A Smart Prevention Management in Gestational Diabetes Mellitus

Abstract

Gestational Diabetes Mellitus (GDM) is a high blood glucose level during pregnancy. Patients have frequent follow-ups throughout pregnancy. The concept of health technology enables the accessibility and efficiency of therapy in terms of time-saving and promotes adherence, especially during Covid-19. The study conducts the predictive of GDM risk using a data classification model, which has high accuracy (more than 90%). The model is used for improving the patient's self-awareness through the color notification feature. In addition, we design the GDM's system, including the electronic health information exchange, to ensure interoperability, improve service accessibility and increase patient participation. Finally, this prototype is evaluated by medical staff using the Technology Acceptance Model. The results are satisfactory and accepted because the data technology and standard are incorporated to deliver high performance. Besides, this system is expected to reduce workload and provide convenience.