iCONCUR: informed CONsent for Clinical data and biosample Use for Research

 描述（由申请人提供）：对临床护理期间收集的数据的使用保持透明对于在患者和研究人员之间建立信任关系非常重要。我们建议开发一个系统，以了解患者对临床数据共享的偏好，该系统考虑到将共享哪些数据以及谁将成为共享数据的接收者。从试点研究中吸取的教训表明，在真实的临床环境中提供此类选项不会导致大量患者退出数据共享。拟议项目将产生实用工具和知识，以指导知情同意管理系统的开发和实施。我们计划进行一项大规模研究，其中我们将：（1）确定向患者呈现数据共享偏好的最佳方式。具体来说，我们将比较通过简单界面（其中数据类别，如实验室测试和数据接收者，如在非营利机构工作的研究人员，将是可用的）或复杂界面（其中每个数据类别和每个类别的接收者中的项目将是可用的，如基因测试和研究人员在制药行业工作，分别）引发的偏好。这些选择将由研究数据交付团队通过链接到我们的临床数据仓库进行研究。 (2)从39个不同的普通和专科诊所随机抽取1,200名患者，研究与数据共享偏好相关的患者特征。在适用的情况下，我们还将比较患者为自己的数据所做的选择与他们作为他人的替代决策者所做的选择。我们将进行调查，患者可以表明他们对疾病的主观看法，我们将从EHR数据中客观评估疾病的严重程度以进行比较。这将有助于我们了解疾病严重程度是否在数据共享偏好中发挥作用。 (3)统计分析患者偏好对共享数据的影响程度。这一点很重要，这样我们就可以确定为研究而共享的数据的质量。

 DESCRIPTION (provided by applicant): Being transparent about the use of data collected during clinical care is important to establish trust relationships between patients and researchers. We propose to develop a system to elicit patient preferences for clinical data sharing that takes into account what data are going to be shared and who is going to be the recipient of shared data. Lessons learned from a pilot study indicate that providing such options in a real clinical setting does not result in massive patient withdrawal in data sharing. The proposed project will generate practical tools and knowledge to guide the development and implementation of informed consent management systems. We plan to conduct a large-scale study in which we will: (1) Determine the best way to present data sharing preferences to patients. Specifically, we will compare preferences elicited via a simple interface (where data categories, such as laboratory tests, and data recipients, such as researchers working in non-profit institutions, will be available) or a complex interface (where items within each data category and within each category of recipients will be available, such as genetic tests and researchers working in the pharmaceutical industry, respectively). These selections will be honored by the research data delivery team through links to our clinical data warehouse for research. (2) Study patient characteristics associated with data sharing preferences for 1,200 randomly sampled patients from 39 diverse general and specialty clinics. Where applicable, we will also compare patient selections for their own data to selections they would make as surrogate decision makers for others. We will conduct surveys where patients can indicate their subjective perception of disease, and we will objectively assess disease severity from EHR data for comparison. This will help us understand whether disease severity plays a role in data sharing preferences. (3) Statistically analyze the degree to which patient preferences affect shared data. This will be important so we can ascertain the quality of data that are shared for research.