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

基本信息

批准号：
9292374
负责人：
MARIA ADELA GRANDO
金额：
$ 36.5万
依托单位：
ARIZONA STATE UNIVERSITY-TEMPE CAMPUS
依托单位国家：
美国
项目类别：
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/9292374
关键词：
Access to Information Address Adult Alcohol abuse Attitude Behavioral Caring Categories Choices and Control Clinical Clinical Data Clinical Research Comprehension Computerized Medical Record Consent Data Data Set Diagnosis Drug abuse Education Educational Materials Electronic Health Record Escitalopram Ethics Evaluation Exercise Focus Groups Goals Health Health Services Accessibility Individual Informed Consent Insurance Carriers Intervention Laws Learning Lexapro Link Medical Modeling Multilingualism 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 Tablets Taxonomy Technology Terminology Testing Trust arm base behavioral health care preference consent management systems data access data exchange data sharing design digital health information technology improved interoperability open source patient population patient privacy permissiveness preference public health relevance severe mental illness software systems tool

项目摘要

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（由适用提供）：关于行为健康状况（BHC）及其替代的患者的数据共享偏好的了解知之甚少，对于患有严重精神疾病（SMI）的患者的选择，知之甚少。我们的假设是，行为健康患者和代理人不需要当前使用的广泛同意模型，而是希望在颗粒状水平上确定哪些健康信息（尤其是敏感信息）以共享护理和研究。 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 precision and uniform way by linking them to standard medical terminology, (3) understanding providers perspective on implementing patients' and surrogates' Driven data sharing choices, (4) deploying and testing an electronic知情的同意管理工具，我们称之为支持分层模型的“ Mychoice”，（5）通过将“ Mychoice”的教育材料嵌入每个数据类别中的信息类型，并帮助BCH患者智能地行使颗粒状控制，并在限制限制护理和测试的情况下，以及在限制ANCENTION和ANCENTINATION ANCENTION和6）的情况下的信息和不利的后果，并进行了``Mychoice''和6）。交换（hie）。在研究结束时，我们将招募200名BHC（70例SMI）和70个代理人的成年患者，并将其随机分配给：（i）干预部门：招聘人员是参与患者护理的人；（ii）控制臂：招聘人员不属于面膜炎的一部分。尽管他们的选择对实际数据共享没有影响，但我们将同意两个武器。我们将研究（i）和（ii）之间以及BHCS患者，SMI和替代患者的共享选择，理解水平和同意水平的差异。此外，我们将检查参与者的电子病历，并在同意Mychoice后的3个月内随机选择50次相遇。对于那些相遇，我们将回顾性地使用受信任的经纪人来确定如果尊重隐私偏好，提供商可能会限制提供的数据。我们将使用这些方案来分析临床，道德，政策，监管和技术影响。