Gesture Based Medication Adherence Confirmation for Clinical Trials

临床试验中基于手势的药物依从性确认

• 批准号: 8199012
• 负责人: Adam Hanina
• 金额: $ 27.32万
• 依托单位: AI CURE TECHNOLOGIES, LLC
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-06 至 2013-03-05
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8199012
• 关键词: Address; Adherence; Attention; Behavior; Biomedical Research; Blood; Bulla; Caring; Cessation of life; Chronic; Clinical Trials; Communities; Computer software; Controlled Environment; Data; Devices; Disease; Electronics; Face; Gestures; Goals; Health; Health Care Costs; Healthcare Systems; Human; Hypertension; Incentives; Instruction; Intervention; Interview; Link; Marketing; Measures; Medical; Medication Systems; Medicine; Methods; Monitor; Morbidity - disease rate; Movement; New York; Oral cavity; Outcome; Participant; Patient Care; Patient Education; Patient Monitoring; Patient Self-Report; Patients; Performance; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Policy Maker; Population; Privacy; Protocols documentation; Provider; Regimen; Reliance; Research; Risk; Safety; Security; Self Administration; Sensitivity and Specificity; Series; Serious Adverse Event; Site; Small Business Innovation Research Grant; Solutions; Staging; Supervision; System; Systems Analysis; Technology; Testing; Time; Work; base; behavior observation; commercial application; cost; diaries; drug efficacy; improved; laptop; medication compliance; patient population; pill; population health; success; tool; trend; usability

DESCRIPTION (provided by applicant): Ai Cure Technologies LLC, was established in 2009 to develop webcam software solutions for mobile devices and other computing platforms that automate and reduce the cost of monitoring patient behavior and medication adherence. Poor medication adherence is one of the healthcare system's greatest challenges. More than two million serious adverse events and about 100,000 deaths occur annually due to this problem. Total US healthcare costs of drug-related morbidity, including poor adherence, are estimated at $290 billion per year. In clinical trials, adherence levels for populations with chronic conditions range from 43% to 78%, the high cost of clinical trials being partly attributable to inefficiencies created by poor adherence. As clinical trials become larger, and more move outside the US, tracking patient behavior becomes more difficult, as does the burden on the FDA to monitor these sites. Traditional monitoring methods such as pill counting, patient interviews, and blood work have proven unreliable. Indeed, a recent clinical trial employing these traditional monitoring methods was confirmed to have failed for poor medication adherence. Products such as smart blister packs and MEMS caps are costly and do not confirm medication has been taken. Direct observation therapy is effective to confirm medication adherence; but is labor-intensive, patient intrusive, and expensive. Ai Cure Technologies will provide a webcam software solution for distribution by clinical trial sponsors to automate direct observation of medication administration and provide an audit trail of medication adherence. The solution will provide reliable data to the research community and policy-makers to improve overall health outcomes and rein in soaring costs. The solution will also act as a tool for the FDA to better regulate trials before drugs come to market. PUBLIC HEALTH RELEVANCE: In clinical trials, whether or not participants take their prescribed medication and to what degree is neither well understood nor reliably monitored through existing and antiquated methods such as pill counting or patient interviews. This means that it is difficult to provide an accurate assessment on drug efficacy or safety within a prescribed regimen and over the course of a clinical trial. AiView will provide a system for automatically determining medication adherence of clinical trial patients, and allow access to this data by clinical trial managers.

描述(申请人提供)：AI Cure Technologies LLC成立于2009年，旨在为移动设备和其他计算平台开发网络摄像头软件解决方案，以自动化并降低监测患者行为和服药依从性的成本。服药依从性差是医疗体系面临的最大挑战之一。由于这个问题，每年发生200多万起严重不良事件，约10万人死亡。据估计，美国每年因药物相关疾病(包括依从性差)而产生的医疗总成本为2900亿美元。在临床试验中，慢性病患者的依从性水平从43%到78%不等，临床试验的高成本部分归因于依从性差造成的效率低下。随着临床试验变得更大，更多的试验转移到美国以外，跟踪患者行为变得更加困难，FDA监测这些地点的负担也变得更加困难。传统的监测方法，如药片计数、患者访谈和血液检查已被证明是不可靠的。事实上，最近一项使用这些传统监测方法的临床试验被证实因服药依从性差而失败。智能泡罩包装和MEMS盖子等产品价格昂贵，而且不能确认是否已经服用了药物。直接观察疗法是确认服药依从性的有效方法，但劳动密集型、患者侵入性和费用昂贵。AI Cure Technologies将提供一个网络摄像头软件解决方案，供临床试验赞助商分发，以自动直接观察用药情况，并提供用药依从性的审计跟踪。该解决方案将为研究界和政策制定者提供可靠的数据，以改善整体健康结果并控制飙升的成本。该解决方案还将成为FDA在药物上市前更好地监管试验的工具。 与公共卫生相关：在临床试验中，参与者是否服用处方药物以及服用程度如何，既不能很好地理解，也不能通过现有的过时方法(如药片计数或患者访谈)进行可靠监测。这意味着，在规定的方案内和临床试验过程中，很难提供对药物有效性或安全性的准确评估。AiView将提供一个自动确定临床试验患者服药依从性的系统，并允许临床试验经理访问这些数据。