Interactive diary for diabetes: A useful and easy-to-use new telemedicine system to support the decision-making process in type 1 diabetes

Accuracy and Feasibility of Using a Smartphone Application for Carbohydrate Counting Versus Traditional Carbohydrate Counting for Adults With Insulin-Treated Diabetes

BACKGROUND

Patients with insulin-treated diabetes struggle with performing accurate carbohydrate counting for proper blood glucose control. Little is known about the comparative accuracy and feasibility of carbohydrate counting methods.

PURPOSE

The purpose of this study was to determine whether carbohydrate counting using a smartphone application is more accurate and feasible than a traditional method.

THEORETICAL/CONCEPTUAL FRAMEWORK

Based on a conceptual model derived from the Technology Acceptance Model, feasibility was defined as usefulness, ease of use, and behavioral intention to use each method.

METHODS

A standardized meal was presented to 20 adults with insulin-treated diabetes who counted carbohydrates using traditional and smartphone methods. Accuracy was measured by comparing carbohydrate counting estimates with the standardized meal values. Perceived feasibility (usefulness, ease of use, behavioral intention) was measured using rating forms derived from the Technology Acceptance Model.

RESULTS

The number of training and estimation minutes were significantly higher for the traditional method than the smartphone method (Z = -3.83, P < .05; Z = -2.30, P < .05). The traditional method took an additional 1.4 minutes for estimation and 12.5 minutes for training. There were no significant differences in accuracy between traditional and smartphone methods for carbohydrate counting (Wilcoxon signed-rank test, Z = -1.10, P = .28). There were no significant differences between traditional and smartphone methods for feasibility (usefulness, Z = -.10, P = .95; ease of use, Z = -.36, P = .72; or behavioral intention, Z = -.94, P = .35).

CONCLUSION

While both traditional and smartphone methods were found to be similar in terms of accuracy and feasibility, the smartphone method took less time for training and for carbohydrate estimation.

Clinical impact of an integrated e-health system for diabetes self-management support and shared decision making (POWER2DM): a randomised controlled trial

AIMS/HYPOTHESIS

There is a lack of e-health systems that integrate the complex variety of aspects relevant for diabetes self-management. We developed and field-tested an e-health system (POWER2DM) that integrates medical, psychological and behavioural aspects and connected wearables to support patients and healthcare professionals in shared decision making and diabetes self-management.

METHODS

Participants with type 1 or type 2 diabetes (aged >18 years) from hospital outpatient diabetes clinics in the Netherlands and Spain were randomised using randomisation software to POWER2DM or usual care for 37 weeks. This RCT assessed the change in HbA1c between the POWER2DM and usual care groups at the end of the study (37 weeks) as a primary outcome measure. Participants and clinicians were not blinded to the intervention. Changes in quality of life (QoL) (WHO-5 Well-Being Index [WHO-5]), diabetes self-management (Diabetes Self-Management Questionnaire - Revised [DSMQ-R]), glycaemic profiles from continuous glucose monitoring devices, awareness of hypoglycaemia (Clarke hypoglycaemia unawareness instrument), incidence of hypoglycaemic episodes and technology acceptance were secondary outcome measures. Additionally, sub-analyses were performed for participants with type 1 and type 2 diabetes separately.

RESULTS

A total of 226 participants participated in the trial (108 with type 1 diabetes; 118 with type 2 diabetes). In the POWER2DM group (n=111), HbA1c decreased from 60.6±14.7 mmol/mol (7.7±1.3%) to 56.7±12.1 mmol/mol (7.3±1.1%) (means ± SD, p<0.001), compared with no change in the usual care group (n=115) (baseline: 61.7±13.7 mmol/mol, 7.8±1.3%; end of study: 61.0±12.4 mmol/mol, 7.7±1.1%; p=0.19) (between-group difference 0.24%, p=0.008). In the sub-analyses in the POWER2DM group, HbA1c in participants with type 2 diabetes decreased from 62.3±17.3 mmol/mol (7.9±1.6%) to 54.3±11.1 mmol/mol (7.1±1.0%) (p<0.001) compared with no change in HbA1c in participants with type 1 diabetes (baseline: 58.8±11.2 mmol/mol [7.5±1.0%]; end of study: 59.2±12.7 mmol/mol [7.6±1.2%]; p=0.84). There was an increase in the time during which interstitial glucose levels were between 3.0 and 3.9 mmol/l in the POWER2DM group, but no increase in clinically relevant hypoglycaemia (interstitial glucose level below 3.0 mmol/l). QoL improved in participants with type 1 diabetes in the POWER2DM group compared with the usual care group (baseline: 15.7±3.8; end of study: 16.3±3.5; p=0.047 for between-group difference). Diabetes self-management improved in both participants with type 1 diabetes (from 7.3±1.2 to 7.7±1.2; p=0.002) and those with type 2 diabetes (from 6.5±1.3 to 6.7±1.3; p=0.003) within the POWER2DM group. The POWER2DM integrated e-health support was well accepted in daily life and no important adverse (or unexpected) effects or side effects were observed.

CONCLUSIONS/INTERPRETATION

POWER2DM improves HbA1c levels compared with usual care in those with type 2 diabetes, improves QoL in those with type 1 diabetes, improves diabetes self-management in those with type 1 and type 2 diabetes, and is well accepted in daily life.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03588104.

FUNDING

This study was funded by the European Union's Horizon 2020 Research and Innovation Programme (grant agreement number 689444).

Food Diary Completion Does Not Significantly Impact Glycemic Control in an Observational Single-Institution Pilot Study of Patients with Type 2 Diabetes Mellitus

INTRODUCTION

Hemoglobin A1c is frequently used to monitor glycemic control in patients with type 2 diabetes mellitus (T2DM). There is an association between dietary habits and hemoglobin A1c. Food diaries are often used to assist in dietary management and have been associated with modification of dietary habits. We aimed to investigate the impact of completing a seven-day food diary on hemoglobin A1c in subjects with T2DM. We hypothesized that patients who completed a food diary might independently modify their dietary habits, resulting in a clinically significant change in hemoglobin A1c.

METHODS

Forty-five subjects with T2DM who completed a seven-day food diary were included in this observational study. Subjects had a mean hemoglobin A1c at baseline of 7.56 ± 1.43 and a body mass index of 33.6 ± 7.6 kg/m². A majority were female (57.8%) and insulin-dependent (71.1%). The primary outcome of interest was a clinically significant change in hemoglobin A1c (≥0.5%). Outcomes were assessed before and within six months after the food diary completion. Chi-square, independent-sample t-tests, and logistic regression were used to analyze the data.

RESULTS

Twelve patients demonstrated a clinically significant decrease in hemoglobin A1c; however, this was not statistically significant regardless of gender (p = 0.5), baseline body mass index (p = 0.5), insulin use (p = 0.3), or community needs index (p = 0.7).

CONCLUSIONS

Although some patients had clinically significant improvements in their hemoglobin A1c, our findings suggest that the use of food diaries alone without goal-directed initiatives is insufficient to achieve differences in hemoglobin A1c in patients with T2DM and an average A1c within the range of 6%-8%.

