My Data Choices, evaluation of effective consent strategies for patients with behavioral health conditions

我的数据选择，评估患有行为健康问题的患者的有效同意策略

• 批准号: 9124370
• 负责人: MARIA ADELA GRANDO
• 金额: $ 43.04万
• 依托单位: ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-07-01 至 2021-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9124370
• 关键词: Access to Information; Address; Adult; Affect; Alcohol abuse; Attitude; Behavioral; Caring; Categories; Choices and Control; Clinical; Clinical Data; Comprehension; Computerized Medical Record; Consent; Data; Data Set; Diagnosis; Drug abuse; Education; Educational Materials; Electronic Health Record; Electronics; Escitalopram; Ethical Analysis; Ethics; Evaluation; Exercise; Focus Groups; Goals; Health; Individual; Informed Consent; Insurance Carriers; Intervention; Laws; Learning; Lexapro; Link; Medical; Modeling; Multimedia; National Institute of Mental Health; Oral; Outpatients; Participant; Patient Care; Patient Preferences; Patients; Pharmaceutical Preparations; Policies; Privacy; Process; Provider; Randomized; Recommendation; Records; Recruitment Activity; Regulation; Research; Source Code; Specific qualifier value; Strategic Planning; Surveys; System; Tablets; Taxonomy; Technology; Terminology; Testing; Trust; arm; base; behavioral health; care preference; data access; data exchange; data sharing; design; digital; health information technology; improved; interoperability; open source; patient population; patient privacy; preference; public health relevance; research clinical testing; severe mental illness; software systems; tool

 DESCRIPTION (provided by applicant): Little is known about data sharing preferences of patients with behavioral health conditions (BHCs) and their surrogates, and even less is known about the choice of patients with Serious Mental Illness (SMI). Our hypothesis is that, instead of wanting the currently used broad consent models, behavioral health patients and surrogates want a greater degree of choice to determine at a granular level which health information (in particular, sensitive information) to share for care and research. The main goals of the proposed research are to address the open challenges of: (1) identifying categories of sensitive health information that are meaningful for behavioral health patients and surrogates, (2) specifying the identified categories of sharing choices in a precise and uniform way by linking them to standard medical terminologies, (3) understanding providers perspective on implementing patients' and surrogates' driven data sharing choices, (4) deploying and testing an electronic informed consent management tool, that we call "MyChoice" that supports tiered-consent models, (5) helping BCH patients to intelligently exercise granular control by embedding into "MyChoice" educational material on the type of information contained in each data category and potential favorable and unfavorable consequences of restricting data access for care, and (6) deploying and testing "MyChoice" and the Trusted Broker in a context of a behavioral health information exchange (HIE). At the end of the study we will recruit 200 adult patients with BHCs (70 with SMI) and 70 surrogates and randomly assign them to: (i) intervention arm: the recruiter is someone involved in the patient's care; (ii) control arm: the recruiter is not part of the facilitis' care team. We will consent both arms with MyChoice, though their choices will have no effect on the actual data sharing. We will investigate if differences occur in sharing options, levels of comprehension and consent between (i) and (ii) and within the population of patients with BHCs, patients with SMI, and surrogates. Also, we will inspect the electronic medical records of the participants and randomly select 50 encounters occurred within 3 months of consenting with MyChoice. For those encounters we will retrospectively use the Trusted Broker to identify the data that providers could have been restricted to access if privacy preferences were respected. We will use those scenarios to analyze clinical, ethical, policy, regulatory and technical implications.

 描述（由申请人提供）：对行为健康状况（BHC）患者及其代理人的数据共享偏好知之甚少，对严重精神疾病（SMI）患者的选择更是知之甚少。我们的假设是，行为健康患者和代理人希望有更大程度的选择，而不是目前使用的广泛的同意模型，以确定在粒度级别上共享哪些健康信息（特别是敏感信息）进行护理和研究。拟议研究的主要目标是应对以下公开挑战：（1）识别对行为健康患者和代理人有意义的敏感健康信息的类别，（2）通过将所识别的共享选择的类别与标准医学术语联系起来，以精确和统一的方式指定所识别的共享选择的类别，（3）理解提供者对实施患者和代理人驱动的数据共享选择的观点，（4）部署和测试电子知情同意管理工具，我们称之为“MyChoice”，它支持分层同意模型，（5）通过在“MyChoice”中嵌入关于每个数据类别中包含的信息类型以及限制数据访问的潜在有利和不利后果的教育材料，帮助BCH患者智能地进行粒度控制，以及（6）在行为健康信息交换（HIE）的上下文中部署和测试“MyChoice”和可信代理。在研究结束时，我们将招募200名BHC成人患者（70名SMI）和70名代理人，并将其随机分配到：（i）干预组：招募者是参与患者护理的人员;（ii）对照组：招募者不是设施炎护理团队的一部分。我们将同意MyChoice的两个手臂，尽管他们的选择不会对实际的数据共享产生影响。我们将调查（i）和（ii）之间以及BHC患者、SMI患者和代理人人群中的共享选项、理解和同意水平是否存在差异。此外，我们将检查参与者的电子医疗记录，并随机选择50个在同意MyChoice后3个月内发生的事件。对于这些遭遇，我们将追溯使用可信代理来识别如果隐私偏好得到尊重，提供商可能被限制访问的数据。我们将使用这些场景来分析临床，伦理，政策，监管和技术影响。