Lalor John P, Woolf Beverly, Yu Hong
College of Information and Computer Sciences, University of Massachusetts, Amherst, MA, United States.
Department of Computer Science, University of Massachusetts Lowell, Lowell, MA, United States.
J Med Internet Res. 2019 Jan 16;21(1):e10793. doi: 10.2196/10793.
Patient portals are becoming more common, and with them, the ability of patients to access their personal electronic health records (EHRs). EHRs, in particular the free-text EHR notes, often contain medical jargon and terms that are difficult for laypersons to understand. There are many Web-based resources for learning more about particular diseases or conditions, including systems that directly link to lay definitions or educational materials for medical concepts.
Our goal is to determine whether use of one such tool, NoteAid, leads to higher EHR note comprehension ability. We use a new EHR note comprehension assessment tool instead of patient self-reported scores.
In this work, we compare a passive, self-service educational resource (MedlinePlus) with an active resource (NoteAid) where definitions are provided to the user for medical concepts that the system identifies. We use Amazon Mechanical Turk (AMT) to recruit individuals to complete ComprehENotes, a new test of EHR note comprehension.
Mean scores for individuals with access to NoteAid are significantly higher than the mean baseline scores, both for raw scores (P=.008) and estimated ability (P=.02).
In our experiments, we show that the active intervention leads to significantly higher scores on the comprehension test as compared with a baseline group with no resources provided. In contrast, there is no significant difference between the group that was provided with the passive intervention and the baseline group. Finally, we analyze the demographics of the individuals who participated in our AMT task and show differences between groups that align with the current understanding of health literacy between populations. This is the first work to show improvements in comprehension using tools such as NoteAid as measured by an EHR note comprehension assessment tool as opposed to patient self-reported scores.
患者门户网站正变得越来越普遍，随之而来的是患者获取其个人电子健康记录（EHR）的能力。EHR，尤其是自由文本形式的EHR记录，通常包含医学术语和行话，外行人很难理解。有许多基于网络的资源可用于更多地了解特定疾病或病症，包括直接链接到医学概念的外行定义或教育材料的系统。
我们的目标是确定使用一种这样的工具NoteAid是否会提高EHR记录的理解能力。我们使用一种新的EHR记录理解评估工具，而不是患者自我报告的分数。
在这项研究中，我们将一种被动的自助式教育资源（MedlinePlus）与一种主动资源（NoteAid）进行比较，NoteAid会为系统识别出的医学概念向用户提供定义。我们使用亚马逊土耳其机器人（AMT）招募人员来完成ComprehENotes，这是一项新的EHR记录理解测试。
能够使用NoteAid的个体的平均分数显著高于平均基线分数（原始分数P = 0.008，估计能力P = 0.02）。
在我们进行的实验中发现，与未提供任何资源作为基线的组相比，主动干预使得理解测试的分数显著更高。相比之下,接受被动干预的组与基线组之间没有显著差异。最后，我们分析了参与我们AMT任务的个体的人口统计学特征，并展示了不同组之间的差异与目前对不同人群健康素养的理解相符。这是第一项表明使用NoteAid等工具能提高理解能力的研究，该理解能力是通过EHR记录理解评估工具来衡量的，而非患者自我报告的分数。