Significance of Educational Literature and Diabetes Log Sheet on Hemoglobin A1c

Diabetes mellitus (DM) is a major cause of morbidity worldwide. The prevalence of DM has doubled over the last 35 years and is escalating. Various complications and manifestations of diabetes have caused numerous deaths worldwide, with numbers increasing every year. There have been many advances and breakthroughs over the past decade in the management of DM. The major focus of many research studies has been to evaluate effective medication combinations, preventative measures, and the way to control such morbid conditions. Our focus in this review is to discuss specific secondary prevention techniques with the diabetes log sheet and educational literature on its effectiveness in controlling diabetes. Hemoglobin A1c (HbA1c) has been accepted as a diabetes control measure in many resources worldwide. Here, we have assessed articles on the effectiveness of the diabetes log sheet and educational literature on HbA1c levels. We will begin with a few key points to acknowledge diabetes initially, followed by discussing the effectiveness of the diabetes log sheet and literature on HbA1c.

Effectiveness of Disease-Specific mHealth Apps in Patients With Diabetes Mellitus: Scoping Review

Background

According to the World Health Organization, the worldwide prevalence of diabetes mellitus (DM) is increasing dramatically and DM comprises a large part of the global burden of disease. At the same time, the ongoing digitalization that is occurring in society today offers novel possibilities to deal with this challenge, such as the creation of mobile health (mHealth) apps. However, while a great variety of DM-specific mHealth apps exist, the evidence in terms of their clinical effectiveness is still limited.

Objective

The objective of this review was to evaluate the clinical effectiveness of mHealth apps in DM management by analyzing health-related outcomes in patients diagnosed with type 1 DM (T1DM), type 2 DM (T2DM), and gestational DM.

Methods

A scoping review was performed. A systematic literature search was conducted in MEDLINE (PubMed), Cochrane Library, EMBASE, CINAHL, and Web of Science Core Collection databases for studies published between January 2008 and October 2020. The studies were categorized by outcomes and type of DM. In addition, we carried out a meta-analysis to determine the impact of DM-specific mHealth apps on the management of glycated hemoglobin (HbA_1c).

Results

In total, 27 studies comprising 2887 patients were included. We analyzed 19 randomized controlled trials, 1 randomized crossover trial, 1 exploratory study, 1 observational study, and 5 pre-post design studies. Overall, there was a clear improvement in HbA_1c values in patients diagnosed with T1DM and T2DM. In addition, positive tendencies toward improved self-care and self-efficacy as a result of mHealth app use were found. The meta-analysis revealed an effect size, compared with usual care, of a mean difference of –0.54% (95% CI –0.8 to –0.28) for T2DM and –0.63% (95% CI –0.93 to –0.32) for T1DM.

Conclusions

DM-specific mHealth apps improved the glycemic control by significantly reducing HbA_1c values in patients with T1DM and T2DM patients. In general, mHealth apps effectively enhanced DM management. However, further research in terms of clinical effectiveness needs to be done in greater detail.

Effects of mobile health interventions on improving glycemic stability and quality of life in patients with type 1 diabetes: A meta-analysis

This meta-analysis aimed to examine the effects of mobile-health-based (mHealth) interventions on improving glycemic stability and quality of life (QOL) in patients with type 1 diabetes (T1D). Various databases, including PubMed, Embase, CINAHL, Cochrane Library, ProQuest, Chinese Electronic Periodical Services, and China Knowledge Resource Integrated, were used to search for relevant articles. A fixed-effects model or random-effects model was used to examine the overall effect. Various methods, including Egger's test, Begg's test, and trim-and-fill, were adopted to examine publication bias. In total, 26 studies were recruited. Results of the random-effects model showed that the use of mHealth-based interventions significantly decreased glycated hemoglobin (HbA1c) (mean difference = -0.37, 95% confidence interval (CI) = -0.53 to -0.22, p < .001), and improved life satisfaction (Hedges' g = 0.30, 95% CI = 0.10 to 0.50, p = .003), worry of diabetes (Hedges' g = -0.25, 95% CI = -0.41 to 0.08, p = .004), and mental health (Hedges' g = 0.36, 95% CI = 0.08 to 0.64, p = .012). Both adults and youths with T1D can benefit from mHealth-based interventions to improve HbA1c (Hedges' g = -0.44, p = .002 vs. -0.30, p = .003). The effect of mHealth-based interventions on improving QOL in both adults and youths could not be examined due to only one study published in adults with T1D. Moreover, those studies that included the function of feedback from professionals showed a significant effect of decreasing HbA1c compared to those without that function (Hedges' g = -0.48 vs. -0.16, p = .019). Mobile devices are convenient, instantaneous, and easy to use to communicate. Applying mHealth-based interventions with the function of feedback from professionals can be considered an alternative healthcare service to achieve optimal glycemic stability in adults and youths with T1D.

The use of mobile technology to facilitate self-management in adults with type 1 diabetes: A qualitative explorative approach

AIMS

(a) To explore how mobile technology can support self-management in adults with type 1 diabetes (T1DM). (b) To inform a usability study in the design of a mobile application to facilitate self-management of T1DM.

DESIGN

Qualitative exploratory design.

METHODS

Semi-structured interviews were undertaken with adults with T1DM (N = 8). The data collected were analysed using a thematic analysis approach.

RESULTS

Mobile technology has the potential to support adults in their self-management of T1DM through facilitating their decision-making, saving time and enabling them to easily share their data with their healthcare professional. Participants identified four main visualization characteristics for technology to aid in decision-making; relationships between inputs, trends, graphs and colours, and identified essential features such as ease of use, convenience and connectivity.

Text Messaging and Type 1 Diabetes Management: Qualitative Study Exploring Interactions Among Patients and Health Care Professionals

BACKGROUND

The diffusion of information and communication technologies (ICTs) in type 1 diabetes (T1D) management has generated a debate on the ways in which ICTs can support the patient-provider relationship. Several studies have focused on text messages. Most of the literature proposes quantitative analysis of the impact of text messaging on the clinical conditions of patients and/or their satisfaction with the technology, while the qualitative studies have focused mainly on patients' perceptions about strengths and weaknesses of this technology.

OBJECTIVE

In contrast to past studies, we adopted a qualitative approach for the in-depth examination of patient-health care professionals' interactions in text messaging.

METHODS

The study focused on the use of the Trento Cartella Clinica del Cittadino Diabetes System (TreC-DS), a digital platform with a built-in messaging system, in two diabetes centers, integrating message analysis with interviews with patients and health care professionals. Each center focused on a specific patient profile: the first one focused on pregnant women with T1D and the second one focused on adult patients with poorly controlled diabetes.

RESULTS

The main results of the study were as follows: (1) Health care professionals and patients perceived the messaging system as useful for sharing information (ie, pregnant women for prescriptions and adults with poorly controlled diabetes for advice); (2) The content and communication styles of the two centers differed: in the case of pregnant women, interactions via text messaging were markedly prescriptive, while in the case of adult patients with poorly controlled diabetes, they were conceived as open dialogues; and (3) Conversations were initiated mainly by professionals; in the cases considered, it was mainly the diabetes center that decided whether a messaging conversation was needed.

CONCLUSIONS

The results show how the features of interactions of text messaging changed based on the patient profiles in two different centers. In addition, in both diabetes centers that were involved, the system seems to have laid a foundation for a closer relationship between patients and health care professionals.

Exploring app features with outcomes in mHealth studies involving chronic respiratory diseases, diabetes, and hypertension: a targeted exploration of the literature

Objectives

Limited data are available on the correlation of mHealth features and statistically significant outcomes. We sought to identify and analyze: types and categories of features; frequency and number of features; and relationship of statistically significant outcomes by type, frequency, and number of features.

