Abstract
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.
Highlights
Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance with the onset or first recognition during pregnancy and resolving post-partum; globally, it is the most common metabolic disorder of pregnancy, occurring in 2%–25% of pregnancies.[1]
machine learning (ML) is a type of artificial intelligence (AI) and in the Computer Science (CS) domain would normally be encompassed in that term, we sought ML separately as we found some authors in the medical domain will describe ML solutions without reference to AI
You should increase your insulin by 2 units per meal
Summary
Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance with the onset or first recognition during pregnancy and resolving post-partum; globally, it is the most common metabolic disorder of pregnancy, occurring in 2%–25% of pregnancies.[1]. Smartphone applications (apps) are one technological approach increasingly promoted to support patient self management and enhance communication between clinicians and women with GDM in community and secondary care settings. Current apps for the management of GDM are largely restricted to blood glucose monitoring and the use of blood glucose data to influence lifestyle and pharmacological treatment decisions.[11,12] AI or AI-enabled clinical decision support in addition to diagnostic blood glucose, lifestyle and medication advice can be used to use the wealth of other data collected electronically that impact the holistic care including, for instance, correctly identifying women with GDM, streamlining community to secondary care management, monitoring fetal growth and well-b eing, delivery decisions and timing, neonatal care and post-natal care/decisions.
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