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

Effects of an Electronic Medical Records-Linked Diabetes Self-Management System on Treatment Targets in Real Clinical Practice: Retrospective, Observational Cohort Study

BACKGRUOUND

This study evaluated the effects of a mobile diabetes management program called "iCareD" (College of Medicine, The Catholic University of Korea) which was integrated into the hospital's electronic medical records system to minimize the workload of the healthcare team in the real clinical practice setting.

METHODS

In this retrospective observational study, we recruited 308 patients. We categorized these patients based on their compliance regarding their use of the iCareD program at home; compliance was determined through self-monitored blood glucose inputs and message subscription rates. We analyzed changes in the ABC (hemoglobin A1c, blood pressure, and low-density lipoprotein cholesterol) levels from the baseline to 12 months thereafter, based on the patients' iCareD usage patterns.

RESULTS

The patients comprised 92 (30%) non-users, 170 (55%) poor-compliance users, and 46 (15%) good-compliance users; the ABC target achievement rate showed prominent changes in good-compliance groups from baseline to 12 months (10.9% vs. 23.9%, P<0.05), whereas no significant changes were observed for poor-compliance users and non-users (13.5% vs. 18.8%, P=0.106; 20.7% vs. 14.1%, P=0.201; respectively).

CONCLUSION

Implementing the iCareD can improve the ABC levels of patients with diabetes with minimal efforts of the healthcare team in real clinical settings. However, the improvement of patients' compliance concerning the use of the system without the vigorous intervention of the healthcare team needs to be solved in the future.

The effect of personalized intelligent digital systems for self-care training on type II diabetes: a systematic review and meta-analysis of clinical trials

AIMS

Type 2 diabetes (T2D) is rising worldwide. Self-care prevents diabetic complications. Lack of knowledge is one reason patients fail at self-care. Intelligent digital health (IDH) solutions have a promising role in training self-care behaviors based on patients' needs. This study reviews the effects of RCTs offering individualized self-care training systems for T2D patients.

METHODS

PubMed, Web of Science, Scopus, Cochrane Library, and Science Direct databases were searched. The included RCTs provided data-driven, individualized self-care training advice for T2D patients. Due to the repeated studies measurements, an all-time-points meta-analysis was conducted to analyze the trends over time. The revised Cochrane risk-of-bias tool (RoB 2.0) was used for quality assessment.

RESULTS

In total, 22 trials met the inclusion criteria, and 19 studies with 3071 participants were included in the meta-analysis. IDH interventions led to a significant reduction of HbA1c level in the intervention group at short-term (in the third month: SMD = - 0.224 with 95% CI - 0.319 to - 0.129, p value < 0.0; in the sixth month: SMD = - 0.548 with 95% CI - 0.860 to - 0.237, p value < 0.05). The difference in HbA1c reduction between groups varied based on patients' age and technological forms of IDH services delivery. The descriptive results confirmed the impact of M-Health technologies in improving HbA1c levels.

CONCLUSIONS

IDH systems had significant and small effects on HbA1c reduction in T2D patients. IDH interventions' impact needs long-term RCTs. This review will help diabetic clinicians, self-care training system developers, and researchers interested in using IDH solutions to empower T2D patients.

Quality improvement strategies for diabetes care: Effects on outcomes for adults living with diabetes

BACKGROUND

There is a large body of evidence evaluating quality improvement (QI) programmes to improve care for adults living with diabetes. These programmes are often comprised of multiple QI strategies, which may be implemented in various combinations. Decision-makers planning to implement or evaluate a new QI programme, or both, need reliable evidence on the relative effectiveness of different QI strategies (individually and in combination) for different patient populations.

OBJECTIVES

To update existing systematic reviews of diabetes QI programmes and apply novel meta-analytical techniques to estimate the effectiveness of QI strategies (individually and in combination) on diabetes quality of care.

SEARCH METHODS

We searched databases (CENTRAL, MEDLINE, Embase and CINAHL) and trials registers (ClinicalTrials.gov and WHO ICTRP) to 4 June 2019. We conducted a top-up search to 23 September 2021; we screened these search results and 42 studies meeting our eligibility criteria are available in the awaiting classification section.

