Patient Input for Design of a Decision Support Smartphone Application for Type 1 Diabetes. (November 2020)

• Record Type: Journal Article
• Authors: Wilson, Leah M.; Tyler, Nichole; Jacobs, Peter G.; Gabo, Virginia; Senf, Brian; Reddy, Ravi; Castle, Jessica R.
• Is Part Of: Journal of diabetes science and technology. Volume 14:Number 6(2020:Nov.)
• Page Start: 1081
• Page End: 1087
• Publication Date: 2020-11
• Subjects: decision support -- multiple daily injections -- type 1 diabetes -- smartphone app -- survey; Diabetes -- Periodicals; Medical technology -- Periodicals; Diabetes Mellitus -- Periodicals; 616.462005
• DOI: 10.1177/1932296819870231
• Languages: English
• ISSNs: 1932-2968

Abstract

Background: Decision support smartphone applications integrated with continuous glucose monitors may improve glycemic control in type 1 diabetes (T1D). We conducted a survey to understand trends and needs of potential users to inform the design of decision support technology. Methods: A 70-question survey was distributed October 2017 through May 2018 to adults aged 18-80 with T1D from a specialty clinic and T1D Exchange online health community (myglu.org ). The survey responses were used to evaluate potential features of a diabetes decision support tool by Likert scale and open responses. Results: There were 1542 responses (mean age 46.1 years [SD 15.2], mean duration of diabetes 26.5 years [SD 15.8]). The majority (84.2%) have never used an app to manage diabetes; however, a large majority (77.8%) expressed interest in using a decision support app. The ability to predict and avoid hypoglycemia was the most important feature identified by a majority of the respondents, with 91% of respondents indicating the highest level of interest in these features. The task that respondents find most difficult was management of glucose during exercise (only 47% of participants were confident in glucose management during exercise). The respondents also highly desired features that help manage glucose during exercise (85% of respondents were interested). The responses identified integration and interoperability with peripheral devices/apps and customization of alerts as important. Responses from participants were generally consistent across stratified categories. Conclusions: These results provide valuable insight into patient needs in decision support applications for management of T1D.