mHealth Consumer Apps: The Case for User-Centered Design

Background Interest in mobile health (mHealth) applications for self-management of diabetes is growing. In July 2009, we found 60 diabetes applications on iTunes for iPhone; by February 2011 the number had increased by more than 400% to 260. Other mobile platforms reflect a similar trend. Despite the growth, research on both the design and the use of diabetes mHealth applications is scarce. Furthermore, the potential influence of social media on diabetes mHealth applications is largely unexplored. Objective Our objective was to study the salient features of mobile applications for diabetes care, in contrast to clinical guideline recommendations for diabetes self-management. These clinical guidelines are published by health authorities or associations such as the National Institute for Health and Clinical Excellence in the United Kingdom and the American Diabetes Association. Methods We searched online vendor markets (online stores for Apple iPhone, Google Android, BlackBerry, and Nokia Symbian), journal databases, and gray literature related to diabetes mobile applications. We included applications that featured a component for self-monitoring of blood glucose and excluded applications without English-language user interfaces, as well as those intended exclusively for health care professionals. We surveyed the following features: (1) self-monitoring: (1.1) blood glucose, (1.2) weight, (1.3) physical activity, (1.4) diet, (1.5) insulin and medication, and (1.6) blood pressure, (2) education, (3) disease-related alerts and reminders, (4) integration of social media functions, (5) disease-related data export and communication, and (6) synchronization with personal health record (PHR) systems or patient portals. We then contrasted the prevalence of these features with guideline recommendations. Results The search resulted in 973 matches, of which 137 met the selection criteria. The four most prevalent features of the applications available on the online markets (n = 101) were (1) insulin and medication recording, 63 (62%), (2) data export and communication, 61 (60%), (3) diet recording, 47 (47%), and (4) weight management, 43 (43%). From the literature search (n = 26), the most prevalent features were (1) PHR or Web server synchronization, 18 (69%), (2) insulin and medication recording, 17 (65%), (3) diet recording, 17 (65%), and (4) data export and communication, 16 (62%). Interestingly, although clinical guidelines widely refer to the importance of education, this is missing from the top functionalities in both cases. Conclusions While a wide selection of mobile applications seems to be available for people with diabetes, this study shows there are obvious gaps between the evidence-based recommendations and the functionality used in study interventions or found in online markets. Current results confirm personalized education as an underrepresented feature in diabetes mobile applications. We found no studies evaluating social media concepts in diabetes self-management on mobile devices, and its potential remains largely unexplored.

Mobile health tools that enable clinicians and researchers to monitor the type, quantity, and quality of everyday activities of patients and trial participants have long been needed to improve daily care, design more clinically meaningful randomized trials of interventions, and establish cost-effective, evidence-based practices. Inexpensive, unobtrusive wireless sensors, including accelerometers, gyroscopes, and pressure-sensitive textiles, combined with Internet-based communications and machine-learning algorithms trained to recognize upper- and lower-extremity movements, have begun to fulfill this need. Continuous data from ankle triaxial accelerometers, for example, can be transmitted from the home and community via WiFi or a smartphone to a remote data analysis server. Reports can include the walking speed and duration of every bout of ambulation, spatiotemporal symmetries between the legs, and the type, duration, and energy used during exercise. For daily care, this readily accessible flow of real-world information allows clinicians to monitor the amount and quality of exercise for risk factor management and compliance in the practice of skills. Feedback may motivate better self-management as well as serve home-based rehabilitation efforts. Monitoring patients with chronic diseases and after hospitalization or the start of new medications for a decline in daily activity may help detect medical complications before rehospitalization becomes necessary. For clinical trials, repeated laboratory-quality assessments of key activities in the community, rather than by clinic testing, self-report, and ordinal scales, may reduce the cost and burden of travel, improve recruitment and retention, and capture more reliable, valid, and responsive ratio-scaled outcome measures that are not mere surrogates for changes in daily impairment, disability, and functioning.

