西北地区农村公平健康分析解决方案(SHARE-NW)农村公共卫生健康公平仪表板:可用性评估。

IF 2.6 Q2 HEALTH CARE SCIENCES & SERVICES
JMIR Human Factors Pub Date : 2024-06-05 DOI:10.2196/51666
Elizabeth Heitkemper, Scott Hulse, Betty Bekemeier, Melinda Schultz, Greg Whitman, Anne M Turner
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引用次数: 0

摘要

背景:鉴于支持农村公共卫生实践的资源匮乏,美国西北部农村公平健康分析解决方案仪表板(SHAREdash)应运而生,以支持美国西北部的农村县级公共卫生部门获取相关数据,识别并解决辖区内的健康差异问题。为确保开发出有用的仪表盘,应在整个系统开发生命周期的多个阶段进行可用性评估。SHAREdash 通过以用户为中心的设计方法进行了改进,在完成后,对 SHAREdash 的可用性进行评估至关重要:本研究旨在根据系统开发生命周期第 3 阶段的评估目标(效率、满意度和有效性)评估 SHAREdash 的可用性:2022 年 1 月至 4 月,来自华盛顿州、爱达荷州、俄勒冈州和阿拉斯加州农村卫生部门的公共卫生专业人员参加了可用性研究。基于网络的评估包括两项思考--朗读任务和一次半结构化定性访谈。朗读思考任务评估效率和效果,访谈调查满意度和总体可用性。采用定向内容分析法对任务和访谈的逐字记录进行了分析:在 9 名参与者中,所有参与者均为女性,大多数在当地卫生部门工作(7/9,78%)。任务 1 的平均点击次数为 10.1 次(标准差为 1.4 次)(可在 7 次点击内完成),任务 2 的平均点击次数为 11.4 次(标准差为 2.0 次)(可在 9 次点击内完成)。在这两项任务中,大多数参与者无需提示,任务 1 和任务 2 分别有 89% (8 人)和 67% (6 人)的参与者无需提示。就有效性而言,所有参与者都能准确、全面地完成每项任务。总体而言,参与者对仪表盘的满意度很高,每个人都说使用仪表盘可以支持他们的工作,特别是将他们的管辖范围与其他人进行比较。最后,半数参与者表示,分享仪表盘中的图表对他们的工作 "非常有用"。仪表板中唯一被认为存在问题的方面是存在大量缺失数据,这也是现有农村辖区数据的一个限制因素:Think-aloud 任务表明,SHAREdash 允许用户高效地完成任务。总体而言,参与者对该仪表盘非常满意,并提供了他们计划使用该仪表盘支持其工作的多种方法。发现的主要可用性问题是缺乏可用数据,这表明解决当前公共卫生数据缺失和分散问题的重要性,尤其是对农村社区而言。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Solutions in Health Analytics for Rural Equity Across the Northwest (SHARE-NW) Dashboard for Health Equity in Rural Public Health: Usability Evaluation.

Background: Given the dearth of resources to support rural public health practice, the solutions in health analytics for rural equity across the northwest dashboard (SHAREdash) was created to support rural county public health departments in northwestern United States with accessible and relevant data to identify and address health disparities in their jurisdictions. To ensure the development of useful dashboards, assessment of usability should occur at multiple stages throughout the system development life cycle. SHAREdash was refined via user-centered design methods, and upon completion, it is critical to evaluate the usability of SHAREdash.

Objective: This study aims to evaluate the usability of SHAREdash based on the system development lifecycle stage 3 evaluation goals of efficiency, satisfaction, and validity.

Methods: Public health professionals from rural health departments from Washington, Idaho, Oregon, and Alaska were enrolled in the usability study from January to April 2022. The web-based evaluation consisted of 2 think-aloud tasks and a semistructured qualitative interview. Think-aloud tasks assessed efficiency and effectiveness, and the interview investigated satisfaction and overall usability. Verbatim transcripts from the tasks and interviews were analyzed using directed content analysis.

Results: Of the 9 participants, all were female and most worked at a local health department (7/9, 78%). A mean of 10.1 (SD 1.4) clicks for task 1 (could be completed in 7 clicks) and 11.4 (SD 2.0) clicks for task 2 (could be completed in 9 clicks) were recorded. For both tasks, most participants required no prompting-89% (n=8) participants for task 1 and 67% (n=6) participants for task 2, respectively. For effectiveness, all participants were able to complete each task accurately and comprehensively. Overall, the participants were highly satisfied with the dashboard with everyone remarking on the utility of using it to support their work, particularly to compare their jurisdiction to others. Finally, half of the participants stated that the ability to share the graphs from the dashboard would be "extremely useful" for their work. The only aspect of the dashboard cited as problematic is the amount of missing data that was present, which was a constraint of the data available about rural jurisdictions.

Conclusions: Think-aloud tasks showed that the SHAREdash allows users to complete tasks efficiently. Overall, participants reported being very satisfied with the dashboard and provided multiple ways they planned to use it to support their work. The main usability issue identified was the lack of available data indicating the importance of addressing the ongoing issues of missing and fragmented public health data, particularly for rural communities.

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来源期刊
JMIR Human Factors
JMIR Human Factors Medicine-Health Informatics
CiteScore
3.40
自引率
3.70%
发文量
123
审稿时长
12 weeks
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