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高度成问题的。在没有直接观察服药模式的情况下，研究人员——就像临床医生一样——经常被报告的依从性所误导，从而导致对方案真实效果的错误解释。药片计数无法揭示服药时间、丢失或囤积的药物，以及“白大褂”依从性——患者在预约前大量服用药片来弥补错过的药片。应用研究人员依赖于回顾性捕获的数据，这些数据存在自传性和回忆性偏见；测量频率低，可靠性差；并且无法捕获可能随时间变化的细粒度流程数据。由于老年人服用的大量药物、高剂量频率、药物之间的相互作用、与老年相关的认知障碍——所有这些都会导致自我报告的进一步混乱，老年学研究特别容易出现报告错误。对于制药业来说，提高数据质量可以加快新疗法的上市时间，从而节省成本，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的评估周期、数字化时间和专业人员的数量。

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.