Materials and Methods

This search included primary articles focused on app-based interventions in managing chronic respiratory diseases, diabetes, and hypertension. The initial search yielded 3622 studies with 70 studies meeting the inclusion criteria. We used thematic analysis to identify 9 features within the studies.

Results

Employing existing terminology, we classified the 9 features as passive or interactive. Passive features included: 1) one-way communication; 2) mobile diary; 3) Bluetooth technology; and 4) reminders. Interactive features included: 1) interactive prompts; 2) upload of biometric measurements; 3) action treatment plan/personalized health goals; 4) 2-way communication; and 5) clinical decision support system.

Discussion

Each feature was included in only one-third of the studies with a mean of 2.6 mHealth features per study. Studies with statistically significant outcomes used a higher combination of passive and interactive features (69%). In contrast, studies without statistically significant outcomes exclusively used a higher frequency of passive features (46%). Inclusion of behavior change features (ie, plan/goals and mobile diary) were correlated with a higher incident of statistically significant outcomes (100%, 77%).

Conclusion

This exploration is the first step in identifying how types and categories of features impact outcomes. While the findings are inconclusive due to lack of homogeneity, this provides a foundation for future feature analysis.

Considerations for the Development of Mobile Phone Apps to Support Diabetes Self-Management: Systematic Review

Background

There is increased research interest in the use of mobile phone apps to support diabetes management. However, there are divergent views on what constitute the minimum standards for inclusion in the development of mobile phone apps. Mobile phone apps require an evidence-based approach to development which will consequently impact on their effectiveness. Therefore, comprehensive information on developmental considerations could help designers and researchers to develop innovative and effective patient-centered self-management mobile phone apps for diabetes patients.

Objective

This systematic review examined the developmental considerations adopted in trials that engaged mobile phone applications for diabetes self-management.

Methods

A comprehensive search strategy was implemented across 5 electronic databases; Medline, Scopus, Social Science Citation Index, the Cochrane Central Register of Controlled Trials and Cumulative Index of Nursing and Allied Health Literature (CINALHL) and supplemented by reference list from identified studies. Study quality was evaluated using the Joanna Briggs Critical appraisal checklist for trials. Information on developmental factors (health behavioral theory, functionality, pilot testing, user and clinical expert involvements, data privacy and app security) were assessed across experimental studies using a template developed for the review.

Results

A total of 11 studies (10 randomized controlled trials and 1 quasi-experimental trial) that fitted the inclusion criteria were identified. All the included studies had the functionality of self-monitoring of blood glucose. However, only some of them included functions for data analytics (7/11, 63.6%), education (6/11, 54.5%) and reminder (6/11, 54.5%). There were 5/11(45.5%) studies with significantly improved glycosylated hemoglobin in the intervention groups where educational functionality was present in the apps used in the 5 trials. Only 1 (1/11, 9.1%) study considered health behavioral theory and user involvement, while 2 (2/11, 18.1%) other studies reported the involvement of clinical experts in the development of their apps. There were 4 (4/11, 36.4%) studies which referred to data security and privacy considerations during their app development while 7 (7/12, 63.6%) studies provided information on pilot testing of apps before use in the full trial. Overall, none of the studies provided information on all developmental factors assessed in the review.

Conclusions

There is a lack of elaborate and detailed information in the literature regarding the factors considered in the development of apps used as interventions for diabetes self-management. Documentation and inclusion of such vital information will foster a transparent and shared decision-making process that will ultimately lead to the development of practical and user-friendly self-management apps that can enhance the quality of life for diabetes patients.

Improving Glycemic Control in Adults and Children With Type 1 Diabetes With the Use of Smartphone-Based Mobile Applications: A Systematic Review

OBJECTIVES

Management of type 1 diabetes is often challenging. Smartphone mobile applications (apps) may provide additional support and help to improve glycemic control and clinical outcomes. The objectives of this study were to examine the literature evaluating the use of mobile apps (stand-alone and text messaging/feedback) in type 1 diabetes and to review top-rated mobile apps applicable to type 1 diabetes.

METHODS

Medline, Cochrane and Embase databases were systematically searched to identify studies published from inception to February 2018. Top-rated relevant apps from Google Play Store and Apple App Store were reviewed in July 2017.

RESULTS

The literature search yielded 3,462 studies. Of these studies, 9 evaluated the stand-alone apps; 3 showed significant improvement in glycated hemoglobin (A1C) levels (0.5%, p<0.05, 0.57%, p<0.05, and 0.58%, p=0.02); 3 demonstrated improved adherence to glucose monitoring; and 1 study demonstrated a reduction in hypoglycemic events (glucose<3.0 mmol/L) in 6 of 10 participants who completed the study. Also, 5 studies evaluated a mobile app plus text-messaging/feedback system. Only 1 showed a significant reduction in severe hypoglycemic events (mobile app+text, IQR 0.33, 95% CI 0.17 to 0.63; vs. control, IQR 2.29, 95% CI 1.80 to 2.91), while another single study demonstrated a reduction in median glycated hemoglobin levels (0.3%; p<0.001). Most top-rated mobile apps logged parameters relevant to diabetes management, and some provided graphic analysis and set reminders.

CONCLUSIONS

This study highlights the need for larger and longer studies to explore the efficacy of apps to optimize outcomes in type 1 diabetes, the populations that would benefit most from these tools and the resources needed to support mobile apps plus text-messaging/feedback systems.

mHealth Application Areas and Technology Combinations*. A Comparison of Literature from High and Low/Middle Income Countries

BACKGROUND

With the continuous and enormous spread of mobile technologies, mHealth has evolved as a new subfield of eHealth. While eHealth is broadly focused on information and communication technologies, mHealth seeks to explore more into mobile devices and wireless communication. Since mobile phone penetration has exceeded other infrastructure in low and middle-income countries (LMICs), mHealth is seen as a promising component to provide pervasive and patient-centered care.

OBJECTIVES

The aim of our research work for this paper is to examine the mHealth literature to identify application areas, target diseases, and mHealth service and technology types that are most appropriate for LMICs.

METHODS

Based on the 2011 WHO mHealth report, a combination of search terms, all including the word "mHealth", was identified. A literature review was conducted by searching the PubMed and IEEE Xplore databases. Articles were included if they were published in English, covered an mHealth solution/ intervention, involved the use of a mobile communication device, and included a pilot evaluation study. Articles were excluded if they did not provide sufficient detail on the solution covered or did not focus on clinical efficacy/effectiveness. Cross-referencing was also performed on included articles.

RESULTS

842 articles were retrieved and analyzed, 255 of which met the inclusion criteria. North America had the highest number of applications (n=74) followed by Europe (n=50), Asia (n=44), Africa (n=25), and Australia (n=9). The Middle East (n=5) and South America (n=3) had the least number of studies. The majority of solutions addressed diabetes (n=51), obesity (n=25), CVDs (n=24), HIV (n=18), mental health (n=16), health behaviors (n=16), and maternal and child's health (MCH) (n=11). Fewer solutions addressed asthma (n=7), cancer (n=5), family health planning (n=5), TB (n=3), malaria (n=2), chronic obtrusive pulmonary disease (COPD) (n=2), vision care (n=2), and dermatology (n=2). Other solutions targeted stroke, dental health, hepatitis vaccination, cold and flu, ED prescribed antibiotics, iodine deficiency, and liver transplantation (n=1 each). The remainder of solutions (n=14) did not focus on a certain disease. Most applications fell in the areas of health monitoring and surveillance (n=93) and health promotion and raising awareness (n=88). Fewer solutions addressed the areas of communication and reporting (n=11), data collection (n=6), telemedicine (n=5), emergency medical care (n=3), point of care support (n=2), and decision support (n=2). The majority of solutions used SMS messaging (n=94) or mobile apps (n=71). Fewer used IVR/phone calls (n=8), mobile website/email (n=5), videoconferencing (n=2), MMS (n=2), or video (n=1) or voice messages (n=1). Studies were mostly RCTs, with the majority suffering from small sample sizes and short study durations. Problems addressed by solutions included travel distance for reporting, self-management and disease monitoring, and treatment/medication adherence.

