包括人工智能在内的医疗保健仪表盘的排序设计属性:可用性研究。

Melina Malkani, Eesha Madan, Dillon Malkani, Arav Madan, Neel Singh, Tara Bamji, Harman Sabharwal
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引用次数: 0

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疾病。由于技术的使用越来越多,人们经常依靠互联网来获取健康信息和统计数据。人们利用医疗信息为自己和他人做出更明智的决定。医疗保健仪表板应提供相关且易于理解的数据,如及时进行癌症筛查的信息,以便公众做出更明智的决定。为了提高医疗效果,有效的仪表盘应该以易于获取和消化的方式提供精确的数据:本研究确定了医疗保健仪表盘的 15 大属性。本研究的目的是通过提供更好的医疗保健信息,让公众做出更明智的决策,并改善人口层面的医疗保健结果,从而改进医疗保健仪表盘,使公众受益:作者对 218 人进行了医疗保健仪表盘调查,以确定创建公共医疗保健仪表盘时应考虑的最佳做法。数据收集时间为 2023 年 6 月至 2023 年 8 月。进行的分析包括描述性统计、频率以及与之前研究的比较:从 2023 年 5 月到 2023 年 6 月,我们在美国多个不同的州收集了 3259 份回复,这些回复来自 218 名 18 岁或以上的人。按重要程度降序排列的功能如下:(1)易于导航,(2)历史数据,(3)设计简洁,(4)可用性高,(5)使用清晰的描述,(6)数据的一致性,(7)使用不同的图表类型,(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)故事性,(13)人工智能预测分析,(14)可调整的阈值,以及(15)带有表格数据的图表:未来的研究可以将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学仪表盘的 15 大最佳实践。医疗信息学界可能会从标准化中获益,以提高效率和有效性,因为仪表盘可以向全世界的患者传达有关重大问题的重要信息。此外,医疗保健专业人员应利用这些最佳实践,通过向医疗保健消费者提供信息,让他们利用更好的数据做出更好的决策,从而帮助提高人口医疗保健成果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rank Ordered Design Attributes for Health Care Dashboards Including Artificial Intelligence: Usability Study.

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.

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