SELECTION CRITERIA

We included randomised trials that assessed a QI programme to improve care in outpatient settings for people living with diabetes. QI programmes needed to evaluate at least one system- or provider-targeted QI strategy alone or in combination with a patient-targeted strategy. - System-targeted: case management (CM); team changes (TC); electronic patient registry (EPR); facilitated relay of clinical information (FR); continuous quality improvement (CQI). - Provider-targeted: audit and feedback (AF); clinician education (CE); clinician reminders (CR); financial incentives (FI). - Patient-targeted: patient education (PE); promotion of self-management (PSM); patient reminders (PR). Patient-targeted QI strategies needed to occur with a minimum of one provider or system-targeted strategy.

DATA COLLECTION AND ANALYSIS

We dual-screened search results and abstracted data on study design, study population and QI strategies. We assessed the impact of the programmes on 13 measures of diabetes care, including: glycaemic control (e.g. mean glycated haemoglobin (HbA1c)); cardiovascular risk factor management (e.g. mean systolic blood pressure (SBP), low-density lipoprotein cholesterol (LDL-C), proportion of people living with diabetes that quit smoking or receiving cardiovascular medications); and screening/prevention of microvascular complications (e.g. proportion of patients receiving retinopathy or foot screening); and harms (e.g. proportion of patients experiencing adverse hypoglycaemia or hyperglycaemia). We modelled the association of each QI strategy with outcomes using a series of hierarchical multivariable meta-regression models in a Bayesian framework. The previous version of this review identified that different strategies were more or less effective depending on baseline levels of outcomes. To explore this further, we extended the main additive model for continuous outcomes (HbA1c, SBP and LDL-C) to include an interaction term between each strategy and average baseline risk for each study (baseline thresholds were based on a data-driven approach; we used the median of all baseline values reported in the trials). Based on model diagnostics, the baseline interaction models for HbA1c, SBP and LDL-C performed better than the main model and are therefore presented as the primary analyses for these outcomes. Based on the model results, we qualitatively ordered each QI strategy within three tiers (Top, Middle, Bottom) based on its magnitude of effect relative to the other QI strategies, where 'Top' indicates that the QI strategy was likely one of the most effective strategies for that specific outcome. Secondary analyses explored the sensitivity of results to choices in model specification and priors.  Additional information about the methods and results of the review are available as Appendices in an online repository. This review will be maintained as a living systematic review; we will update our syntheses as more data become available.

MAIN RESULTS

We identified 553 trials (428 patient-randomised and 125 cluster-randomised trials), including a total of 412,161 participants. Of the included studies, 66% involved people living with type 2 diabetes only. Participants were 50% female and the median age of participants was 58.4 years. The mean duration of follow-up was 12.5 months. HbA1c was the commonest reported outcome; screening outcomes and outcomes related to cardiovascular medications, smoking and harms were reported infrequently. The most frequently evaluated QI strategies across all study arms were PE, PSM and CM, while the least frequently evaluated QI strategies included AF, FI and CQI. Our confidence in the evidence is limited due to a lack of information on how studies were conducted.  Four QI strategies (CM, TC, PE, PSM) were consistently identified as 'Top' across the majority of outcomes. All QI strategies were ranked as 'Top' for at least one key outcome. The majority of effects of individual QI strategies were modest, but when used in combination could result in meaningful population-level improvements across the majority of outcomes. The median number of QI strategies in multicomponent QI programmes was three.  Combinations of the three most effective QI strategies were estimated to lead to the below effects:  - PR + PSM + CE: decrease in HbA1c by 0.41% (credibility interval (CrI) -0.61 to -0.22) when baseline HbA1c < 8.3%; - CM + PE + EPR: decrease in HbA1c by 0.62% (CrI -0.84 to -0.39) when baseline HbA1c > 8.3%;  - PE + TC + PSM: reduction in SBP by 2.14 mmHg (CrI -3.80 to -0.52) when baseline SBP < 136 mmHg; - CM + TC + PSM: reduction in SBP by 4.39 mmHg (CrI -6.20 to -2.56) when baseline SBP > 136 mmHg;  - TC + PE + CM: LDL-C lowering of 5.73 mg/dL (CrI -7.93 to -3.61) when baseline LDL < 107 mg/dL; - TC + CM + CR: LDL-C lowering by 5.52 mg/dL (CrI -9.24 to -1.89) when baseline LDL > 107 mg/dL. Assuming a baseline screening rate of 50%, the three most effective QI strategies were estimated to lead to an absolute improvement of 33% in retinopathy screening (PE + PR + TC) and 38% absolute increase in foot screening (PE + TC + Other).

