An expert Personal Health System to monitor patients affected by Gestational Diabetes Mellitus: A feasibility study

Abstract

Purpose: Gestational Diabetes Mellitus (GDM) is a condition affecting 3-4% of pregnant women due to increased resistance to insulin caused by the growth of the fetus. Such a condition disappears just after delivery, but it is an indicator of the insurgence of diabetes type 2 (DT2) later in life: about 40% of the women affected by GDM also develop DT2 [22]. GDM brings several complications during pregnancy to both the mother and the fetus. We aim here at presenting our Personal Health System for monitoring GDM and we also present the results of outpatient monitoring and management by utilizing a personal health system (PHS) for GDM. Methods: The Personal Health System (PHS) was deployed in a feasibility study, modelled as a single-center, parallel group, open randomized controlled trial conducted in Lausanne University Hospital. Patients (n=24) were assigned to 2 different groups: standard protocol group (SP) and telemedicine group (TM). SP patients were managed by regular clinic visits. TM patients were managed with our EPHS system. The targeted feasibility outcome was whole trial feasibility, functioning of the PHS and its appropriateness for patient use. Results: Mean age was 32±5 years and patients were pregnant for 29.1±1.9 weeks at study inclusion. Patients came from 16 different countries. The follow-up rate was 100%. Acceptability in the TM-group was high, as 100% were satisfied with the care provided and equally 100% were at ease with the technology. Overall median[IQR] glucose control was 5.4 mmol/l [4.7-6.4] in the TM-group and 5.7mmol/l [4.9-6.7] in the SP-group (p<0.001). Four out of 6 daily plasma glucose values were significantly better controlled with telemedicine compared to standard care. Conclusion: The feasibility study that we conducted shows that PHSs have a great potential to improve the life of the patient by allowing a better communication of their physiological values to the caregivers. With respect to the particular case of GDM, the study suggests that use of PHS technology may improve glycaemic control in GDM, but to confirm this trend, a main trial is needed.

Assessment of Psychological Dimensions in Telemedicine Care for Gestational Diabetes Mellitus: A Systematic Review of Qualitative and Quantitative Studies

“…Another medical and technical evaluation of a telemedicine system for women with GDM was presented by Bromuri et al (2016). Its results indicated that the telemedicine group recorded more blood values than did the standard protocol group ( p < 0.001).…”

Automatic classification of glycaemia measurements to enhance data interpretation in an expert system for gestational diabetes

“…To solve this problem, the expert system can preselect a meal tag for each measurement downloaded and allow patients to modify it. Bromuri et al, preselect glycaemia meal tags based on previous measurements, so, if the last measurement was taken before dinner, an after dinner period is preselected (Bromuri, Puricel, & Schumann, 2016). However, this method might present problems when dealing with repeated or missing measurements, for example if the patient forgets to measure her glycaemia after dinner, she measures it the following day before breakfast and she, by mistake, accepts the preselected meal tag.…”

Propuesta y evaluación de un sistema de telemedicina y de ayuda a la decisión para el cuidado de pacientes con diabetes gestacional

“…El uso de las TICs permite a las pacientes enviar sus datos de monitorización con mayor frecuencia, proporcionando de manera instantánea información precisa y actualizada de su estado de salud (Bromuri et al, 2016). Este aumento en la disponibilidad de los datos, tanto en frecuencia como en cantidad, reduce la incertidumbre en las decisiones médicas al contar con más información, y podría contribuir a mejorar los tiempos de respuesta del personal clínico propiciando diagnósticos y tratamientos más rápidos al reducir el tiempo que transcurre desde que se dan criterios de actuación hasta que se ejecuta la actividad requerida.…”

“…La visualización suele imitar las cartillas de papel de las pacientes y suelen permitir la introducción de otros datos de monitorización como por ejemplo la dosis de insulina, o incluso solicitar tiras reactivas al equipo médico. Las más novedosas ya empiezan a incorporar herramientas de ayuda a la decisión (García-Sáez, Rigla, Martínez-Sarriegui, et al, 2014;Bromuri et al, 2016;Mackillop et al, 2016). Detallaremos este tipo de soluciones para DMG en el apartado 2.5.2.…”

“…El PHS es uno de los sistema de ayuda a la decisión para DMG basado en reglas lógicas, diseñado con el objetivo de presentar al equipo médico los eventos de interés de las pacientes (hipoglucemias e hiperglucemias) para optimizar el tiempo de evaluación clínica (Bromuri et al, 2016). Este sistema ha sido desarrollado en paralelo al trabajo de investigación aquí presentado.…”