Investigation of a Mobile Health Texting Tool for Embedding Patient-Reported Data Into Diabetes Management (i-Matter): Development and Usability Study

Which diabetes specific patient reported outcomes should be measured in routine care? A systematic review to inform a core outcome set for adults with Type 1 and 2 diabetes mellitus: The European Health Outcomes Observatory (H2O) programme

OBJECTIVES

The objective was to identify candidate patient reported outcomes with potential to inform individual patient care and service development for inclusion in a digital outcome set to be collected in routine care, as part of an international project to enhance care outcomes for people with diabetes.

METHODS

PubMed, COSMIN and COMET databases were searched. Published studies were included if they recommended patient reported outcomes that were clinically useful and/or important to people with diabetes. To aid selection decisions, recommended outcomes were considered in terms of the evidence endorsing them and their importance to people with diabetes.

RESULTS

Twenty-seven studies recommending 53 diabetes specific outcomes, and patient reported outcome measures, were included. The outcomes reflected the experience of living with diabetes (e.g. psychological well-being, symptom experience, health beliefs and stigma) and behaviours (e.g. self-management). Diabetes distress and self-management behaviours were most endorsed by the evidence.

CONCLUSIONS

The review provides a comprehensive list of candidate outcomes endorsed by international evidence and informed by existing outcome sets, and suggestions for measures.

PRACTICE IMPLICATIONS

The review offers evidence to guide clinical application. Integrated measurement of these outcomes in care settings holds enormous potential to improve provision of care and outcomes in diabetes.

Opening the Black Box of an mHealth Patient-Reported Outcome Tool for Diabetes Self-Management: Interview Study Among Patients With Type 2 Diabetes

BACKGROUND

Mobile health (mHealth) tools are used to collect data on patient-reported outcomes (PROs) and facilitate the assessment of patients' self-management behaviors outside the clinic environment. Despite the high availability of mHealth diabetes tools, there is a lack of understanding regarding the underlying reasons why these mHealth PRO tools succeed or fail in terms of changing patients' self-management behaviors.

OBJECTIVE

This study aims to identify the factors that drive engagement with an mHealth PRO tool and facilitate patients' adoption of self-management behaviors, as well as elicit suggestions for improvement.

METHODS

This qualitative study was conducted within the context of a randomized controlled trial designed to evaluate the efficacy of an mHealth PRO tool (known as i-Matter) versus usual care regarding reduction in glycated hemoglobin (HbA1c) levels and adherence to self-management behaviors at 12 months among patients with uncontrolled type 2 diabetes. Patients randomized to i-Matter participated in semistructured interviews about their experiences at the 3-, 6-, 9-, and 12-month study visits. A qualitative analysis of the interviews was conducted by 2 experienced qualitative researchers using conventional qualitative content analysis.

RESULTS

The sample comprised 71 patients, of whom 67 (94%) completed at least one interview (n=48, 72% female patients; n=25, 37% identified as African American or Black; mean age 56.65 [SD 9.79] years). We identified 4 overarching themes and 6 subthemes. Theme 1 showed that the patients' reasons for engagement with i-Matter were multifactorial. Patients were driven by internal motivating factors that bolstered their engagement and helped them feel accountable for their diabetes (subtheme 1) and external motivating factors that helped to serve as reminders to be consistent with their self-management behaviors (subtheme 2). Theme 2 revealed that the use of i-Matter changed patients' attitudes toward their disease and their health behaviors in 2 ways: patients developed more positive attitudes about their condition and their ability to effectively self-manage it (subtheme 3), and they also developed a better awareness of their current behaviors, which motivated them to adopt healthier lifestyle behaviors (subtheme 4). Theme 3 showed that patients felt more committed to their health as a result of using i-Matter. Theme 4 highlighted the limitations of i-Matter, which included its technical design (subtheme 5) and the need for more resources to support the PRO data collected and shared through the tool (subtheme 6).

CONCLUSIONS

This study isolated internal and external factors that prompted patients to change their views about their diabetes, become more engaged with the intervention and their health, and adopt healthy behaviors. These behavioral mechanisms provide important insights to drive future development of mHealth interventions that could lead to sustained behavior change.

Electronic health strategies to improve medication adherence in patients with cardiometabolic disease: current status and future directions

PURPOSE OF REVIEW

Enabled by widespread technological advancements, electronic health (eHealth) strategies have expanded rapidly over the last decade, presenting opportunities to support self-management including medication adherence for cardiometabolic disease control. eHealth can minimize access barriers to medications, enable timely assessment and shared decision-making, and provide medication reminders and health data feedback. This review summarizes current evidence for effectiveness of eHealth strategies for improving medication adherence in patients with hypertension, type 2 diabetes, and/or hyperlipidemia, and identifies priorities for future research.

RECENT FINDINGS

Current research supports the effectiveness of eHealth strategies to improve medication adherence and clinical outcomes for cardiometabolic disease. Although patient acceptability of eHealth strategies is generally high, engagement may decline over time. In addition, differences in effectiveness across intervention characteristics and sociodemographic groups are understudied, limiting generalizability and tailoring of interventions to local health system resources, culture, and patient needs or preferences.

SUMMARY

eHealth is a promising tool for addressing low medication adherence. Further work incorporating rigorous evaluation, assessment of patient engagement over time and effectiveness of intervention characteristics and components, and a health equity lens addressing eHealth use in vulnerable groups will increase understanding of the full potential of eHealth for improving medication adherence in diverse patients with cardiometabolic disease.

From Digital Health to Digital Well-being: Systematic Scoping Review

Background

Digital health refers to the proper use of technology for improving the health and well-being of people and enhancing the care of patients through the intelligent processing of clinical and genetic data. Despite increasing interest in well-being in both health care and technology, there is no clear understanding of what constitutes well-being, which leads to uncertainty in how to create well-being through digital health. In an effort to clarify this uncertainty, Brey developed a framework to define problems in technology for well-being using the following four categories: epistemological problem, scope problem, specification problem, and aggregation problem.

Objective

This systematic scoping review aims to gain insights into how to define and address well-being in digital health.

Methods

We followed the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) checklist. Papers were identified from 6 databases and included if they addressed the design or evaluation of digital health and reported the enhancement of patient well-being as their purpose. These papers were divided into design and evaluation papers. We studied how the 4 problems in technology for well-being are considered per paper.

Results

A total of 117 studies were eligible for analysis (n=46, 39.3% design papers and n=71, 60.7% evaluation papers). For the epistemological problem, the thematic analysis resulted in various definitions of well-being, which were grouped into the following seven values: healthy body, functional me, healthy mind, happy me, social me, self-managing me, and external conditions. Design papers mostly considered well-being as healthy body and self-managing me, whereas evaluation papers considered the values of healthy mind and happy me. Users were rarely involved in defining well-being. For the scope problem, patients with chronic care needs were commonly considered as the main users. Design papers also regularly involved other users, such as caregivers and relatives. These users were often not involved in evaluation papers. For the specification problem, most design and evaluation papers focused on the provision of care support through a digital platform. Design papers used numerous design methods, whereas evaluation papers mostly considered pre-post measurements and randomized controlled trials. For the aggregation problem, value conflicts were rarely described.

Conclusions

Current practice has found pragmatic ways of circumventing or dealing with the problems of digital health for well-being. Major differences exist between the design and evaluation of digital health, particularly regarding their conceptualization of well-being and the types of users studied. In addition, we found that current methodologies for designing and evaluating digital health can be improved. For optimal digital health for well-being, multidisciplinary collaborations that move beyond the common dichotomy of design and evaluation are needed.