AUTHORS' CONCLUSIONS

There is a significant body of evidence about QI programmes to improve the management of diabetes. Multicomponent QI programmes for diabetes care (comprised of effective QI strategies) may achieve meaningful population-level improvements across the majority of outcomes. For health system decision-makers, the evidence summarised in this review can be used to identify strategies to include in QI programmes. For researchers, this synthesis identifies higher-priority QI strategies to examine in further research regarding how to optimise their evaluation and effects. We will maintain this as a living systematic review.

Towards Telemedicine Adoption in Korea: 10 Practical Recommendations for Physicians

Due to the coronavirus disease 2019 (COVID-19) outbreak, consultation and prescription via telemedicine were temporarily allowed in the Korean population. However, at this point, it is difficult to determine whether telemedicine fulfills its role as a health care strategy. Arguably, if we had enough previous experience with telemedicine or sufficient preparation for its application, telemedicine could be more smoothly and flexibly adopted in the medical field. As it is still not possible to predict when the COVID-19 pandemic will end, phone consultation and prescription are likely to continue for some time. Hence, it is expected that telemedicine will naturally settle in the medical field in the near future. However, as we have noticed during this outbreak, improvised telemedicine without adequate guidance can be confusing to both patients and health professionals, thus reducing the benefit to patients. Medical staff requires preparation on how to appropriately use telemedicine. Thus, here we present some suggestions on implementing and preparing for telemedicine in the medical community.

Effect of Telemetric Interventions on Glycated Hemoglobin A1c and Management of Type 2 Diabetes Mellitus: Systematic Meta-Review

Background

Diabetes mellitus is a chronic burden, with a prevalence that is increasing worldwide. Telemetric interventions have attracted great interest and may provide effective new therapeutic approaches for improving type 2 diabetes mellitus (T2DM) care.

Objective

The objective of this study was to analyze the clinical effectiveness of telemetric interventions on glycated hemoglobin A_1c (HbA_1c) specifically and T2DM management generally in a systematic meta-review.

Methods

A systematic literature search was performed in PubMed, CINAHL, Cochrane Library, Web of Science Core Collection, and EMBASE databases from January 2008 to April 2020. Studies that addressed HbA_1c, blood pressure, fasting blood glucose, BMI, diabetes-related and health-related quality of life, cost-effectiveness, time savings, and the clinical effectiveness of telemetric interventions were analyzed. In total, 73 randomized controlled trials (RCTs), 10 systematic reviews/meta-analyses, 9 qualitative studies, 2 cohort studies, 2 nonrandomized controlled studies, 2 observational studies, and 1 noncontrolled intervention study were analyzed.

Results

Overall, 1647 citations were identified. After careful screening, 99 studies (n=15,939 patients; n=82,436 patient cases) were selected by two independent reviewers for inclusion in the review. Telemetric interventions were categorized according to communication channels to health care providers: (1) “real-time video” interventions, (2) “real-time audio” interventions, (3) “asynchronous” interventions, and (4) “combined” interventions. To analyze changes in HbA_1c, suitable RCTs were pooled and the average was determined. An HbA_1c decrease of –1.15% (95% CI –1.84% to –0.45%), yielding an HbA_1c value of 6.95% (SD 0.495), was shown in studies using 6-month “real-time video” interventions.

Conclusions

Telemetric interventions clearly improve HbA_1c values in both the short term and the long term and contribute to the effective management of T2DM. More studies need to be done in greater detail.

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.

