应用创新方法构建卫生系统数字化转型基础设施:发展项目评估。

IF 2 Q3 HEALTH CARE SCIENCES & SERVICES
M Claire Buchan, Tarun Reddy Katapally, Jasmin Bhawra
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引用次数: 0

摘要

背景:我们当前面临的公共卫生危机,包括COVID-19等传染病大流行,需要社会齐心协力,解决卫生系统中的决策差距。合理利用来自公民的大数据的数字卫生平台可以通过实现实时数据收集、通信和快速反应来改变卫生系统。然而,目前缺乏标准化和基于证据的方法来开发和实施数字卫生平台,限制了它们的应用。目的:本研究旨在通过与跨学科研究人员(即关键利益相关者)组成的开发和研究团队合作,在公开发布前应用混合评估方法对快速反应COVID-19数字卫生平台的开发进行评估。方法:采用发展性评估方法,本研究进行了(1)定性调查,评估了数字健康平台的目标、修改和挑战,对软件开发团队的5名关键成员进行了调查;(2)与7名关键利益相关者进行了角色扮演试点,他们模拟了8名现实世界的用户,随后进行了自我报告调查,以评估数字健康平台对每个目标的效用。调查数据采用归纳专题分析方法进行分析。试验后调查数据按参与者角色进行汇总和综合。结果:数字健康平台实现了最初的目标,并进行了扩展,以适应潜在用户不断变化的需求和COVID-19大流行法规。开发团队指出的主要挑战包括导航不断变化的政府政策和支持平台用户的数据主权。强大的团队凝聚力和解决问题的能力在项目开发的整体成功中是必不可少的。在试点测试期间,参与者报告了与该平台互动的积极体验,并发现其功能相对容易使用。社区成员角色的用户认为该平台准确反映了他们感染COVID-19的风险,但报告了与界面交互的一些挑战。那些决策者发现数据可视化有助于理解复杂的信息。两个参与者组都强调了教程对未来用户的实用性。结论:通过对数字健康平台开发过程的评估,我们决定将研究团队与开发团队更紧密地整合在一起,鉴于在健康研究中使用外部技术供应商,这种做法目前并不常见。在短期内,开发评估导致了更短的冲刺,角色扮演练习使登录过程和用户界面能够在公开部署之前得到改进。从长远来看,这一实践决定在两个团队中都加入一名数据科学家,以便在整个开发过程中与研究人员保持联系。通过向计算机程序员提供卫生系统培训,更多的跨学科研究也被纳入了研究过程,这是以人为本的人工智能发展的一个关键因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of an Innovative Methodology to Build Infrastructure for Digital Transformation of Health Systems: Developmental Program Evaluation.

Background: The current public health crises we face, including communicable disease pandemics such as COVID-19, require cohesive societal efforts to address decision-making gaps in our health systems. Digital health platforms that leverage big data ethically from citizens can transform health systems by enabling real-time data collection, communication, and rapid responses. However, the lack of standardized and evidence-based methods to develop and implement digital health platforms currently limits their application.

Objective: This study aims to apply mixed evaluation methods to assess the development of a rapid response COVID-19 digital health platform before public launch by engaging with the development and research team, which consists of interdisciplinary researchers (ie, key stakeholders).

Methods: Using a developmental evaluation approach, this study conducted (1) a qualitative survey assessing digital health platform objectives, modifications, and challenges administered to 5 key members of the software development team and (2) a role-play pilot with 7 key stakeholders who simulated 8 real-world users, followed by a self-report survey, to evaluate the utility of the digital health platform for each of its objectives. Survey data were analyzed using an inductive thematic analysis approach. Postpilot test survey data were aggregated and synthesized by participant role.

Results: The digital health platform met original objectives and was expanded to accommodate the evolving needs of potential users and COVID-19 pandemic regulations. Key challenges noted by the development team included navigating changing government policies and supporting the data sovereignty of platform users. Strong team cohesion and problem-solving were essential in the overall success of program development. During the pilot test, participants reported positive experiences interacting with the platform and found its features relatively easy to use. Users in the community member role felt that the platform accurately reflected their risk of contracting COVID-19, but reported some challenges interacting with the interface. Those in the decision maker role found the data visualizations helpful for understanding complex information. Both participant groups highlighted the utility of a tutorial for future users.

Conclusions: Evaluation of the digital health platform development process informed our decisions to integrate the research team more cohesively with the development team, a practice that is currently uncommon given the use of external technology vendors in health research. In the short term, the developmental evaluation resulted in shorter sprints, and the role-play exercise enabled improvements to the log-in process and user interface ahead of public deployment. In the long term, this exercise informed the decision to include a data scientist as part of both teams going forward to liaise with researchers throughout the development process. More interdisciplinarity was also integrated into the research process by providing health system training to computer programmers, a key factor in human-centered artificial intelligence development.

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来源期刊
JMIR Formative Research
JMIR Formative Research Medicine-Medicine (miscellaneous)
CiteScore
2.70
自引率
9.10%
发文量
579
审稿时长
12 weeks
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