Pills & Patient Behavior:Smarter Experience Tracking
Pills & Patient Behavior:Smarter Experience Tracking
批准号:
7455833
负责人:
Vesta Brue
金额:
$51.82万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-02-01 至 2010-04-30
关键词:
AddressAdherenceAgreementAppointmentBehaviorBiological MarkersBiosensorCaregiversCerealsClinical TrialsCommunicationConditionConsumptionControl GroupsCopyrightCost SavingsCountDailyDataData CollectionData QualityDevelopmentDevice DesignsDevicesDisclosureDrug PrescriptionsDrug usageElderlyElectronicsEvaluationEventEyedropsFeedbackFocus GroupsFrequenciesGenerationsGerontologyHealthHealth StatusHousingHuman ResourcesIndividualIntakeInternetLeadMarketingMeasurementMeasuresMethodsModelingModificationMonitorNumbersOintmentsOlder PopulationOnline SystemsPaperParticipantPatient Self-ReportPatientsPatternPerformancePharmaceutical PreparationsPharmacologic SubstancePhasePhase II Clinical TrialsPopulationPreparationProcessProtocols documentationPurposeQuestionnairesRandomized Controlled Clinical TrialsRandomized Controlled TrialsRateReadingReportingResearchResearch InfrastructureResearch PersonnelSamplingScheduleScoreSmall Business Funding MechanismsSmall Business Innovation Research GrantSolidSolutionsSpecific qualifier valueStatistical Data InterpretationSystemTelephoneTestingTimeUnited States National Institutes of HealthUpper armcapsulecaregivingcommercializationcomputerized data processingconsumption measuresdata collection evaluationdaydesigndiariesengineering designexperienceimprovedmedication compliancemembermonitoring devicenovelolder patientpillpreferenceprototyperesponsetoolusability
中文摘要
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——很像临床医生——经常被报告的依从性误导,导致对方案真正功效的错误解释。药片计数不能显示服药时间,丢失或囤积的药物,以及预约前的“白大褂”依从性。应用研究人员依靠回忆问卷收集自我报告的总结数据,并使用简单的纸笔日记在自然环境中自我监测摄入量。这种回顾性捕获的数据存在自传性和回忆性偏差;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。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。各种各样的电子工具已经出现,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的服用时间。该提案要求一个集成系统,在自然环境中提供被动监测,实时数据捕获,并收集对研究问题的回答,同时还跟踪实时药物摄入。药物依从性在药物研究中存在问题。该提案提出了一个集成系统,该系统可以被动地监控自然环境下的实时用药情况,收集对研究问题的回答,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,每天上传他们的健康状况数据。
英文摘要
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.
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科研奖励(0)
会议论文
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