Ethical Approaches to Research Use of Clinical Records and Data

临床记录和数据研究使用的道德方法

• 批准号: 8928648
• 负责人: LAURA M. BESKOW
• 金额: $ 37.18万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-25 至 2017-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8928648
• 关键词: Adoption; Algorithms; Area; Attitude; Behavior; Clinical; Clinical Data; Code; Communities; Complement; Confidentiality; Consent; County; Data; Development; Diagnosis; Disease; Electronic Health Record; Enrollment; Environmental Risk Factor; Ethics; Event; Focus Groups; Genomics; Goals; Health; Healthcare Systems; Incentives; Information Technology; Informed Consent; Interview; Laboratory Procedures; Learning; Link; Manuals; Mining; Noise; Outcome; Participant; Patient Self-Report; Patients; Persons; Pharmaceutical Preparations; Phenotype; Policies; Positioning Attribute; Privacy; Process; Protocols documentation; Public Health; Reaction; Recommendation; Records; Research; Research Personnel; Series; Site; Source; Structure; System; Techniques; Telephone; Vision; Writing; base; cohort; comparative effectiveness; cost; deliberative democracy; demographics; effectiveness research; electronic data; lifestyle factors; meetings; novel; public trust; success; tool; willingness

DESCRIPTION (provided by applicant): Federal incentives to create a nationwide system of electronic health records (EHRs), together with advances in information technology, are rapidly leading to the ability to identify cohorts of patients with precise attributes. This process, known as "EHR phenotyping", applies high-throughput algorithms to electronic data to classify patients based on exact constellations of information (e.g., demographics, diagnoses, procedures, laboratory values, vital signs, medications, lifestyle and environmental factors). EHR phenotyping is expected to result in studies with greater power and lower costs, and is a key component of the vision for learning healthcare systems that support an array of clinical, observational, outcomes, and comparative effectiveness research. The ultimate success of this enterprise depends on building and maintaining public trust, and patient input is vital. Little is known about patients' willingness to share their data for research purposes, their preferred level of control over such use, or their perspectives on the need for and acceptability of different approaches to informed consent. In addition, EHR data are far from perfect, reflecting the noise and complexity inherent in the healthcare system and thus subject to incompleteness, inaccuracies, and bias. Researchers using EHRs will almost certainly uncover discrepancies (e.g., between diagnosis codes and lab values), and find themselves in the position of needing to contact patients-either to inform them of a serious potential health concern, or to otherwise resolve the discrepancy. This is a novel challenge that researchers will increasingly confront. The objective of the proposed research is to help fill these gaps by gathering empirical data from patients in four highly diverse counties in the southeastern US, capitalizing on two existing studies taking place in these counties to obtain rich, policy-relevant data both on patients' opinions and their actual behavior. To attain this objective, we will: (1) Conduct semi-structured interviews to assess patients' willingness to share their clinical data for research use, including acceptable approaches to informed consent; (2) Investigate patients' reactions to researcher contact based on the results of EHR phenotyping, through focus group research as well as analyses of audio recordings of actual telephone calls made by researchers to participants to resolve discrepancies between participants' self-reported health information and their EHR data; and (3) Convene a series of deliberative democracy events to systematically develop recommendations concerning consent and contact with patients to inform the ethical use of clinical data for research.

描述（由申请人提供）：联邦激励措施创建全国性电子健康记录系统（EHR）以及信息技术的进步，迅速导致能够识别具有精确属性的患者的同类。这个过程，已知 作为“ EHR表型”，将高通量算法应用于电子数据，以根据信息的确切星座（例如人口统计学，诊断，程序，实验室价值，生命体征，药物，生活方式和环境因素）对患者进行分类。 EHR表型预计将导致具有更大功能和较低成本的研究，并且是学习医疗系统愿景的关键组成部分，这些系统支持一系列临床，观察，结果和比较有效性研究。该企业的最终成功取决于建立和维持公共信任，患者的意见至关重要。关于患者出于研究目的共享数据的意愿，对这种使用的首选控制水平，或者他们对不同方法的需求和可接受性的知情同意方法的观点知之甚少。此外，EHR数据远非完美，反映了医疗保健系统固有的噪声和复杂性，因此会遭受不完整，不准确和偏见。使用EHRS的研究人员几乎可以肯定会发现差异（例如，诊断代码和实验室价值观之间），并发现自己处于需要与患者联系的位置，以告知他们严重的潜在健康问题，或者以其他方式解决差异。这是研究人员将越来越面对的新颖挑战。拟议的研究的目的是通过收集美国东南部四个高度不同县的患者的经验数据来帮助填补这些空白，利用这些县正在进行的两项现有研究，以获取有关患者意见及其实际行为的丰富，政策相关的数据。为了实现这一目标，我们将：（1）进行半结构化访谈，以评估患者分享其临床数据的意愿，包括 可接受的知情同意方法； （2）根据EHR表型的结果，通过焦点小组研究的结果以及研究人员向参与者对参与者进行的实际电话记录进行分析，研究患者对研究人员接触的反应，以解决参与者自我报告的健康信息和他们的EHR数据之间的差异； （3）召集一系列审议民主事件，以系统地制定有关同意并与患者接触的建议，以告知临床数据的道德使用。