Satisfaction Survey on Information Technology-Based Glucose Monitoring System Targeting Diabetes Mellitus in Private Local Clinics in Korea

BACKGROUND

Private local clinics in Korea have little experience with information technology (IT)-based glucose monitoring (ITGM). Our aim is to examine user satisfaction and the possibility of using ITGM service practically.

METHODS

Patients sent their blood glucose levels to physicians in local clinics. The physicians reviewed the blood glucose values online and provided personal consultations through text messaging or phone calls. Thereafter, a satisfaction survey on the ITGM service, the modified Morisky scale, and patient assessment of chronic illness care were administered.

RESULTS

One hundred and seventy patients from seven private local clinics used the ITGM. Overall satisfaction, including that about the ITGM service, the device, and its usefulness, was rated higher than "mostly satisfied" (score 4.2±0.8 out of 5.0) and even higher among the elderly. Satisfaction was positively associated with age, especially in those older than 60 years. The main reason for intent for future use of the service was the time/place flexibility. Highly motivated patients tended to answer positively regarding information satisfaction (P=0.0377).

CONCLUSION

Our study is the first to investigate ITGM satisfaction in private local clinics. The feasibility of users utilizing ITGM should be clarified, and future clinical research on the service's clinical effects and cost-benefit analysis is needed.

Effect of telemedicine on glycated hemoglobin in diabetes: a systematic review and meta-analysis of randomized trials

BACKGROUND

Telemedicine, the use of telecommunications to deliver health services, expertise and information, is a promising but unproven tool for improving the quality of diabetes care. We summarized the effectiveness of different methods of telemedicine for the management of diabetes compared with usual care.

METHODS

We searched MEDLINE, Embase and the Cochrane Central Register of Controlled Trials databases (to November 2015) and reference lists of existing systematic reviews for randomized controlled trials (RCTs) comparing telemedicine with usual care for adults with diabetes. Two independent reviewers selected the studies and assessed risk of bias in the studies. The primary outcome was glycated hemoglobin (HbA1C) reported at 3 time points (≤ 3 mo, 4-12 mo and > 12 mo). Other outcomes were quality of life, mortality and episodes of hypoglycemia. Trials were pooled using randomeffects meta-analysis, and heterogeneity was quantified using the I2 statistic.

RESULTS

From 3688 citations, we identified 111 eligible RCTs (n = 23 648). Telemedicine achieved significant but modest reductions in HbA1C in all 3 follow-up periods (difference in mean at ≤ 3 mo: -0.57%, 95% confidence interval [CI] -0.74% to -0.40% [39 trials]; at 4-12 mo: -0.28%, 95% CI -0.37% to -0.20% [87 trials]; and at > 12 mo: -0.26%, 95% CI -0.46% to -0.06% [5 trials]). Quantified heterogeneity (I2 statistic) was 75%, 69% and 58%, respectively. In meta-regression analyses, the effect of telemedicine on HbA1C appeared greatest in trials with higher HbA1C concentrations at baseline, in trials where providers used Web portals or text messaging to communicate with patients and in trials where telemedicine facilitated medication adjustment. Telemedicine had no convincing effect on quality of life, mortality or hypoglycemia.

INTERPRETATION

Compared with usual care, the addition of telemedicine, especially systems that allowed medication adjustments with or without text messaging or a Web portal, improved HbA1C but not other clinically relevant outcomes among patients with diabetes.

An Internet-based health gateway device for interactive communication and automatic data uploading: Clinical efficacy for type 2 diabetes in a multi-centre trial

