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包括人工智能在内的医疗保健仪表板的排序设计属性:可用性研究。

Rank Ordered Design Attributes for Health Care Dashboards Including Artificial Intelligence: Usability Study.

作者信息

Malkani Melina, Madan Eesha, Malkani Dillon, Madan Arav, Singh Neel, Bamji Tara, Sabharwal Harman

机构信息

Bullis School, Potomac, MD, United States.

George Washington University, Washington DC, DC, United States.

出版信息

Online J Public Health Inform. 2024 Nov 20;16:e58277. doi: 10.2196/58277.

Abstract

BACKGROUND

On average, people in the United States visit a doctor 4 times a year, and many of them have chronic illnesses. Because of the increased use of technology, people frequently rely on the internet to access health information and statistics. People use health care information to make better-educated decisions for themselves and others. Health care dashboards should provide pertinent and easily understood data, such as information on timely cancer screenings, so the public can make better-informed decisions. In order to enhance health outcomes, effective dashboards should provide precise data in an accessible and easily digestible manner.

OBJECTIVE

This study identifies the top 15 attributes of a health care dashboard. The objective of this research is to enhance health care dashboards to benefit the public by making better health care information available for more informed decisions by the public and to improve population-level health care outcomes.

METHODS

The authors conducted a survey of health care dashboards with 218 individuals identifying the best practices to consider when creating a public health care dashboard. The data collection was conducted from June 2023 to August 2023. The analyses performed were descriptive statistics, frequencies, and a comparison to a prior study.

RESULTS

From May 2023 to June 2023, we collected 3259 responses in multiple different states around the United States from 218 people aged 18 years or older. The features ranking in descending order of importance are as follows: (1) easy navigation, (2) historical data, (3) simplicity of design, (4) high usability, (5) use of clear descriptions, (6) consistency of data, (7) use of diverse chart types, (8) compliance with the Americans with Disabilities Act, (9) incorporated user feedback, (10) mobile compatibility, (11) comparison data with other entities, (12) storytelling, (13) predictive analytics with artificial intelligence, (14) adjustable thresholds, and (15) charts with tabulated data.

CONCLUSIONS

Future studies can extend the research to other types of dashboards such as bioinformatics, financial, and managerial dashboards as well as confirm these top 15 best practices for medical dashboards with further evidentiary support. The medical informatics community may benefit from standardization to improve efficiency and effectiveness as dashboards can communicate vital information to patients worldwide on critically prominent issues. Furthermore, health care professionals should use these best practices to help increase population health care outcomes by informing health care consumers to make better decisions with better data.

摘要

背景

美国人平均每年看4次医生,其中许多人患有慢性病。由于技术使用的增加,人们经常依靠互联网获取健康信息和统计数据。人们利用医疗保健信息为自己和他人做出更明智的决策。医疗保健仪表盘应提供相关且易于理解的数据,如及时癌症筛查的信息,以便公众能够做出更明智的决策。为了提高健康结果,有效的仪表盘应以可访问且易于理解的方式提供精确数据。

目的

本研究确定了医疗保健仪表盘的前15个属性。本研究的目的是改进医疗保健仪表盘,通过提供更好的医疗保健信息,使公众能够做出更明智的决策,从而造福公众,并改善人群层面的医疗保健结果。

方法

作者对218名个人进行了医疗保健仪表盘调查,确定创建公共医疗保健仪表盘时应考虑的最佳实践。数据收集于2023年6月至2023年8月进行。所进行的分析包括描述性统计、频率以及与先前研究的比较。

结果

2023年5月至2023年6月,我们在美国多个不同州收集了218名18岁及以上人群的3259份回复。按重要性降序排列的功能如下:(1)易于导航,(2)历史数据,(3)设计简单,(4)高可用性,(5)使用清晰的描述,(6)数据一致性,(7)使用多种图表类型,(8)符合《美国残疾人法案》,(9)纳入用户反馈,(10)移动兼容性,(11)与其他实体的比较数据,(12)叙事,(13)人工智能预测分析,(14)可调整阈值,(15)带有列表数据的图表。

结论

未来的研究可以将该研究扩展到其他类型的仪表盘,如生物信息学、财务和管理仪表盘,并通过进一步的证据支持来确认医疗仪表盘的这前15个最佳实践。医疗信息学社区可能会从标准化中受益,以提高效率和有效性,因为仪表盘可以就关键突出问题向全球患者传达重要信息。此外,医疗保健专业人员应利用这些最佳实践,通过告知医疗保健消费者利用更好的数据做出更好的决策,来帮助提高人群医疗保健结果。

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