Centre for Genomics and Child Health, Blizard Institute, Queen Mary University of London, London, UK.
Risk and Information Management, Queen Mary University of London, London, UK.
Diabet Med. 2022 Jan;39(1):e14735. doi: 10.1111/dme.14735. Epub 2021 Nov 16.
Gestational diabetes (GDM) is the most common metabolic disorder of pregnancy, requiring complex management and empowerment of those affected. Mobile health (mHealth) applications (apps) are proposed for streamlining healthcare service delivery, extending care relationships into the community, and empowering those affected by prolonged medical disorders to be equal collaborators in their healthcare. This review investigates mHealth apps intended for use with GDM; specifically those powered by artificial intelligence (AI) or providing decision support.
A scoping review using the novel Survey Tool approach for collaborative literature Reviews (STaR) process was performed.
From 18 papers, 11 discrete GDM-based mHealth apps were identified, but only 3 were reasonably mature with only one currently in use in a clinical setting. Two-thirds of the apps provided condition-relevant contextual user feedback that could aid in patient self care. However, although each app targeted one or more components of the GDM clinical pathway, no app addressed the entirety from diagnosis to postpartum.
There are limited mHealth apps for GDM that incorporate AI or AI-based decision support. Many exist only to record patient information like blood glucose readings or diet, provide generic patient education or advice, or to reduce adverse events by providing medication or appointment alerts. Significant barriers remain that continue to limit the adoption of mHealth apps in clinical care settings. Further research and development are needed to deliver intelligent holistic mHealth apps using AI that can truly reduce healthcare resource use and improve outcomes by enabling patient self care in the community.
妊娠糖尿病（GDM）是最常见的妊娠代谢紊乱，需要对受影响者进行复杂的管理和赋能。移动医疗（mHealth）应用程序（apps）被提议用于简化医疗服务的提供，将护理关系扩展到社区，并赋能那些受长期医疗疾病影响的人，使他们成为医疗保健的平等合作伙伴。本综述调查了用于 GDM 的 mHealth 应用程序；特别是那些由人工智能（AI）驱动或提供决策支持的应用程序。
使用新的协作文献综述调查工具方法（STaR）进行了范围综述。
从 18 篇论文中，确定了 11 个离散的基于 GDM 的 mHealth 应用程序，但只有 3 个具有相当的成熟度，只有 1 个目前在临床环境中使用。三分之二的应用程序提供了与病情相关的情境用户反馈，有助于患者自我护理。然而，尽管每个应用程序都针对 GDM 临床路径的一个或多个部分，但没有一个应用程序涵盖从诊断到产后的所有内容。
用于 GDM 的 mHealth 应用程序有限，其中包含 AI 或基于 AI 的决策支持。许多应用程序仅用于记录患者信息，如血糖读数或饮食，提供通用的患者教育或建议，或通过提供药物或预约提醒来减少不良事件。仍然存在重大障碍，继续限制 mHealth 应用程序在临床护理环境中的采用。需要进一步的研究和开发，以使用 AI 提供智能的整体 mHealth 应用程序，从而通过在社区中实现患者自我护理真正减少医疗保健资源的使用并改善结果。
