Systematic Design of Meaningful Presentations of Medical Test Data for Patients

描述（由申请人提供）：以患者为中心的护理方法和健康信息技术的进步（例如，电子健康记录的患者门户）正在增加患者直接获得可识别健康状况的医学检测结果的频率 关注，监测健康状况或预测未来的健康风险。原则上，这些数据使患者能够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。对于这些患者来说，“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他们需要考虑采取什么行动。这样的数据可以，从字面上看，“毫无意义”，病人可能会忽略这些信息，即使他们完全“知情”的决策。“我们建议借鉴设计科学，决策心理学，人机交互和健康传播的研究方法，并将其整合到一个单一的，高度创新的研究过程中，该过程将解决如何最好地向糖尿病患者提供血红蛋白A1c值和类似的测试结果的问题，作为无意义的医学测试数据的更大问题的一个范例。我们将（a）从多个角度定义问题空间，（B）阐明当我们向糖尿病患者展示他们的测试结果时，我们希望实现什么，以及（c）确定提高数据意义的可能方法。我们的迭代研究方法包括三个阶段。在第一阶段，我们将使用密集的“深潜”设计会议（从设计科学中借鉴的方法），由多学科团队将健康沟通和人机交互方面的专家与执业临床医生和专家患者结合起来。这些会议将确定糖尿病患者对测试结果数据的需求与向患者提供此类数据的格式之间的差异，确定何时低算术技能将成为患者解释和使用此类数据的障碍，并集思广益潜在的解决方案概念。在第2阶段，我们将使用（a）用户体验设计会议和（B）大样本、多因素、随机对照实验的迭代序列对拟议设计进行严格的比较评估，以确定何种格式使血红蛋白A1 c值和其他类型的测试数据最有意义，并有助于患者做出明智的医疗决策。在第3阶段，我们将采用我们确定的测试结果通信“最佳实践”，并开发、编程和传播测试结果“显示生成器”应用程序，该应用程序将能够与现有的电子健康记录系统和其他应用程序集成，并将通过免费网站提供给患者。

DESCRIPTION (provided by applicant): 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 manage 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.