Continuing the quality improvement of an electronic personal health record and interactive website for people with diabetes in Scotland (My Diabetes My Way).

AIMS: eHealth applications have the potential to enable patients to take more control over managing their own health, helping to delay and prevent complications. My Diabetes My Way (MDMW) is an electronic personal health record/educational platform available to people with diabetes in Scotland. This study aims to assess user experience with respect to demographic subgroups, examine effectiveness of previous improvements made to the platform and inform its ongoing development. METHODS: All active MDMW users (22,665) were invited to take part in a questionnaire combining Likert scale and free-response items relating to system utility. Likert responses were used to generate a 'utility score'. This was used in regression analyses to determine predictors of system utility scoring. Free-response answers were analysed thematically and themes were generated. RESULTS: A total of 4713 (21%) MDMW users responded to the questionnaire. Most agreed that MDMW helps them to track changes over time, prepare for face-to-face consultations, remember information discussed in consultations and reduced the need to contact their general practitioner. Free-response answers showed that users valued earlier enhancements made to the site (e.g. linking Fitbit data), and highlighted areas needing further improvement. Evidence of the 'digital divide' was seen in respondent demographics, and some users mentioned 'lack of digital skills' as a barrier to engaging with the platform. CONCLUSIONS: User experience of MDMW was positive. Users agreed with statements that MDMW facilitates diabetes self management. Several areas of potential improvement were identified, including linking more wearable device data, and assisting/directing users to gain the digital skills required to engage fully with MDMW.

User-Centered Design of A Novel Risk Prediction Behavior Change Tool Augmented With an Artificial Intelligence Engine (MyDiabetesIQ): A Sociotechnical Systems Approach.

BACKGROUND: Diabetes and its complications account for 10% of annual health care spending in the United Kingdom. Digital health care interventions (DHIs) can provide scalable care, fostering diabetes self-management and reducing the risk of complications. Tailorability (providing personalized interventions) and usability are key to DHI engagement/effectiveness. User-centered design of DHIs (aligning features to end users' needs) can generate more usable interventions, avoiding unintended consequences and improving user engagement. OBJECTIVE: MyDiabetesIQ (MDIQ) is an artificial intelligence engine intended to predict users' diabetes complications risk. It will underpin a user interface in which users will alter lifestyle parameters to see the impact on their future risks. MDIQ will link to an existing DHI, My Diabetes My Way (MDMW). We describe the user-centered design of the user interface of MDIQ as informed by human factors engineering. METHODS: Current users of MDMW were invited to take part in focus groups to gather their insights about users being shown their likelihood of developing diabetes-related complications and any risks they perceived from using MDIQ. Findings from focus groups informed the development of a prototype MDIQ interface, which was then user-tested through the "think aloud" method, in which users speak aloud about their thoughts/impressions while performing prescribed tasks. Focus group and think aloud transcripts were analyzed thematically, using a combination of inductive and deductive analysis. For think aloud data, a sociotechnical model was used as a framework for thematic analysis. RESULTS: Focus group participants (n=8) felt that some users could become anxious when shown their future complications risks. They highlighted the importance of easy navigation, jargon avoidance, and the use of positive/encouraging language. User testing of the prototype site through think aloud sessions (n=7) highlighted several usability issues. Issues included confusing visual cues and confusion over whether user-updated information fed back to health care teams. Some issues could be compounded for users with limited digital skills. Results from the focus groups and think aloud workshops were used in the development of a live MDIQ platform. CONCLUSIONS: Acting on the input of end users at each iterative stage of a digital tool's development can help to prioritize users throughout the design process, ensuring the alignment of DHI features with user needs. The use of the sociotechnical framework encouraged the consideration of interactions between different sociotechnical dimensions in finding solutions to issues, for example, avoiding the exclusion of users with limited digital skills. Based on user feedback, the tool could scaffold good goal setting, allowing users to balance their palatable future complications risk against acceptable lifestyle changes. Optimal control of diabetes relies heavily on self-management. Tools such as MDMW/ MDIQ can offer personalized support for self-management alongside access to users' electronic health records, potentially helping to delay or reduce long-term complications, thereby providing significant reductions in health care costs.

A Longitudinal Perspective on User Uptake of an Electronic Personal Health Record for Diabetes, With Respect To Patient Demographics.

INTRODUCTION: The growing prevalence of diabetes has increased the need for scalable technologies to improve outcomes. My Diabetes My Way (MDMW) is an electronic personal health record (ePHR) available to all people with diabetes in Scotland since 2010, associated with improved clinical outcomes among users. MDMW pulls data from a national clinician-facing informatics platform and provides self-management and educational information. This study aims to describe MDMW user demographics through time with respect to the national diabetes population, with a view to addressing potential health inequalities. METHODS: Aggregate data were obtained retrospectively from the MDMW database and annual Scottish Diabetes Survey (SDS) from 2010 to 2020. Variables included diabetes type, sex, age, socioeconomic status, ethnicity, and glycemic control. Prevalence of MDMW uptake was calculated using corresponding SDS data as denominators. Comparisons between years and demographic sub-groups were made using Chi- Squared tests. RESULTS: Overall uptake of MDMW has steadily increased since implementation. By 2020, of all people with T1D or T2D in Scotland, 13% were fully enrolled to MDMW (39,881/312,326). There was proportionately greater numbers of users in younger, more affluent demographic groups (with a clear social gradient) with better glycemic control. As uptake has increased through time, so too has the observed gaps between different demographic sub-groups. CONCLUSIONS: The large number of MDMW users is encouraging, but remains a minority of people with diabetes in Scotland. There is a risk that innovations like MDMW can widen health inequalities and it is incumbent upon healthcare providers to identify strategies to prevent this.