Introduction The aim of this study was to improve the quality of diabetes control and evaluate the efficacy of an Internet-based integrated healthcare system for diabetes management and safety. Methods We conducted a large-scale, multi-centre, randomized clinical trial involving 484 patients. Patients in the intervention group ( n = 244) were treated with the Internet-based system for six months, while the control group ( n = 240) received the usual outpatient management over the same period. HbA1c, blood chemistries, anthropometric parameters, and adverse events were assessed at the beginning of the study, after three months, and the end of the study. Results There were no initial significant differences between the groups with respect to demographics and clinical parameters. Upon six-month follow-up, HbA1c levels were significantly decreased from 7.86 ± 0.69% to 7.55 ± 0.86% within the intervention group ( p < 0.001) compared to 7.81 ± 0.66% to 7.70 ± 0.88% within the control group. Postprandial glucose reduction was predominant. A subgroup with baseline HbA1c higher than 8% and good compliance achieved a reduction of HbA1c by 0.8 ± 1.05%. Glucose control and waist circumference reduction were more effective in females and subjects older than 40 years of age. There were no adverse events associated with the intervention. Discussion This e-healthcare system was effective for glucose control and body composition improvement without associated adverse events in a multi-centre trial. This system may be effective in improving diabetes control in the general population.

Current Clinical Status of Telehealth in Korea: Categories, Scientific Basis, and Obstacles

Objectives

Through telehealth, medical services have expanded beyond spatial boundaries and are now available in living spaces outside of hospitals. It can also contribute to patient medical knowledge improvement because patients can access their hospital records and data from home. However, concepts of telehealth are rather vague in Korea.

Methods

We refer to several clinical reports to determine the current clinical status of and obstacles to telehealth in Korea.

Results

Patients' health conditions are now reported regularly to doctors remotely, and patients can receive varied assistance. Self-improvement based on minute details that are beyond medical staff's reach is another possible benefit that may be realized with the help of a variety of medical equipment (sensors). The feasibility, clinical effect, and cost-benefit of telehealth have been verified by scientific evidence.

Conclusions

Patients will be able to improve their treatment adherence by receiving help from various professionals, such as doctors, nurses, nutritionists, and sports therapists. This means that the actual treatment time per patient will increase as well. Ultimately, this will increase the quality of patients' self-administration of care to impede disease progression and prevent complications.

Interactive telemedicine: effects on professional practice and health care outcomes

BACKGROUND

Telemedicine (TM) is the use of telecommunication systems to deliver health care at a distance. It has the potential to improve patient health outcomes, access to health care and reduce healthcare costs. As TM applications continue to evolve it is important to understand the impact TM might have on patients, healthcare professionals and the organisation of care.

OBJECTIVES

To assess the effectiveness, acceptability and costs of interactive TM as an alternative to, or in addition to, usual care (i.e. face-to-face care, or telephone consultation).

SEARCH METHODS

We searched the Effective Practice and Organisation of Care (EPOC) Group's specialised register, CENTRAL, MEDLINE, EMBASE, five other databases and two trials registers to June 2013, together with reference checking, citation searching, handsearching and contact with study authors to identify additional studies.

SELECTION CRITERIA

We considered randomised controlled trials of interactive TM that involved direct patient-provider interaction and was delivered in addition to, or substituting for, usual care compared with usual care alone, to participants with any clinical condition. We excluded telephone only interventions and wholly automatic self-management TM interventions.

DATA COLLECTION AND ANALYSIS

For each condition, we pooled outcome data that were sufficiently homogenous using fixed effect meta-analysis. We reported risk ratios (RR) and 95% confidence intervals (CI) for dichotomous outcomes, and mean differences (MD) for continuous outcomes.

