Artificial intelligence in diabetes care

Buch, Varun; Varughese, George; Maruthappu, Mahiben

doi:10.1111/dme.13587

Cited by 32 publications

(32 citation statements)

References 7 publications

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“…As these algorithms were found to have limited efficacy and were incorrect [ 50 ], we did not include an insulin calculator in our app. Artificial intelligence may have potential use in this area [ 51 ].…”

Section: Discussionmentioning

confidence: 99%

Exploration of Users’ Perspectives and Needs and Design of a Type 1 Diabetes Management Mobile App: Mixed-Methods Study

Zhang¹,

Li²,

Luo³

et al. 2018

JMIR Mhealth Uhealth

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BackgroundWith the popularity of mobile phones, mobile apps have great potential for the management of diabetes, but the effectiveness of current diabetes apps for type 1 diabetes mellitus (T1DM) is poor. No study has explored the reasons for this deficiency from the users’ perspective.ObjectiveThe aims of this study were to explore the perspectives and needs of T1DM patients and diabetes experts concerning a diabetes app and to design a new T1DM management mobile app.MethodsA mixed-methods design combining quantitative surveys and qualitative interviews was used to explore users’ needs and perspectives. Experts were surveyed at 2 diabetes conferences using paper questionnaires. T1DM patients were surveyed using Sojump (Changsha ran Xing InfoTech Ltd) on a network. We conducted semistructured, in-depth interviews with adult T1DM patients or parents of child patients who had ever used diabetes apps. The interviews were audio-recorded, transcribed, and coded for theme identification.ResultsThe expert response rate was 63.5% (127/200). The respondents thought that the reasons for app invalidity were that patients did not continue using the app (76.4%, 97/127), little guidance was received from health care professionals (HCPs; 73.2%, 93/127), diabetes education knowledge was unsystematic (52.8%, 67/127), and the app functions were incomplete (44.1%, 56/127). A total of 245 T1DM patient questionnaires were collected, of which 21.2% (52/245) of the respondents had used diabetes apps. The reasons for their reluctance to use an app were limited time (39%, 20/52), complicated operations (25%, 13/52), uselessness (25%, 13/52), and cost (25%, 13/52). Both the experts and patients thought that the most important functions of the app were patient-doctor communication and the availability of a diabetes diary. Two themes that were useful for app design were identified from the interviews: (1) problems with patients’ diabetes self-management and (2) problems with current apps. In addition, needs and suggestions for a diabetes app were obtained. Patient-doctor communication, diabetes diary, diabetes education, and peer support were all considered important by the patients, which informed the development of a prototype multifunctional app.ConclusionsPatient-doctor communication is the most important function of a diabetes app. Apps should be integrated with HCPs rather than stand-alone. We advocate that doctors follow up with their patients using a diabetes app. Our user-centered method explored comprehensively and deeply why the effectiveness of current diabetes apps for T1DM was poor and what T1DM patients needed for a diabetes app and provided meaningful guidance for app design.

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Section: Discussionmentioning

confidence: 99%

Exploration of Users’ Perspectives and Needs and Design of a Type 1 Diabetes Management Mobile App: Mixed-Methods Study

Zhang¹,

Li²,

Luo³

et al. 2018

JMIR Mhealth Uhealth

View full text Add to dashboard Cite

show abstract

“…Artificial intelligence (AI) and machine learning are being applied to diabetes management. 59 Medical devices and diagnostics tools are starting to provide blood glucose management tools that improve adherence. Medtronic's Sugar.IQÔ smart diabetes assistant is now available in the Guardian Connect CGM for people using MDIs.…”

Section: Data Management Decision Analysis and Connected Carementioning

confidence: 99%

Emerging Technologies for Diabetes Care

Bailey

Walsh

Stone

2018

Diabetes Technology & Therapeutics

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New therapies, monitoring, and revolutionary enabling technologies applied to healthcare represent an historic opportunity to improve the lives of people with diabetes. These advances enable more meaningful monitoring of blood glucose values with the facilitation of more optimal insulin dosing and delivery. Newer insulins and delivery systems are in development that seek to mitigate both hyperglycemia and hypoglycemia and increase time in range. Information systems now exist that may be leveraged to merge data from previously discrete systems into new models of connected care. This review highlights important developments that serve to increase effectiveness while reducing the burden of diabetes care in the near future.

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“…Finally, due to the impact of AI on the detection and management of diabetes, it should be noted that AI technologies applied in diabetes health care systems can improve the interactions between patients, health care professionals, and the health care system 22–24. The algorithms and computer models used in the AI tools are capable of handling and manipulating a vast number of variables of users and the environment that facilitate interactions between patients and mobile apps, assisting in a more effective way the medical treatment.…”

Section: Introductionmentioning

confidence: 99%

mHealth for diabetes self-management in the Kingdom of Saudi Arabia: barriers and solutions

Alanzi

2018

JMDH

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PurposeIn this paper I present a perspective of mobile health (mHealth) technologies for diabetes in conjunction with an overview of the current status of mHealth technologies for diabetes self-management and the clinical evidence in the Kingdom of Saudi Arabia. In addition, a small survey to identify the barriers to mHealth for diabetes care in the Kingdom and the relevant solutions are discussed.Participants and methodsIn order to study the relevant obstacles for adopting mHealth solutions for diabetes care and to suggest appropriate solutions, a small survey study was conducted with a specific questionnaire deployed to >40 anonymous leading health care professionals and decision-makers of the Kingdom. The survey was distributed by means of a link to the target population through a WhatsApp group. The data were collected during 1 month, and three reminders were sent to the group to complete the survey. Basic descriptive statistics were used to analyze the survey data.ResultsThe high percentages of agreement among the participants suggest that mHealth expertise and human shortage; funding and infrastructure investments; legal, privacy standardization and regulatory obstacles; and health care organizational and bureaucracy impediments are barriers to the implementation of mHealth technologies in the self-management of diabetes in this region. However, most of these barriers can be mitigated by the creation of the appropriate leadership and clinical environment in the current health care system.ConclusionThe mHealth technologies for diabetes self-management have not yet been translated successfully in the Kingdom of Saudi Arabia as it was detected in the literature review carried out in this work. Among other possibilities, the causes of this situation are the existence of human, organizational, funding, bureaucracy, and legal barriers, as shown by the results of the survey conducted among decision-makers and senior clinicians of the Kingdom of Saudi Arabia.

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Artificial intelligence in diabetes care

Cited by 32 publications

References 7 publications

Exploration of Users’ Perspectives and Needs and Design of a Type 1 Diabetes Management Mobile App: Mixed-Methods Study

Exploration of Users’ Perspectives and Needs and Design of a Type 1 Diabetes Management Mobile App: Mixed-Methods Study

Emerging Technologies for Diabetes Care

mHealth for diabetes self-management in the Kingdom of Saudi Arabia: barriers and solutions

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