Arun Sasipriya, Sykes Edward R, Tanbeer Syed
Centre for Applied AI, Sheridan College, Oakville, ON, Canada.
AI Lab, School of Computer Science, University of Guelph, Guelph, ON, Canada.
Digit Health. 2024 Dec 10;10:20552076241300748. doi: 10.1177/20552076241300748. eCollection 2024 Jan-Dec.
This paper introduces , a novel web-based healthcare system designed to enable healthcare professionals to monitor patients remotely with enhanced efficacy. Central to our system is its integration with the Vitaliti™ wearable, equipped with biosensors for real-time vital signs monitoring. distinguishes itself by offering advanced, custom visualizations for interactive engagement with medical data, facilitating rapid clinical decision-making through intuitive access to vital signs and trends. The primary research question we sought to answer was: 'Which design of vital sign visualizations is most effective in improving intuitive and rapid understanding for healthcare practitioners?'
An iterative agile/SCRUM methodology was employed in the design and development of . We describe the architectural design of our web-based application, data visualization techniques, and user interface design. A user interface/user experience (UI/UX) study was conducted to assess the efficacy of our system.
The usability study revealed the system's capacity to translate complex bedside data into accessible, real-world visualizations, promoting efficient pattern recognition and anomaly detection. This is crucial for enhancing clinician performance, regardless of the patient's location. The paper further details a usability study involving healthcare practitioners to ascertain efficacy. The System Usability Scale (SUS) assessment yielded a score of 71.5, indicating high usability. This score is significant, positioning our system above the average usability threshold for healthcare technologies, and suggesting it as a valuable tool for remote patient monitoring.
Our web-based healthcare system and findings from the usability study contribute to the domains of Mobile Health (mHealth) and e-Health by advancing remote monitoring capabilities and offering a promising avenue for healthcare IT to improve patient care and clinician workflow.
本文介绍了一种新型的基于网络的医疗保健系统，旨在使医疗保健专业人员能够更高效地远程监测患者。我们系统的核心是与Vitaliti™可穿戴设备集成，该设备配备了用于实时生命体征监测的生物传感器。该系统通过提供先进的定制可视化功能，实现与医疗数据的交互式参与，通过直观地获取生命体征和趋势，促进快速临床决策。我们试图回答的主要研究问题是：“哪种生命体征可视化设计在提高医疗从业者的直观和快速理解方面最有效？”
在该系统的设计和开发中采用了迭代敏捷/Scrum方法。我们描述了基于网络的应用程序的架构设计、数据可视化技术和用户界面设计。进行了用户界面/用户体验（UI/UX）研究，以评估我们系统的有效性。
可用性研究表明，该系统能够将复杂的床边数据转化为易于理解的现实世界可视化，促进高效的模式识别和异常检测。这对于提高临床医生的表现至关重要，无论患者身在何处。本文进一步详细介绍了一项涉及医疗从业者的可用性研究，以确定其有效性。系统可用性量表（SUS）评估得分为71.5，表明可用性较高。这个分数很重要，表明我们的系统高于医疗技术的平均可用性阈值，并表明它是远程患者监测的宝贵工具。
我们基于网络的医疗保健系统和可用性研究结果通过提高远程监测能力，为移动健康（mHealth）和电子健康领域做出了贡献，并为医疗信息技术改善患者护理和临床医生工作流程提供了一条有前景的途径。
