Gestational Diabetes Management Using Smart Mobile Telemedicine

Rigla, Mercedes; Martínez-Sarriegui, Iñaki; García-Sáez, Gema; Pons, Belén; Hernando, M. Elena

doi:10.1177/1932296817704442

Cited by 79 publications

(88 citation statements)

References 18 publications

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“…The system, which is based on the application of a natural language processing (NLP) algorithm, was validated during the postpartum visits of 600 GDM patients. Rigla et al also investigated tools for GDM patients [ 133 ]. They proposed a mobile app based on an AI-augmented telemedicine DSS as a tool for helping GDM patients.…”

Section: Resultsmentioning

confidence: 99%

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

Contreras¹,

Vehı́²

2018

J Med Internet Res

363

207

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BackgroundArtificial intelligence methods in combination with the latest technologies, including medical devices, mobile computing, and sensor technologies, have the potential to enable the creation and delivery of better management services to deal with chronic diseases. One of the most lethal and prevalent chronic diseases is diabetes mellitus, which is characterized by dysfunction of glucose homeostasis.ObjectiveThe objective of this paper is to review recent efforts to use artificial intelligence techniques to assist in the management of diabetes, along with the associated challenges.MethodsA review of the literature was conducted using PubMed and related bibliographic resources. Analyses of the literature from 2010 to 2018 yielded 1849 pertinent articles, of which we selected 141 for detailed review.ResultsWe propose a functional taxonomy for diabetes management and artificial intelligence. Additionally, a detailed analysis of each subject category was performed using related key outcomes. This approach revealed that the experiments and studies reviewed yielded encouraging results.ConclusionsWe obtained evidence of an acceleration of research activity aimed at developing artificial intelligence-powered tools for prediction and prevention of complications associated with diabetes. Our results indicate that artificial intelligence methods are being progressively established as suitable for use in clinical daily practice, as well as for the self-management of diabetes. Consequently, these methods provide powerful tools for improving patients’ quality of life.

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Section: Resultsmentioning

confidence: 99%

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

Contreras¹,

Vehı́²

2018

J Med Internet Res

363

207

View full text Add to dashboard Cite

show abstract

“…A previous systematic review concluded that there was insufficient evidence showing that the use of telemedicine technology was superior to the use of the standard care procedure for women with GDM [ 39 ]. Riga et al [ 40 ] reported promising results with regard to the acceptance of mobile phone telemedicine among pregnant women with GDM. However, little is known about the use of mobile phone apps for the management of GDM [ 25 , 41 ].…”

Section: Discussionmentioning

confidence: 99%

Health Care Professionals’ Attitudes Toward, and Experiences of Using, a Culture-Sensitive Smartphone App for Women with Gestational Diabetes Mellitus: Qualitative Study

Garnweidner-Holme¹,

Andersen²,

Sando³

et al. 2018

JMIR Mhealth Uhealth

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BackgroundThe increasing prevalence of gestational diabetes mellitus (GDM) among women of different ethnic backgrounds provides new challenges for health care professionals, who often find it difficult to provide information about the management of this disease to such individuals. Mobile health (mHealth) may act as a useful tool for blood sugar control and care process enhancement. However, little is known about health care professionals’ experiences and attitudes toward the use of mHealth for women with GDM.ObjectiveThe aim of this study was to explore how health care professionals perceived the provision of care to pregnant women who managed their GDM using the culture-sensitive Pregnant+ app in a randomized controlled trial.MethodsIndividual interviews with 9 health care professionals providing care for women with GDM were conducted. Braun and Clark’s method of thematic content analysis inspired the analysis. This study included health care professionals who were primarily responsible for providing care to participants with GDM in the Pregnant+ randomized controlled trial at 5 diabetes outpatient clinics in Oslo, Norway.ResultsHealth care professionals perceived mHealth, particularly the Pregnant+ app, as an appropriate tool for the care of women with GDM, who were described as individuals comprising a heterogeneous, motivated group that could be easily approached with health-related information. Some participants reported challenges with respect to provision of advice to women with different food cultures. The advantages of the Pregnant+ app included provision of information that women could access at home, the information provided being perceived as trustworthy by health care professionals, the culture sensitivity of the app, and the convenience for women to register blood sugar levels. Technical problems, particularly those associated with the automatic transfer of blood glucose measurements, were identified as the main barrier to the use of the Pregnant+ app. Strict inclusion criteria and the inclusion of participants who could not speak Norwegian were the main challenges in the recruitment process for the randomized controlled trial.ConclusionsThe findings of this study suggest that mHealth is a useful tool to enhance the care provided by health care professionals to women with GDM. Future mobile apps for the management of GDM should be developed by a trustworthy source and in cooperation with health care professionals. They should also be culture sensitive and should not exhibit technical problems.

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“…A systematic review concluded that there is currently insufficient evidence that telemedicine technology is superior to standard care for women with GDM [33]. Riga et al found promising results regarding the acceptance of smart mobile telemedicine for pregnant women with GDM [34]. Little is known about the use of smartphone apps for the management of GDM [22,35].…”

Section: Discussion Principal Resultsmentioning

confidence: 99%

Health Care Professionals� Attitudes Toward, and Experiences of Using, a Culture-Sensitive Smartphone App for Women with Gestational Diabetes Mellitus: Qualitative Study (Preprint)

Garnweidner-Holme¹,

Andersen²,

Sando³

et al. 2017

Preprint

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Background: The increase in women with gestational diabetes mellitus (GDM) provides new challenges for health professionals. Health professionals can find it challenging to provide information about the management of GDM to women with different ethnic backgrounds. mHealth may constitute a useful tool for blood sugar control and the care process. However, little is known about health professionals' experiences and attitudes towards the use of mHealth for women with GDM.

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Gestational Diabetes Management Using Smart Mobile Telemedicine

Cited by 79 publications

References 18 publications

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

Artificial Intelligence for Diabetes Management and Decision Support: Literature Review

Health Care Professionals’ Attitudes Toward, and Experiences of Using, a Culture-Sensitive Smartphone App for Women with Gestational Diabetes Mellitus: Qualitative Study

Health Care Professionals� Attitudes Toward, and Experiences of Using, a Culture-Sensitive Smartphone App for Women with Gestational Diabetes Mellitus: Qualitative Study (Preprint)

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