CONCLUSIONS

SMS and app solutions are the most common forms of mHealth applications. SMS solutions are prevalent in both high and LMICs while app solutions are mostly used in high income countries. Common application areas include health promotion and raising awareness using SMS and health monitoring and surveillance using mobile apps. Remaining application areas are rarely addressed. Diabetes is the most commonly targeted medical condition, yet remains deficient in LMICs.

A Systematic Review of Application and Effectiveness of mHealth Interventions for Obesity and Diabetes Treatment and Self-Management

The use of mobile and wireless technologies and wearable devices for improving health care processes and outcomes (mHealth) is promising for health promotion among patients with chronic diseases such as obesity and diabetes. This study comprehensively examined published mHealth intervention studies for obesity and diabetes treatment and management to assess their effectiveness and provide recommendations for future research. We systematically searched PubMed for mHealth-related studies on diabetes and obesity treatment and management published during 2000-2016. Relevant information was extracted and analyzed. Twenty-four studies met inclusion criteria and varied in terms of sample size, ethnicity, gender, and age of the participating patients and length of follow-up. The mHealth interventions were categorized into 3 types: mobile phone text messaging, wearable or portable monitoring devices, and applications running on smartphones. Primary outcomes included weight loss (an average loss ranging from -1.97 kg in 16 wk to -7.1 kg in 5 wk) or maintenance and blood glucose reduction (an average decrease of glycated hemoglobin ranging from -0.4% in 10 mo to -1.9% in 12 mo); main secondary outcomes included behavior changes and patient perceptions such as self-efficacy and acceptability of the intervention programs. More than 50% of studies reported positive effects of interventions based on primary outcomes. The duration or length of intervention ranged from 1 wk to 24 mo. However, most studies included small samples and short intervention periods and did not use rigorous data collection or analytic approaches. Although some studies suggest that mHealth interventions are effective and promising, most are pilot studies or have limitations in their study designs. There is an essential need for future studies that use larger study samples, longer intervention (≥ 6 mo) and follow-up periods (≥ 6 mo), and integrative and personalized innovative mobile technologies to provide comprehensive and sustainable support for patients and health service providers.

mHealth for diabetes support: a systematic review of apps available on the Italian market

mHealth is an expanding field of research and experimentation, concerned with the potentialities of mobile applications as tools to enhance patients' abilities in the management of chronic conditions. We present a systematic review of mHealth applications available on the Italian market and for the Italian speakers in order to assess their reported usability and functions. The review shows that there are rather few products on offer and the ones that are available display weak educational components, do not seem to be based on solid theoretical models of behavior change or decision making, and do not seem to be intended as devices to be integrated in the ecology of the doctor-patient relationship.

Compliance Patterns and Utilization of e-Health for Glucose Monitoring: Standalone Internet Gateway and Tablet Device

BACKGROUND

Knowledge regarding compliance patterns and service utilization in e-health is important for the development of effective services. To develop proper e-health, the characteristics of compliance patterns and utilization of e-health should be studied. We studied these for glucose monitoring of diabetic patients from primary clinics.

MATERIALS AND METHODS

Data were collected from 160 outpatients who participated in e-health for glucose monitoring funded by the Korean government. Specifically, this study focused on two device types: a standalone Internet gateway and a tablet device. The SPSS 18.0 software was used for statistical analyses of demographic characteristics, survival data, and Cox proportional hazards regression model.

RESULTS

Standalone Internet gateway users demonstrated a more stable compliance pattern than did tablet device users. The compliance rate differed according to the device type. Typically, compliance decreases considerably around 8 months. In these results, standalone Internet gateway users utilized the service for longer periods than tablet device users. Gateway type and location also influenced utilization (p < 0.05).

CONCLUSIONS

The service should be designed according to the device type to develop appropriate service models. Thus, service designers should understand the different characteristics of service devices. This study provides insight into compliance patterns and utilization to develop appropriate service models and service interventions depending on the device.

Clinical Safety and Feasibility of the Advanced Bolus Calculator for Type 1 Diabetes Based on Case-Based Reasoning: A 6-Week Nonrandomized Single-Arm Pilot Study

BACKGROUND

The Advanced Bolus Calculator for Diabetes (ABC4D) is an insulin bolus dose decision support system based on case-based reasoning (CBR). The system is implemented in a smartphone application to provide personalized and adaptive insulin bolus advice for people with type 1 diabetes. We aimed to assess proof of concept, safety, and feasibility of ABC4D in a free-living environment over 6 weeks.

METHODS

Prospective nonrandomized single-arm pilot study. Participants used the ABC4D smartphone application for 6 weeks in their home environment, attending the clinical research facility weekly for data upload, revision, and adaptation of the CBR case base. The primary outcome was postprandial hypoglycemia.

RESULTS

Ten adults with type 1 diabetes, on multiple daily injections of insulin, mean (standard deviation) age 47 (17), diabetes duration 25 (16), and HbA1c 68 (16) mmol/mol (8.4 (1.5) %) participated. A total of 182 and 150 meals, in week 1 and week 6, respectively, were included in the analysis of postprandial outcomes. The median (interquartile range) number of postprandial hypoglycemia episodes within 6-h after the meal was 4.5 (2.0-8.2) in week 1 versus 2.0 (0.5-6.5) in week 6 (P = 0.1). No episodes of severe hypoglycemia occurred during the study.

CONCLUSION

The ABC4D is safe for use as a decision support tool for insulin bolus dosing in self-management of type 1 diabetes. A trend suggesting a reduction in postprandial hypoglycemia was observed in the final week compared with week 1.

Effectiveness of short message service-based intervention (SMS) on self-care in type 2 diabetes: A feasibility study

AIM

The objective of the current study is to assess the effectiveness of Mobile Short Message Service (SMS) intervention on education of basic self-care skills in patients with type 2 diabetes. Moreover, we aimed to determine whether delivering individually-tailored educational messages can be more effective than general educational messages.

METHODS

A total of 150 patients with diabetes type 2 were randomized into three groups: tailored SMS group, non-tailored SMS group, and the control group. Biochemical parameters including HbA1c, FBS, lipid profile were evaluated for the three groups at baseline and after 12 weeks. Moreover, self-care Inventory (SCI), Diabetes Management Self-Efficacy Scale (DMSES) and Diabetes Self-Care Barriers assessment scale for Older Adults (DSCB-OA) were completed. In the tailored SMS group, each person received 75% of their messages based on the top two barriers to adherence that they had experienced and reported in their scale. In the non-tailored SMS group, random messages were sent to every patient.

RESULTS

After 12 weeks, although HgA1c levels did not significantly change, significant decline was observed in FBS and mean BMI in both intervention groups. Mean SCI-R scores significantly increased and mean DSCB and DMSES scores significantly decreased in both tailored and non-tailored SMS groups. In the control group, mean SCI-R scores decreased and mean DSCB and DMSES scores significantly increased (P<0.001).