MAIN RESULTS

We included 93 eligible trials (N = 22,047 participants), which evaluated the effectiveness of interactive TM delivered in addition to (32% of studies), as an alternative to (57% of studies), or partly substituted for usual care (11%) as compared to usual care alone.The included studies recruited patients with the following clinical conditions: cardiovascular disease (36), diabetes (21), respiratory conditions (9), mental health or substance abuse conditions (7), conditions requiring a specialist consultation (6), co morbidities (3), urogenital conditions (3), neurological injuries and conditions (2), gastrointestinal conditions (2), neonatal conditions requiring specialist care (2), solid organ transplantation (1), and cancer (1).Telemedicine provided remote monitoring (55 studies), or real-time video-conferencing (38 studies), which was used either alone or in combination. The main TM function varied depending on clinical condition, but fell typically into one of the following six categories, with some overlap: i) monitoring of a chronic condition to detect early signs of deterioration and prompt treatment and advice, (41); ii) provision of treatment or rehabilitation (12), for example the delivery of cognitive behavioural therapy, or incontinence training; iii) education and advice for self-management (23), for example nurses delivering education to patients with diabetes or providing support to parents of very low birth weight infants or to patients with home parenteral nutrition; iv) specialist consultations for diagnosis and treatment decisions (8), v) real-time assessment of clinical status, for example post-operative assessment after minor operation or follow-up after solid organ transplantation (8) vi), screening, for angina (1).The type of data transmitted by the patient, the frequency of data transfer, (e.g. telephone, e-mail, SMS) and frequency of interactions between patient and healthcare provider varied across studies, as did the type of healthcare provider/s and healthcare system involved in delivering the intervention.We found no difference between groups for all-cause mortality for patients with heart failure (16 studies; N = 5239; RR:0.89, 95% CI 0.76 to 1.03, P = 0.12; I(2) = 44%) (moderate to high certainty of evidence) at a median of six months follow-up. Admissions to hospital (11 studies; N = 4529) ranged from a decrease of 64% to an increase of 60% at median eight months follow-up (moderate certainty of evidence). We found some evidence of improved quality of life (five studies; N = 482; MD:-4.39, 95% CI -7.94 to -0.83; P < 0.02; I(2) = 0%) (moderate certainty of evidence) for those allocated to TM as compared with usual care at a median three months follow-up. In studies recruiting participants with diabetes (16 studies; N = 2768) we found lower glycated haemoglobin (HbA1c %) levels in those allocated to TM than in controls (MD -0.31, 95% CI -0.37 to -0.24; P < 0.00001; I(2)= 42%, P = 0.04) (high certainty of evidence) at a median of nine months follow-up. We found some evidence for a decrease in LDL (four studies, N = 1692; MD -12.45, 95% CI -14.23 to -10.68; P < 0.00001; I(2 =) 0%) (moderate certainty of evidence), and blood pressure (four studies, N = 1770: MD: SBP:-4.33, 95% CI -5.30 to -3.35, P < 0.00001; I(2) = 17%; DBP: -2.75 95% CI -3.28 to -2.22, P < 0.00001; I(2) = 45% (moderate certainty evidence), in TM as compared with usual care.Seven studies that recruited participants with different mental health and substance abuse problems, reported no differences in the effect of therapy delivered over video-conferencing, as compared to face-to-face delivery. Findings from the other studies were inconsistent; there was some evidence that monitoring via TM improved blood pressure control in participants with hypertension, and a few studies reported improved symptom scores for those with a respiratory condition. Studies recruiting participants requiring mental health services and those requiring specialist consultation for a dermatological condition reported no differences between groups.

AUTHORS' CONCLUSIONS

The findings in our review indicate that the use of TM in the management of heart failure appears to lead to similar health outcomes as face-to-face or telephone delivery of care; there is evidence that TM can improve the control of blood glucose in those with diabetes. The cost to a health service, and acceptability by patients and healthcare professionals, is not clear due to limited data reported for these outcomes. The effectiveness of TM may depend on a number of different factors, including those related to the study population e.g. the severity of the condition and the disease trajectory of the participants, the function of the intervention e.g., if it is used for monitoring a chronic condition, or to provide access to diagnostic services, as well as the healthcare provider and healthcare system involved in delivering the intervention.

Interactive telemedicine: effects on professional practice and health care outcomes

BACKGROUND

Telemedicine (TM) is the use of telecommunication systems to deliver health care at a distance. It has the potential to improve patient health outcomes, access to health care and reduce healthcare costs. As TM applications continue to evolve it is important to understand the impact TM might have on patients, healthcare professionals and the organisation of care.

OBJECTIVES

To assess the effectiveness, acceptability and costs of interactive TM as an alternative to, or in addition to, usual care (i.e. face-to-face care, or telephone consultation).

SEARCH METHODS

We searched the Effective Practice and Organisation of Care (EPOC) Group's specialised register, CENTRAL, MEDLINE, EMBASE, five other databases and two trials registers to June 2013, together with reference checking, citation searching, handsearching and contact with study authors to identify additional studies.

