未能揭示服药时间、丢失或囤积药物的时间，以及患者在预约前通过大量服药来补偿错过服药的“白大褂”依从性。应用研究人员依赖于回溯捕获的数据，这些数据存在自传性和回忆偏差；测量频率较低，可能导致可靠性较差；以及无法捕获可能会随时间变化的细粒度、过程数据。老年学研究特别容易出现报告错误，原因是老年人服用大量药物、剂量频率高、药片之间的相互作用、与老年人相关的认知障碍-所有这些都导致自我报告进一步混乱。对于制药公司来说，数据质量的提高可以迅速将一种新疗法推向市场，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。 各种电子工具已经出现，它们提供了解决方案的各个部分。个人数字助理(PDA)帮助调查人员提出问题并收集数据，这些数据可以传输到主机环境，但不会附加到被测量的行为上。电子干预设备用于在时间范围内测量服药情况，但在一个负担得起、患者友好的便携式设备中，没有一种设备可以同时测量多种药物。这个应用程序需要一个集成的基础设施，以支持原型形式存在的4仓计算机化地堡。总而言之，该系统将提供被动监测的、自然环境下的药片消费的实时数据捕获，并收集对每天提出的研究问题的回应。当建造和测试时，综合研究系统将是一个负担得起的、灵活的和端到端的数据收集基础设施，以帮助人类受试者进行试验。它将在40名老年患者中进行交叉研究，每人服用四种药物，每天回答设备产生的问题。

DESCRIPTION (provided by applicant): Medication noncompliance is highly problematic in pharmaceutical studies. Without direct observation of pilltaking patterns, investigators - much like clinicians-are often misled by reported adherence, resulting in false interpretation of a protocol's true effects. Pill counts fail to reveal timing of intake, lost or hoarded medications, and "white coat" compliance in which patients compensate for missed pills by dosing heavily before appointments. Applied researchers have relied on retrospectively captured data that 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. Gerontological studies are particularly vulnerable to reporting errors due to large quantities of drugs taken by elders, high dosing frequencies, interactions between pills, cognitive impairment that is associated with elder years-all of which result in further confusion in self reports. 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 various parts of a solution. Personal digital assistants (PDAs) help investigators pose questions and collect data that can be transferred to the host environment, but none are attached to the behavior being measured. Electronic medminding devices serve to measure pilltaking in its temporal context but none for multiple medications simultaneously in an affordable, patient-friendly portable device. This application calls for an integrated infrastructure that will support a 4-bin computerized pillbox that exists in prototype form. Together, the system will provide passively monitored, real-time data capture of pill consumption in naturalistic settings, and collect responses to study questions posed daily. When built and tested, the integrated research system will be an affordable, flexible, and end-to-end data collection infrastructure to assist in human subjects trials. It will be tested here in a crossover study among 40 elderly patients, each taking four drugs and responding daily to device-generating questions.