CONCLUSION

Sending short text messages as a method of education in conjunction with conventional diabetes treatment can improve glycemic control and positively influence other aspects of diabetes self-care. According to our findings, sending SMS regularly in particular times appears to be as effective as sending individually tailored messages.

What do we know about mobile applications for diabetes self-management? A review of reviews

Diabetes is a chronic illness with significant health consequences, especially for those who are unable to adhere to the complex treatment regimen. Self-management tasks such as regular medication and insulin use, frequent blood sugar checks, strict diet management, and consistent exercise can be quite challenging. Mobile technologies, specifically mobile applications (apps), present a unique opportunity to help patients improve adherence to these behaviors. The availability of commercial diabetes self-management apps is increasing rapidly, making it difficult for patients and providers to stay informed about app options. A number of reviews have described commercial app technology and use for patients with diabetes. The aims of this article are to summarize the results and themes of those reviews, to review outcomes of apps described in the research literature, and to identify areas for further consideration in the use of mobile apps for diabetes self-management.

Innovative health informatics as an effective modern strategy in diabetes management: a critical review

OBJECTIVE

Diabetes mellitus is the most common metabolic disorder in developing countries. Mobile health applications are helpful in improving the diabetes management. However, the effectiveness of these techniques needs to be assessed rigorously. Therefore, the authors have systematically reviewed the recent clinical studies using mobile health applications for diabetes management.

MATERIALS AND METHODS

Original articles that were published in ISI indexed journals listed in PubMed from the year 2007 till 2014 were searched using specific search key phrases. The intervention technology and study methodology were analysed to have a better understanding of the outcomes of each study.

RESULTS

Twenty-one articles were selected for the review. Most studies (76%) reported positive outcomes after use of the mobile health applications. Smartphone apps significantly improved the clinical outcomes. User-friendliness of the systems often influence the patient compliance and the clinical outcomes.

CONCLUSION

Smartphone/web applications offer significant benefits for patient care, education and behavioural modifications. Providing a continuous patient support using mobile may be a challenging task and would require adequate infrastructure and personnel.

Home telehealth for chronic disease management: selected findings of a narrative synthesis

BACKGROUND

Chronic disease has become an increasingly important issue for individuals and healthcare organizations across Canada. Home telehealth may have the potential to alleviate the economic and social challenges associated with rising rates of chronic disease. An aim of this review was to gather and synthesize the evidence on the effectiveness of home telehealth in chronic disease management.

MATERIALS AND METHODS

We searched the Medline, EMBASE, Web of Science, CINAHL, and PAIS databases for studies published in English from January 1, 2005, and December 31, 2010. Academic publications, white papers, and gray literature were all considered eligible for inclusion, provided an original research element was present. Articles were screened for relevance.

RESULTS

One hundred one articles on quantitative or mixed-methods studies reported the effects of home telehealth on disease state, symptoms, and quality of life in chronic disease patients. Studies were consistent in finding that home telehealth was equivalent or superior to usual care.

CONCLUSIONS

The literature strongly supports the use of home telehealth as an equally effective alternative to usual care. The circumstances under which home telehealth emerges as significantly better than usual care have not been extensively researched. Further research into factors affecting the effectiveness of home telehealth would support more widespread realization of telehealth's potential benefits.

The Effects of a Mobile Phone Application on Quality of Life in Patients With Type 1 Diabetes Mellitus: A Randomized Controlled Trial

BACKGROUND

The combination of an increasing prevalence of diabetes mellitus and more people having access to smartphones creates opportunities for patient care. This study aims to investigate whether the use of the Diabetes Under Control (DBEES) mobile phone application, a digital diabetes diary, results in a change in quality of life for patients with type 1 diabetes mellitus (T1DM) compared with the standard paper diary.

METHODS

In this randomized controlled open-label trial, 63 patients with T1DM having access to a smartphone were assigned to the intervention group using the DBEES application (n = 31) or the control group using the standard paper diary (n = 32). Primary outcome was the change in quality of life, as measured by the RAND-36 questionnaire, between both groups. Secondary outcomes included diabetes-related distress (PAID), HbA1c, frequency of self-monitoring blood glucose, and the usability of the diabetes application (SUS).

RESULTS

Patients had a median age (IQR) of 33 (21) years, diabetes duration of 17 (16) years, and an HbA1c of 62 ± 16 mmol/mol. No significant differences in the QOL, using the RAND-36, within and between both groups were observed after 3 months. Glycemic control, diabetes-related emotional distress, and frequency of self-monitoring of blood glucose remained within and between groups. Users reviewed the usability of DBEES with a 72 ± 20, on a range of 0-100.

CONCLUSIONS

The use of the DBEES application in the management of patients with T1DM for 3 months yields no alterations in quality of life compared to the standard paper diary.

Digital health interventions for the prevention of cardiovascular disease: a systematic review and meta-analysis

OBJECTIVE

To assess the potential benefit of digital health interventions (DHIs) on cardiovascular disease (CVD) outcomes (CVD events, all-cause mortality, hospitalizations) and risk factors compared with non-DHIs.

PATIENTS AND METHODS

We conducted a systematic search of PubMed, MEDLINE, EMBASE, Web of Science, Ovid, CINHAL, ERIC, PsychINFO, Cochrane, and Cochrane Central Register of Controlled Trials for articles published from January 1, 1990, through January 21, 2014. Included studies examined any element of DHI (telemedicine, Web-based strategies, e-mail, mobile phones, mobile applications, text messaging, and monitoring sensors) and CVD outcomes or risk factors. Two reviewers independently evaluated study quality utilizing a modified version of the Cochrane Collaboration risk assessment tool. Authors extracted CVD outcomes and risk factors for CVD such as weight, body mass index, blood pressure, and lipid levels from 51 full-text articles that met validity and inclusion criteria.

RESULTS

Digital health interventions significantly reduced CVD outcomes (relative risk, 0.61; 95% CI, 0.46-0.80; P<.001; I(2)=22%). Concomitant reductions in weight (-2.77 lb [95% CI, -4.49 to -1.05 lb]; P<.002; I(2)=97%) and body mass index (-0.17 kg/m(2) [95% CI, -0.32 kg/m(2) to -0.01 kg/m(2)]; P=.03; I(2)=97%) but not blood pressure (-1.18 mm Hg [95% CI, -2.93 mm Hg to 0.57 mm Hg]; P=.19; I(2)=100%) were found in these DHI trials compared with usual care. In the 6 studies reporting Framingham risk score, 10-year risk percentages were also significantly improved (-1.24%; 95% CI, -1.73% to -0.76%; P<.001; I(2)=94%). Results were limited by heterogeneity not fully explained by study population (primary or secondary prevention) or DHI modality.

CONCLUSION

Overall, these aggregations of data provide evidence that DHIs can reduce CVD outcomes and have a positive impact on risk factors for CVD.

Texting teens in transition: the use of text messages in clinical intervention research

BACKGROUND

The rapidly growing population of young adults living with congenital heart disease (CHD), currently challenging ill-prepared cardiac care systems, presents a novel population in which to consider the use of mHealth. This methodological study was part of a larger study that tested the effectiveness of a clinic-based nursing intervention to prepare teens for transfer from pediatric to adult cardiology care. The intervention included creation of a MyHealth Passport and subsequently SMS (short message service) text messages between the intervention nurse and study participant.