A systematic literature review, covering publications from 1994 to 2009, was carried out to determine the effects of teleconsultation regarding clinical, behavioral, and care coordination outcomes of diabetes care compared to usual care. Two types of teleconsultation were distinguished: (1) asynchronous teleconsultation for monitoring and delivering feedback via email and cell phone, automated messaging systems, or other equipment without face-to-face contact; and (2) synchronous teleconsultation that involves real-time, face-to-face contact (image and voice) via videoconferencing equipment (television, digital camera, webcam, videophone, etc.) to connect caregivers and one or more patients simultaneously, e.g., for the purpose of education. Electronic databases were searched for relevant publications about asynchronous and synchronous tele-consultation [Medline, Picarta, Psychinfo, ScienceDirect, Telemedicine Information Exchange, Institute for Scientific Information Web of Science, Google Scholar]. Reference lists of identified publications were hand searched. The contribution to diabetes care was examined for clinical outcomes [e.g., hemoglobin A1c (HbA1c), dietary values, blood pressure, quality of life], for behavioral outcomes (patient-caregiver interaction, self-care), and for care coordination outcomes (usability of technology, cost-effectiveness, transparency of guidelines, equity of access to care). Randomized controlled trials with HbA1c as an outcome were pooled using standard meta-analytical methods. Of 2060 publications identified, 90 met inclusion criteria for electronic communication between (groups of) caregivers and patients with type 1 and 2 or gestational diabetes. Studies that evaluated teleconsultation not particularly aimed at diabetes were excluded, as were those that described interventions aimed solely at clinical improvements (e.g., HbA1c or lipid profiles). In 63 of 90 interventions, the interaction had an asynchronous teleconsultation character, in 18 cases interaction was synchronously (videoconferencing), and 9 involved a combination of synchronous with asynchronous interaction. Most of the reported improvements concerned clinical values (n = 49), self-care (n = 46), and satisfaction with technology (n = 43). A minority of studies demonstrated improvements in patient-caregiver interactions (n = 28) and cost reductions (n = 27). Only a few studies reported enhanced quality of life (n = 12), transparency of health care (n = 7), and improved equity in care delivery (n = 4). Asynchronous and synchronous applications appeared to differ in the type of contribution they made to diabetes care compared to usual care: asynchronous applications were more successful in improving clinical values and self-care, whereas synchronous applications led to relatively high usability of technology and cost reduction in terms of lower travel costs for both patients and care providers and reduced unscheduled visits compared to usual care. The combined applications (n = 9) scored best according to quality of life (22.2%). No differences between synchronous and asynchronous teleconsultation could be observed regarding the positive effect of technology on the quality of patient-provider interaction. Both types of applications resulted in intensified contact and increased frequency of transmission of clinical values with respect to usual care. Fifteen of the studies contained HbA1c data that permitted pooling. There was significant statistical heterogeneity among the pooled randomized controlled trials (chi(2) = 96.46, P < 0.001). The pooled reduction in HbA1c was not statically significant (weighted mean difference -0.10; 95% confidence interval -0.39 to 0.18). The included studies suggest that both synchronous and asynchronous teleconsultations for diabetes care are feasible, cost-effective, and reliable. However, it should be noted that many of the included studies showed no significant differences between control (usual care) and intervention groups. This might be due to the diversity and lack of quality in study designs (e.g., inaccurate or incompletely reported sample size calculations). Future research needs quasi-experimental study designs and a holistic approach that focuses on multilevel determinants (clinical, behavioral, and care coordination) to promote self-care and proactive collaborations between health care professionals and patients to manage diabetes care. Also, a participatory design approach is needed in which target users are involved in the development of cost-effective and personalized interventions. Currently, too often technology is developed within the scope of the existing structures of the health care system. Including patients as part of the design team stimulates and enables designers to think differently, unconventionally, or from a new perspective, leading to applications that are better tailored to patients' needs. (c) 2010 Diabetes Technology Society.