Ethical Approaches to Research Use of Clinical Records and Data

描述(由申请人提供)：联邦政府鼓励建立一个全国性的电子健康记录系统(EHR)，加上信息技术的进步，正在迅速产生识别具有准确属性的患者队列的能力。这一过程，众所周知 作为“EHR表型”，将高通量算法应用于电子数据，根据准确的信息星座(例如，人口统计、诊断、程序、化验值、生命体征、药物、生活方式和环境因素)对患者进行分类。EHR表型预计将导致更强大的研究和更低的成本，并是学习支持一系列临床、观察、结果和比较有效性研究的医疗保健系统愿景的关键组成部分。这项事业的最终成功取决于建立和维持公众信任，而耐心的投入至关重要。关于患者是否愿意为研究目的分享他们的数据，他们对这种使用的控制程度，或者他们对知情同意的不同方法的必要性和可接受性的看法，人们知之甚少。此外，电子病历数据远不完美，反映了医疗保健系统固有的噪声和复杂性，因此容易受到不完整、不准确和偏差的影响。使用EHR的研究人员几乎肯定会发现差异(例如，诊断代码和实验室值之间的差异)，并发现他们需要联系患者-要么通知他们严重的潜在健康问题，要么以其他方式解决差异。这是研究人员将越来越多地面临的一个新挑战。拟议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，利用这些县正在进行的两项现有研究，获得丰富的、与政策相关的患者意见和他们的实际行为数据，以帮助填补这些空白。为达致这个目标，我们会：(1)进行半结构性访问，以评估病人是否愿意分享他们的临床资料作研究用途，包括 (2)通过焦点小组研究以及分析研究人员向参与者发出的实际电话录音，调查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与他们的电子健康记录数据之间的差异；以及(3)召开一系列审议民主活动，系统地制定关于同意和接触患者的建议，以告知临床数据用于研究的合乎道德的使用。

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.