OBJECTIVE

Our aim was to determine (1) the preference of teens with CHD to be contacted via text message following the nursing intervention, (2) the effectiveness of texting to collect data regarding the use of MyHealth Passport after participation in the intervention, (3) the nature of the texting interaction, and (4) the risks and benefits of texting.

METHODS

Participants were recruited through the intervention study (n=24) by either choosing to receive information from the study coordinator through text message, or texting a question to the study nurses. Inclusion criteria were age 15-17 years, diagnosed with moderate or complex heart disease, and currently being followed by the Division of Cardiology at Stollery Children's Hospital. Exclusion criteria were heart transplantation and/or less than a 6th grade reading and comprehension ability. Text message transcripts were analyzed by qualitative inductive content analysis.

RESULTS

Two-thirds of teens (16/24, 67%) chose text messaging as their preferred contact, making them eligible for the study. Texting was effective in collecting information regarding the MyHealth Passport; all but one teen had their MyHealth Passport on them, and many reported carrying it with them wherever they went. All teens reported showing their MyHealth Passport to at least one person. Seven themes were identified in the texting transcripts: mixing formal and informal language, the passive teen, interaction with health care providers, texting teens in transition, texting as a mechanism to initiate other forms of communication, affirmation, and the nurse as an educator. Benefits of texting were identified as flexibility, ability to respond over time, information presented in byte-sized amounts, and information directly related to patient questions. Risks of texting were identified as the possibility that interactions may not be in-depth, distraction of teen and researcher, and invasiveness.

CONCLUSIONS

Text messaging was useful in collecting data regarding the use of the MyHealth Passport. Text messaging resulted in conversations with the teens that were sometimes in-depth and meaningful, especially when combined with other communication modalities. Using text messaging in a manner resulting in full conversations with the patients requires more study and may benefit from protocols and the use of solid theoretical foundations that would standardize the interaction so that more conclusions could be drawn.

Bolus calculators

Matching meal insulin to carbohydrate intake, blood glucose, and activity level is recommended in type 1 diabetes management. Calculating an appropriate insulin bolus size several times per day is, however, challenging and resource demanding. Accordingly, there is a need for bolus calculators to support patients in insulin treatment decisions. Currently, bolus calculators are available integrated in insulin pumps, as stand-alone devices and in the form of software applications that can be downloaded to, for example, smartphones. Functionality and complexity of bolus calculators vary greatly, and the few handfuls of published bolus calculator studies are heterogeneous with regard to study design, intervention, duration, and outcome measures. Furthermore, many factors unrelated to the specific device affect outcomes from bolus calculator use and therefore bolus calculator study comparisons should be conducted cautiously. Despite these reservations, there seems to be increasing evidence that bolus calculators may improve glycemic control and treatment satisfaction in patients who use the devices actively and as intended.

Tracking and journaling the cancer journey

Clinicians sometimes suggest to patients that they keep track of illness-related issues. Self-monitoring is a helpful term to describe these at-home activities that yield essential information for self-management. The purpose of this article is to create greater awareness of the opportunities (and potential shortcomings) of patient self-monitoring for oncology nursing practice.

Diabetes self-management smartphone application for adults with type 1 diabetes: randomized controlled trial

Background

Persistently poor glycemic control in adult type 1 diabetes patients is a common, complex, and serious problem initiating significant damage to the cardiovascular, renal, neural, and visual systems. Currently, there is a plethora of low-cost and free diabetes self-management smartphone applications available in online stores.

Objective

The aim of this study was to examine the effectiveness of a freely available smartphone application combined with text-message feedback from a certified diabetes educator to improve glycemic control and other diabetes-related outcomes in adult patients with type 1 diabetes in a two-group randomized controlled trial.

Methods

Patients were recruited through an online type 1 diabetes support group and letters mailed to adults with type 1 diabetes throughout Australia. In a 6-month intervention, followed by a three-month follow-up, patients (n=72) were randomized to usual care (control group) or usual care and the use of a smartphone application (Glucose Buddy) with weekly text-message feedback from a Certified Diabetes Educator (intervention group). All outcome measures were collected at baseline and every three months over the study period. Patients’ glycosylated hemoglobin levels (HbA1c) were measured with a blood test and diabetes-related self-efficacy, self-care activities, and quality of life were measured with online questionnaires.

Results

The mean age of patients was 35.20 years (SD 10.43) (28 male, 44 female), 39% (28/72) were male, and patients had been diagnosed with type 1 diabetes for a mean of 18.94 years (SD 9.66). Of the initial 72 patients, 53 completed the study (25 intervention, 28 control group). The intervention group significantly improved glycemic control (HbA1c) from baseline (mean 9.08%, SD 1.18) to 9-month follow-up (mean 7.80%, SD 0.75), compared to the control group (baseline: mean 8.47%, SD 0.86, follow-up: mean 8.58%, SD 1.16). No significant change over time was found in either group in relation to self-efficacy, self-care activities, and quality of life.

Conclusions

In adjunct to usual care, the use of a diabetes-related smartphone application combined with weekly text-message support from a health care professional can significantly improve glycemic control in adults with type 1 diabetes.

Trial Registration

Australian New Zealand Clinical Trials Registry: ACTRN12612000132842; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?ACTRN=12612000132842 (Archived by WebCite at http://www.webcitation.org/6Kl4jqn5u).

Glucose variability: An emerging target for the treatment of diabetes mellitus

Alterations in glucose metabolism in individuals with diabetes have been considered for many years, as they appear at first glance, i.e., simply as hyperglycemia, and its surrogate marker, glycated hemoglobin (HbA1c), used both to estimate the risk of developing diabetic complications and to define the targets and measure the efficacy of diabetes treatments. However, over time diabetes-related glycemic alterations have been considered in more complex terms, by attempting to identify the role of fasting glycemia, postprandial glycemia and hypoglycemia in the overall assessment of the disease. This set of evaluations has led to the concept of glucose variability. Although intuitively easy to understand, it cannot be equally simply translated into terms of definition, measuring, prognostic and therapeutic impact. The literature available on glucose variability is extensive yet confused, with the only common element being the need to find out more on the subject. The purpose of this manuscript is not only to review the most recent evidence on glucose variability, but also to help the reader to better understand the available measurement options, and how the various definitions can differently be related with the development of diabetic complications. Finally, we provide how new and old drugs can impact on glucose variability.

Impact of the "Diabetes Interactive Diary" telemedicine system on metabolic control, risk of hypoglycemia, and quality of life: a randomized clinical trial in type 1 diabetes

BACKGROUND

Telemedicine systems based on mobile phones represent new promising educational tools. The "Diabetes Interactive Diary" (DID) is a carbohydrate/bolus calculator promoting the patient-physician communication via short message service. This study aimed to compare the efficacy of the DID versus usual care on metabolic control, hypoglycemia, and quality of life.

PATIENTS AND METHODS

Patients with type 1 diabetes on a basal:bolus regimen with insulin glargine and insulin glulisine, not previously educated on carbohydrate (CHO) counting, were randomized to DID (Group A; n=63) or traditional education (Group B; n=64). Generalized hierarchical linear regression models for repeated measures were applied to compare changes between groups. Incidence of hypoglycemia was compared using Poisson regression models.

