Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Jul 10, 2018
Open Peer Review Period: Jul 15, 2018 - Sep 9, 2018
Date Accepted: May 10, 2019
(closed for review but you can still tweet)
Customizing of types of technologies used by T1D patients for diabetes treatment: exemplification made by set of case series
ABSTRACT
Background:
Despite the fact there are many wearable and mobile medical devices that enable patients to better self-manage their diabetes, not many patients are aware of all the options they have. In addition, there are those, who are not fully satisfied with the devices they use and, besides that, they often do not use them effectively.
Objective:
Deeper understanding of patients’ needs and abilities can help to both tailor a given device for a particular group of patients and assemble sets and types of devices that best comply with the needs of the patients.
Methods:
6 specific patients (3 men and 3 women), who have been using the Diani telemedicine system for at least 3 months up to 4 years, were properly instructed by a technology educator in how to operate each of the system components. Before starting to use the system and during the monitoring phase, the patients took interviews with a doctor and the educator about their daily regimen, technology capabilities, life preferences and similar topics. The technology educator was also tracking patterns of handling the devices 1) by observation while educating the patients on how to use them, and 2) via the Diani web application during the monitoring phase. Informed consent was signed and obtained from each of the patients included.
Results:
Each of the presented case study describes how a given patient is handling the system and its particular parts based on his/her lifestyle, level of education, manners in diabetes management, personality type and other factors. At the conclusion of each case study, the best composition of devices for patients with similar personal description is suggested.
Conclusions:
Except for the input information we get about a patient, it is obvious that there is a substantial need for proper education of both patients and healthcare providers. We believe this article can provide a relevant guidance on how to help particular patients choose the best technology that is likely to fit them the most, based on specific patient information we are able to obtain from them.
Citation
Per the author's request the PDF is not available.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.