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面向患者的免疫可视化设计会影响任务表现:四种电子可视化工具的实验比较。

Design of patient-facing immunization visualizations affects task performance: an experimental comparison of 4 electronic visualizations.

机构信息

School of Nursing, University of Minnesota, Minneapolis, MN 55455, United States.

Institute for Health Informatics, University of Minnesota, Minneapolis, MN 55455, United States.

出版信息

J Am Med Inform Assoc. 2024 Nov 1;31(11):2429-2439. doi: 10.1093/jamia/ocae125.

Abstract

OBJECTIVE

This study experimentally evaluated how well lay individuals could interpret and use 4 types of electronic health record (EHR) patient-facing immunization visualizations.

MATERIALS AND METHODS

Participants (n = 69) completed the study using a secure online survey platform. Participants viewed the same immunization information in 1 of 4 EHR-based immunization visualizations: 2 different patient portals (Epic MyChart and eClinicWorks), a downloadable EHR record, and a clinic-generated electronic letter (eLetter). Participants completed a common task, created a standard vaccine schedule form, and answered questions about their perceived workload, subjective numeracy and health literacy, demographic variables, and familiarity with the task.

RESULTS

The design of the immunization visualization significantly affected both task performance measures (time taken to complete the task and number of correct dates). In particular, those using Epic MyChart took significantly longer to complete the task than those using eLetter or eClinicWorks. Those using Epic MyChart entered fewer correct dates than those using the eLetter or eClinicWorks. There were no systematic statistically significant differences in task performance measures based on the numeracy, health literacy, demographic, and experience-related questions we asked.

DISCUSSION

The 4 immunization visualizations had unique design elements that likely contributed to these performance differences.

CONCLUSION

Based on our findings, we provide practical guidance for the design of immunization visualizations, and future studies. Future research should focus on understanding the contexts of use and design elements that make tables an effective type of health data visualization.

摘要

目的

本研究通过实验评估了非专业人士对 4 种电子健康记录(EHR)患者界面免疫可视化的解释和使用能力。

材料与方法

参与者(n=69)通过安全的在线调查平台完成了研究。参与者查看了 4 种 EHR 免疫可视化中的同一种免疫信息:2 种不同的患者门户(Epic MyChart 和 eClinicWorks)、可下载的 EHR 记录和诊所生成的电子信函(eLetter)。参与者完成了一项共同任务,创建了标准疫苗接种时间表,并回答了关于他们的感知工作量、主观计算能力和健康素养、人口统计学变量以及对任务的熟悉程度的问题。

结果

免疫可视化设计显著影响了任务绩效测量指标(完成任务所需的时间和正确日期的数量)。特别是,使用 Epic MyChart 的人完成任务的时间明显长于使用 eLetter 或 eClinicWorks 的人。使用 Epic MyChart 的人输入的正确日期少于使用 eLetter 或 eClinicWorks 的人。根据我们提出的计算能力、健康素养、人口统计学和经验相关问题,任务绩效指标没有系统的统计学显著差异。

讨论

这 4 种免疫可视化具有独特的设计元素,这可能导致了这些性能差异。

结论

基于我们的发现,我们为免疫可视化的设计和未来的研究提供了实用的指导。未来的研究应侧重于理解使用情况和设计元素,这些元素使表格成为有效的健康数据可视化类型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56bf/11491626/43d352de48dd/ocae125f1.jpg

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