Systematic Design of Meaningful Presentations of Medical Test Data for Patients

为患者有意义地呈现医学测试数据的系统设计

• 批准号: 8627732
• 负责人: BRIAN J ZIKMUND-FISHER
• 金额: $ 48.86万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-09-30 至 2016-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8627732
• 关键词: Systematic; Design; Meaningful; Presentations; Medical

Both patient-centered care approaches and health information technology advances (e.g. patient portals to electronic health records) are increasing how often patients are directly presented with medical test results that identify health concerns, monitor health status, or predict future health risk. In principle, such data enable patients to actively mange health conditions and participate in care decisions. In practice, availability of data may not result in understanding, as test results are often presented in confusing formats with little context. Many patients, especially those with lower numeracy skills (i.e., poor ability to draw meaning from numbers), may be unable to interpret test outcome data and use it in decision making. For these patients, "knowing" test results or risk estimates does not ensure that they understand what those numbers imply or what actions they need to consider. Such data can be, quite literally, "meaning-less," and patients are likely ignore such information in decision making even when they are fully "informed." We propose to draw on research methodologies from design science, decision psychology, human- computer interaction, and health communication and integrate them into a single, highly innovative research process that will tackle the problem of how best to present Hemoglobin A1c values and similar test results to patients with diabetes as an exemplar of the larger problem of meaningless medical test data. We will (a) define the problem space from multiple perspectives, (b) clarify what we can hope to achieve when we present diabetic patients with their test results, and (c) and identify possible approaches for improving data meaningfulness. Our iterative research approach involves three phases. In Phase 1, we will use intensive "deep dive" design sessions (a methodology borrowed from design science) with a multidisciplinary team combining experts in health communication and human-computer interaction with both practicing clinicians and expert patients. These sessions will identify discrepancies between diabetic patient needs for test result data and the formats in which such data are provided to patients, identify when low numeracy skills will be a barrier to patient interpretation and use of such data, and brainstorm potential solution concepts. In Phase 2, we will conduct rigorous comparative evaluations of proposed designs using (a) user-experience design sessions, and (b) an iterative sequence of large-sample, multi-factorial, randomized-controlled experiments in order to identify what formats make Hemoglobin A1c values and other types of test data maximally meaningful and useful for facilitating informed patient decisions about medical care. In Phase 3, we will take our identified test results communication "best practices" and develop, program, and disseminate a test results "display generator" application that will be able to be integrated with existing electronic health record systems and other applications and will be made available to patients via a freely available website.

以患者为中心的护理方法和健康信息技术的进步（例如， 电子健康记录）正在增加直接向患者呈现医学测试结果的频率， 识别健康问题、监测健康状况或预测未来的健康风险。原则上，这些数据使 患者积极管理健康状况并参与护理决策。在实践中，数据的可用性 可能不会导致理解，因为测试结果通常以混乱的格式呈现，几乎没有上下文。 许多患者，特别是那些计算能力较低的患者（即，从数字中提取意义的能力差）， 可能无法解释测试结果数据并将其用于决策。对于这些患者，“知道”测试 结果或风险估计并不能确保他们理解这些数字意味着什么，或者他们应该采取什么行动。 需要考虑。这样的数据可以，从字面上看，“毫无意义”，患者可能会忽略这些数据。 即使他们完全“知情”，决策过程中的信息也是如此。" 我们建议借鉴设计科学、决策心理学、人类学和心理学的研究方法， 计算机交互和健康交流，并将它们整合到一个单一的，高度创新的研究中。 该过程将解决如何最好地呈现血红蛋白A1c值和类似测试结果的问题， 糖尿病患者作为一个例子，更大的问题，毫无意义的医疗测试数据。我们将（a） 从多个角度定义问题空间，（B）阐明当我们提出问题时，我们希望实现什么 糖尿病患者的测试结果，以及（c）并确定改善数据的可能方法 意义我们的迭代研究方法包括三个阶段。在第一阶段，我们将使用密集型 与多学科团队进行“深度潜水”设计会议（从设计科学中借鉴的方法） 将健康传播和人机交互方面的专家与执业临床医生相结合， 专家患者这些会议将确定糖尿病患者对测试结果数据需求之间的差异 以及向患者提供此类数据的格式，确定低计算能力何时会成为障碍 耐心地解释和使用这些数据，并集思广益潜在的解决方案的概念。在第二阶段，我们将 使用（a）用户体验设计会议，对拟议设计进行严格的比较评估， (b)大样本、多因子、随机对照实验的迭代序列，以识别 什么格式使血红蛋白A1c值和其他类型的测试数据最有意义和有用， 帮助患者做出关于医疗护理的知情决定。在第三阶段，我们将把我们确定的测试结果 交流“最佳实践”，开发、编程和传播测试结果“显示生成器” 该应用程序将能够与现有的电子健康记录系统和其他 申请，并将通过免费网站提供给患者。