RESULTS

Of 127 patients (age, 36.9±10.5 years; diabetes duration, 16.3±9.3 years), 15 (11.8%) dropped out. After 6 months, hemoglobin A1c (HbA1c) levels decreased by -0.49±0.11 in Group A and -0.48±0.11 in Group B (P=0.73). Group A showed a 86% lower risk of grade 2 hypoglycemia than Group B. Compared with usual care, DID improved the "perceived frequency of hyperglycemic episodes" scale of the Diabetes Treatment Satisfaction Questionnaire and the "social relations" and the "fear of hypoglycemia" dimensions of the Diabetes Specific Quality of Life Scale. Results obtained with DID markedly differ among patients and centers.

CONCLUSIONS

DID is no more effective than traditional CHO counting education in reducing HbA1c levels. DID reduces the risk of moderate/severe hypoglycemia and improves quality of life. A better understanding of patients' and healthcare professionals' attitudes associated with an effective care supported by technology is essential to avoid waste of resources.

A systematic review of IT for diabetes self-management: are we there yet?

BACKGROUND

Recent advances in information technology (IT) coupled with the increased ubiquitous nature of information technology (IT) present unique opportunities for improving diabetes self-management. The objective of this paper is to determine, in a systematic review, how IT has been used to improve self-management for adults with Type 1 and Type 2 diabetes.

METHODS

The review covers articles extracted from relevant databases using search terms related information technology and diabetes self-management published after 1970 until August 2012. Additional articles were extracted using the citation map in Web of Science. Articles representing original research describing the use of IT as an enabler for self-management tasks performed by the patient are included in the final analysis.

RESULTS

Overall, 74% of studies showed some form of added benefit, 13% articles showed no-significant value provided by IT, and 13% of articles did not clearly define the added benefit due to IT. Information technologies used included the Internet (47%), cellular phones (32%), telemedicine (12%), and decision support techniques (9%). Limitations and research gaps identified include usability, real-time feedback, integration with provider electronic medical record (EMR), as well as analytics and decision support capabilities.

CONCLUSION

There is a distinct need for more comprehensive interventions, in which several technologies are integrated in order to be able to manage chronic conditions such as diabetes. Such IT interventions should be theoretically founded and should rely on principles of user-centered and socio-technical design in its planning, design and implementation. Moreover, the effectiveness of self-management systems should be assessed along multiple dimensions: motivation for self-management, long-term adherence, cost, adoption, satisfaction and outcomes as a final result.

The impact of mobile monitoring technologies on glycosylated hemoglobin in diabetes: a systematic review

BACKGROUND

A new development in the field of telehealth is the use of mobile health technologies (mhealth) to help patients record and track medical information. Mhealth appears particularly advantageous for conditions that require intense and ongoing monitoring, such as diabetes, and where people are of working age and not disabled. This review aims to evaluate the evidence for the effectiveness of mhealth interventions in diabetes management on glycosylated hemoglobin.

METHOD

A comprehensive search strategy was developed and applied to eight electronic databases to identify studies that investigated the clinical effectiveness of mobile-based applications that allowed patients to record and send their blood glucose readings to a central server. The eligibility of 8543 papers was assessed against the selection criteria, and 24 papers were reviewed. All studies reviewed were assessed for quality using a standardized quality assessment tool.

RESULTS

Results for patients with type 1 and type 2 diabetes were examined separately. Study variability and poor reporting made comparison difficult, and most studies had important methodological weaknesses. Evidence on the effectiveness of mhealth interventions for diabetes was inconsistent for both types of diabetes and remains weak.

Use of an automated bolus calculator in MDI-treated type 1 diabetes: the BolusCal Study, a randomized controlled pilot study

OBJECTIVE

To investigate the effect of flexible intensive insulin therapy (FIIT) and an automated bolus calculator (ABC) in a Danish type 1 diabetes population treated with multiple daily injections. Furthermore, to test the feasibility of teaching FIIT in a 3-h structured course.

RESEARCH DESIGN AND METHODS

The BolusCal Study was a 16-week randomized, controlled, open-label, three-arm parallel, clinical study of 51 adults with type 1 diabetes. Patients aged 18-65 years in poor metabolic control (HbA(1c) 8.0-10.5%) were randomized to the Control (n = 8), CarbCount (n = 21), or CarbCountABC (n = 22) arm. During a 3-h group teaching, the Control arm received FIIT education excluding carbohydrate counting. CarbCount patients were taught FIIT and how to count carbohydrates. CarbCountABC group teaching included FIIT and carbohydrate counting and patients were provided with an ABC.

RESULTS

At 16 weeks, the within-group change in HbA(1c) was -0.1% (95% CI -1.0 to 0.7%; P = 0.730) in the Control arm, -0.8% (-1.3 to -0.3%; P = 0.002) in the CarbCount arm, and -0.7% (-1.0 to -0.4%; P < 0.0001) in the CarbCountABC arm. The difference in change in HbA(1c) between CarbCount and CarbCountABC was insignificant. Adjusting for baseline HbA(1c) in a regression model, the relative change in HbA(1c) was -0.6% (-1.2 to 0.1%; P = 0.082) in CarbCount and -0.8% (-1.4 to -0.1%; P = 0.017) in CarbCountABC. Treatment satisfaction measured by the Diabetes Treatment Satisfaction Questionnaire (status version) improved in all study arms, but the improvement was significantly greater in CarbCountABC.

CONCLUSIONS

FIIT and carbohydrate counting were successfully taught in 3 h and improved metabolic control and treatment satisfaction. Concurrent use of an ABC improved treatment satisfaction further.

Diabetes management via mobile phones: a systematic review

BACKGROUND

This study sought to understand the most common uses and functions of mobile phones in monitoring and managing diabetes, their potential role in a clinical setting, and the current state of research in this area.

METHODS

We identified peer-reviewed articles published between 2000 and 2010. Twenty-one articles were analyzed for this systematic literature review.

RESULTS

The majority of studies examined the use of mobile phones from the patient's perspective. Subjects with type 1 diabetes were enrolled exclusively in over 50% of the studies. Seventy-one percent of the studies used a study-specific application, which had supplemental features in addition to text messaging. The outcomes assessed varied considerably across studies, but some positive trends were noted, such as improved self-efficacy, hemoglobin A1c, and self-management behaviors.

CONCLUSIONS

The studies evaluated showed promise in using mobile phones to help people with diabetes manage their condition effectively. However, many of these studies lacked sufficient sample sizes or intervention lengths to determine whether the results might be clinically or statistically significant. Future research should examine other key issues, such as provider perceptions, integration into a healthcare practice, and cost, which would provide important insight into the use of mobile phones for chronic disease management.

Mobile intervention design in diabetes: review and recommendations

Mobile technology enhances the potential to assess, prompt, educate, and engage individuals with diabetes. The near-ubiquitous presence of mobile phones allows real-time contextually relevant support for diabetes self-care. We review the design of mobile interventions included in a recent meta-analysis. Although mobile programs can lead to improvements in glycemic control, many aspects, such as the role of the diabetes clinician, real-time features, and patient engagement have not been documented. Studies with the greatest impact on hemoglobin A(1c) integrated patient feedback and a role for clinicians. Research is needed regarding feasible and efficacious roles for clinical support in mobile interventions. Recommendations for design and research include the following: consideration of patient and clinician burden; identification of patterns and metrics for patient treatment adherence and engagement; integration of goal setting and problem solving; enhancing patient education; a greater focus on patient-centered motivational strategies; and utilization of study designs that relate intervention design elements to outcomes.

