公开(公告)号：US07415447B2

公开(公告)日：2008-08-19

申请号：US11324504

申请日：2006-01-03

申请人： Saul Shiffman ,  Michael R. Hufford ,  Jean A. Paty

发明人： Saul Shiffman ,  Michael R. Hufford ,  Jean A. Paty

IPC分类号： G06F17/00 ,  G06N5/00 ,  G06N5/02

CPC分类号： G06Q90/00 ,  G06F19/00 ,  G06Q10/04 ,  G16H10/20 ,  G16H40/20

摘要： A system for developing and implementing empirically derived algorithms to generate decision rules to determine participant noncompliance and fraud with research protocols in clinical trials allows for the identification of complex patterns of variables that detect or predict participant noncompliance and fraud with research protocol, including performance and enrollment goals, in the clinical trial. The data may be used to overall predict the performance of any participant in a clinical trial, allowing selection of participants that tend to produce useful, high-quality results. The present invention can also be used to monitor participant compliance with the research protocol and goals to determine preferred actions to be performed. Optionally, the invention may provide a spectrum of noncompliance, from minor noncompliance needing only corrective feedback, to significant noncompliance requiring participant removal from the clinical trial or from future clinical trials. The algorithms and decision rules can also be domain-specific, such as detecting non-compliance or fraud among subjects in a cardiovascular drug trial, or demographically specific, such as taking into account gender, age or location, which provides for algorithms and decision rules to be optimized for the specific sample of participants being studied.

摘要翻译： 用于开发和实施经验派生算法以生成决策规则以确定临床试验中的研究协议的参与者违规和欺诈的系统允许通过研究方案来识别检测或预测参与者违规和欺诈的复杂变量模式，包括绩效和注册 目标，在临床试验。 数据可用于总体预测临床试验中任何参与者的表现，允许选择倾向于产生有用的高质量结果的参与者。 本发明还可以用于监视参与者遵守研究协议和目标以确定要执行的优选动作。 任选地，本发明可以从仅需要纠正反馈的轻微不合规性到要求参与者从临床试验或未来临床试验中移除的重大不合规提供一系列不合规。 算法和决策规则也可以是域特定的，例如在心血管药物试验中检测受试者的不合规或欺诈，或人口统计特异性，例如考虑性别，年龄或位置，其提供算法和决策规则 针对正在研究的参与者的具体样本进行优化。

公开(公告)号：US06879970B2

公开(公告)日：2005-04-12

申请号：US09825534

申请日：2001-04-02

申请人： Saul Shiffman ,  Michael R. Hufford ,  Jean A. Paty

发明人： Saul Shiffman ,  Michael R. Hufford ,  Jean A. Paty

IPC分类号： G06F15/18 ,  G06F19/00 ,  G06Q10/04 ,  G06Q50/22

CPC分类号： G06Q10/04 ,  G06F19/00 ,  G06Q50/22 ,  G06Q90/00 ,  G16H10/20 ,  G16H40/20

摘要： A system for developing and implementing empirically derived algorithms to generate decision rules to predict subject noncompliance and fraud with research protocols in clinical trials allows for the identification of complex patterns of variables that detect or predict subject noncompliance and fraud with research protocol in the clinical trial. The present invention can also be used to monitor subject compliance with the research protocol to determine preferred actions to be performed. Optionally, the invention may provide a spectrum of noncompliance, from minor noncompliance needing only corrective feedback, to significant noncompliance requiring subject removal from the clinical trial. The algorithms and decision rules can also be domain-specific, such as detecting non-compliance or fraud among subjects in a cardiovascular drug trial, or demographically specific, such as taking into account gender or age which provides for algorithms and decision rules to be optimized for the specific sample of subjects being studied.

摘要翻译： 用于开发和实施经验导出的算法以生成决策规则以用于临床试验中的研究方案来预测受试者不合规和欺诈的系统允许通过临床试验中的研究方案来鉴定检测或预测受试者不合规和欺诈的复杂变量模式。 本发明还可以用于监测与研究协议的对象一致性，以确定要执行的优选动作。 任选地，本发明可以提供一系列不合规，从仅需要纠正反馈的轻微不合规到需要从临床试验中除去主体的重大不合规。 算法和决策规则也可以是域特异性的，例如在心血管药物试验中检测受试者的不合规或欺诈，或人口特异性，例如考虑性别或年龄，其提供要优化的算法和决策规则 对于正在研究的受试者的具体样本。