Department of Information Technology, Analytics, and Operations, Mendoza College of Business, University of Notre Dame, Notre Dame, IN, United States.
Department of Computer Science, University of Massachusetts Lowell, Lowell, MA, United States.
J Med Internet Res. 2021 May 13;23(5):e26354. doi: 10.2196/26354.
Interventions to define medical jargon have been shown to improve electronic health record (EHR) note comprehension among crowdsourced participants on Amazon Mechanical Turk (AMT). However, AMT participants may not be representative of the general population or patients who are most at-risk for low health literacy.
In this work, we assessed the efficacy of an intervention (NoteAid) for EHR note comprehension among participants in a community hospital setting.
Participants were recruited from Lowell General Hospital (LGH), a community hospital in Massachusetts, to take the ComprehENotes test, a web-based test of EHR note comprehension. Participants were randomly assigned to control (n=85) or intervention (n=89) groups to take the test without or with NoteAid, respectively. For comparison, we used a sample of 200 participants recruited from AMT to take the ComprehENotes test (100 in the control group and 100 in the intervention group).
A total of 174 participants were recruited from LGH, and 200 participants were recruited from AMT. Participants in both intervention groups (community hospital and AMT) scored significantly higher than participants in the control groups (P<.001). The average score for the community hospital participants was significantly lower than the average score for the AMT participants (P<.001), consistent with the lower education levels in the community hospital sample. Education level had a significant effect on scores for the community hospital participants (P<.001).
Use of NoteAid was associated with significantly improved EHR note comprehension in both community hospital and AMT samples. Our results demonstrate the generalizability of ComprehENotes as a test of EHR note comprehension and the effectiveness of NoteAid for improving EHR note comprehension.
干预措施来定义医学术语已被证明可以提高在亚马逊机械土耳其（AMT）众包参与者对电子健康记录（EHR）注释的理解。然而，AMT 参与者可能无法代表一般人群或最有可能患有低健康素养的患者。
在这项工作中，我们评估了一种干预措施（NoteAid）对马萨诸塞州洛厄尔综合医院（LGH）社区医院参与者 EHR 注释理解的效果。
参与者从洛厄尔综合医院（LGH）招募，参加基于网络的 EHR 注释理解 ComprehENotes 测试。参与者被随机分配到对照组（n=85）或干预组（n=89），分别在没有或有 NoteAid 的情况下参加测试。为了进行比较，我们使用了从 AMT 招募的 200 名参与者的样本参加 ComprehENotes 测试（对照组 100 名，干预组 100 名）。
共有 174 名参与者从 LGH 招募，200 名参与者从 AMT 招募。干预组（社区医院和 AMT）的参与者得分均明显高于对照组（P<.001）。社区医院参与者的平均得分明显低于 AMT 参与者的平均得分（P<.001），这与社区医院样本中较低的教育水平一致。教育水平对社区医院参与者的分数有显著影响（P<.001）。
使用 NoteAid 与社区医院和 AMT 样本中 EHR 注释理解的显著提高相关。我们的结果表明，ComprehENotes 作为 EHR 注释理解测试具有普遍性，并且 NoteAid 对提高 EHR 注释理解是有效的。