Effectiveness and safety of a glucose data-filtering system with automatic response software to reduce the physician workload in managing type 2 diabetes

We conducted a randomized controlled trial to investigate the efficacy and safety of a system for online glucose monitoring of type 2 diabetes patients. The software automatically filtered the self-monitored blood glucose data to reduce physicians' time. In the control group, the physicians had to contact the patients manually. We measured the time spent by physicians for online management in a 24-week study. Seventy-nine patients were recruited. The frequency of physicians' online monitoring of the patients was decreased by 55% in patients with HbA(1c) ≤ 6.5% and by 29% when HbA(1c) > 6.5% (P < 0.01). Physicians' log-in time was reduced by 67% and 55% in patients with HbA(1c) ≤6.5% and >6.5%, respectively (P <0.05). HbA(1c) levels were maintained at <6.5% during the study period in both groups. The study showed the efficacy and safety of the software for online communication in diabetes management. The results suggest that it could improve the cost-effectiveness of online communication systems and form the basis of future clinical applications.

Effect of mobile phone intervention for diabetes on glycaemic control: a meta-analysis

AIMS

  To assess the effect of mobile phone intervention on glycaemic control in diabetes self-management.

METHODS

We searched three electronic databases (PubMed, EMBASE and Cochrane Library) using the following terms: diabetes or diabetes mellitus and mobile phone or cellular phone, or text message. We also manually searched reference lists of relevant papers to identify additional studies. Clinical studies that used mobile phone intervention and reported changes in glycosylated haemoglobin (HbA(1c) ) values in patients with diabetes were reviewed. The study design, intervention methods, sample size and clinical outcomes were extracted from each trial. The results of the HbA(1c) change in the trials were pooled using meta-analysis methods.

RESULTS

  A total of 22 trials were selected for the review. Meta-analysis among 1657 participants showed that mobile phone interventions for diabetes self-management reduced HbA(1c) values by a mean of 0.5% [6 mmol/mol; 95% confidence interval, 0.3-0.7% (4-8 mmol/mol)] over a median of 6 months follow-up duration. In subgroup analysis, 11 studies among Type 2 diabetes patients reported significantly greater reduction in HbA(1c) than studies among Type 1 diabetes patients [0.8 (9 mmol/mol) vs. 0.3% (3 mmol/mol); P=0.02]. The effect of mobile phone intervention did not significantly differ by other participant characteristics or intervention strategies.

CONCLUSIONS

  Results pooled from the included trials provided strong evidence that mobile phone intervention led to statistically significant improvement in glycaemic control and self-management in diabetes care, especially for Type 2 diabetes patients.

Mobile phone technologies and advanced data analysis towards the enhancement of diabetes self-management

Advances in the area of mobile and wireless communication for healthcare (m-Health) along with the improvements in information science allow the design and development of new patient-centric models for the provision of personalised healthcare services, increase of patient independence and improvement of patient's self-control and self-management capabilities. This paper comprises a brief overview of the m-Health applications towards the self-management of individuals with diabetes mellitus and the enhancement of their quality of life. Furthermore, the design and development of a mobile phone application for Type 1 Diabetes Mellitus (T1DM) self-management is presented. The technical evaluation of the application, which permits the management of blood glucose measurements, blood pressure measurements, insulin dosage, food/drink intake and physical activity, has shown that the use of the mobile phone technologies along with data analysis methods might improve the self-management of T1DM.

Text messaging in health care: a systematic review of impact studies

BACKGROUND

Studies suggest text messaging is beneficial to health care; however, no one has synthesized the overall evidence on texting interventions. In response to this need, we conducted a systematic review of the impacts of text messaging in health care.

METHODS

PubMed database searches and subsequent reference list reviews sought English-language, peer-reviewed studies involving text messaging in health care. Commentaries, conference proceedings, and feasibilities studies were excluded. Data was extracted using an article coding sheet and input into a database for analysis.

RESULTS

Of the 61 papers reviewed, 50 articles (82%) found text messaging had a positive effect on the primary outcome. Average sample sizes in articles reporting positive findings (n=813) were significantly larger than those that did not find a positive impact (n=178) on outcomes (p = 0.032). Articles were categorized into focal groups as follows: 27 articles (44.3%) investigated the impact of texting on disease management, 24 articles (39.3%) focused texting's impact to public health related outcomes, and 10 articles (16.4%) examined texting and its influence on administrative processes. Articles in focal groups differed by the purpose of the study, direction of the communication, and where they were published, but not in likelihood of reporting a positive impact from texting.

CONCLUSIONS

Current evidence indicates that text messaging health care interventions are largely beneficial clinically, in public health related uses, and in terms of administrative processes. However, despite the promise of these findings, literature gaps exist, especially in primary care settings, across geographic regions and with vulnerable populations.

Telemedicine-supported insulin optimisation in primary care

We investigated the feasibility of a mobile-phone based system for patients with type 2 diabetes who had recently commenced insulin therapy but remained poorly controlled. The system was evaluated in a feasibility study in a general practice setting with 23 patients over six months. A total of 22 patients successfully completed the study and used the system for a mean of 217 days (range 162-376). Blood glucose control improved, as reflected by a mean decrease in HbA(1c) of 0.66% (P = 0.05), with the mean insulin dose increasing by 17 units (P = 0.006). Blood glucose monitoring compliance was high, with readings available for 6.2 days per week, although use of the mobile phone decreased during the study. On average, the mobile phone diary was used for 3.5 days per week. Insulin dose adjustments were made throughout the study by all patients, but not as frequently as would be expected for the degree of hyperglycaemia observed.

Asynchronous and synchronous teleconsultation for diabetes care: a systematic literature review

AIM

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.

METHODS

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.

RESULTS

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).

CONCLUSION

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.

Diabetes Interactive Diary: a new telemedicine system enabling flexible diet and insulin therapy while improving quality of life: an open-label, international, multicenter, randomized study

OBJECTIVE

Widespread use of carbohydrate counting is limited by its complex education. In this study we compared a Diabetes Interactive Diary (DID) with standard carbohydrate counting in terms of metabolic and weight control, time required for education, quality of life, and treatment satisfaction.

RESEARCH DESIGN AND METHODS

Adults with type 1 diabetes were randomly assigned to DID (group A, n = 67) or standard education (group B, n = 63) and followed for 6 months. A subgroup also completed the SF-36 Health Survey (SF-36) and World Health Organization-Diabetes Treatment Satisfaction Questionnaire (WHO-DTSQ) at each visit.

RESULTS

Of 130 patients (aged 35.7 +/- 9.4 years; diabetes duration 16.5 +/- 10.5 years), 11 dropped out. Time for education was 6 h (range 2-15 h) in group A and 12 h (2.5-25 h) in group B (P = 0.07). A1C reduction was similar in both groups (group A from 8.2 +/- 0.8 to 7.8 +/- 0.8% and group B from 8.4 +/- 0.7 to 7.9 +/- 1.1%; P = 0.68). Nonsignificant differences in favor of group A were documented for fasting blood glucose and body weight. No severe hypoglycemic episode occurred. WHO-DTSQ scores increased significantly more in group A (from 26.7 +/- 4.4 to 30.3 +/- 4.5) than in group B (from 27.5 +/- 4.8 to 28.6 +/- 5.1) (P = 0.04). Role Physical, General Health, Vitality, and Role Emotional SF-36 scores improved significantly more in group A than in group B.

CONCLUSIONS

DID is at least as effective as traditional carbohydrate counting education, allowing dietary freedom for a larger proportion of type 1 diabetic patients. DID is safe, requires less time for education, and is associated with lower weight gain. DID significantly improved treatment satisfaction and several quality-of-life dimensions.