SELECTION CRITERIA

We considered randomised controlled trials of interactive TM that involved direct patient-provider interaction and was delivered in addition to, or substituting for, usual care compared with usual care alone, to participants with any clinical condition. We excluded telephone only interventions and wholly automatic self-management TM interventions.

DATA COLLECTION AND ANALYSIS

For each condition, we pooled outcome data that were sufficiently homogenous using fixed effect meta-analysis. We reported risk ratios (RR) and 95% confidence intervals (CI) for dichotomous outcomes, and mean differences (MD) for continuous outcomes.

MAIN RESULTS

We included 93 eligible trials (N = 22,047 participants), which evaluated the effectiveness of interactive TM delivered in addition to (32% of studies), as an alternative to (57% of studies), or partly substituted for usual care (11%) as compared to usual care alone.The included studies recruited patients with the following clinical conditions: cardiovascular disease (36), diabetes (21), respiratory conditions (9), mental health or substance abuse conditions (7), conditions requiring a specialist consultation (6), co morbidities (3), urogenital conditions (3), neurological injuries and conditions (2), gastrointestinal conditions (2), neonatal conditions requiring specialist care (2), solid organ transplantation (1), and cancer (1).Telemedicine provided remote monitoring (55 studies), or real-time video-conferencing (38 studies), which was used either alone or in combination. The main TM function varied depending on clinical condition, but fell typically into one of the following six categories, with some overlap: i) monitoring of a chronic condition to detect early signs of deterioration and prompt treatment and advice, (41); ii) provision of treatment or rehabilitation (12), for example the delivery of cognitive behavioural therapy, or incontinence training; iii) education and advice for self-management (23), for example nurses delivering education to patients with diabetes or providing support to parents of very low birth weight infants or to patients with home parenteral nutrition; iv) specialist consultations for diagnosis and treatment decisions (8), v) real-time assessment of clinical status, for example post-operative assessment after minor operation or follow-up after solid organ transplantation (8) vi), screening, for angina (1).The type of data transmitted by the patient, the frequency of data transfer, (e.g. telephone, e-mail, SMS) and frequency of interactions between patient and healthcare provider varied across studies, as did the type of healthcare provider/s and healthcare system involved in delivering the intervention.We found no difference between groups for all-cause mortality for patients with heart failure (16 studies; N = 5239; RR:0.89, 95% CI 0.76 to 1.03, P = 0.12; I(2) = 44%) (moderate to high certainty of evidence) at a median of six months follow-up. Admissions to hospital (11 studies; N = 4529) ranged from a decrease of 64% to an increase of 60% at median eight months follow-up (moderate certainty of evidence). We found some evidence of improved quality of life (five studies; N = 482; MD:-4.39, 95% CI -7.94 to -0.83; P < 0.02; I(2) = 0%) (moderate certainty of evidence) for those allocated to TM as compared with usual care at a median three months follow-up. In studies recruiting participants with diabetes (16 studies; N = 2768) we found lower glycated haemoglobin (HbA1c %) levels in those allocated to TM than in controls (MD -0.31, 95% CI -0.37 to -0.24; P < 0.00001; I(2)= 42%, P = 0.04) (high certainty of evidence) at a median of nine months follow-up. We found some evidence for a decrease in LDL (four studies, N = 1692; MD -12.45, 95% CI -14.23 to -10.68; P < 0.00001; I(2 =) 0%) (moderate certainty of evidence), and blood pressure (four studies, N = 1770: MD: SBP:-4.33, 95% CI -5.30 to -3.35, P < 0.00001; I(2) = 17%; DBP: -2.75 95% CI -3.28 to -2.22, P < 0.00001; I(2) = 45% (moderate certainty evidence), in TM as compared with usual care.Seven studies that recruited participants with different mental health and substance abuse problems, reported no differences in the effect of therapy delivered over video-conferencing, as compared to face-to-face delivery. Findings from the other studies were inconsistent; there was some evidence that monitoring via TM improved blood pressure control in participants with hypertension, and a few studies reported improved symptom scores for those with a respiratory condition. Studies recruiting participants requiring mental health services and those requiring specialist consultation for a dermatological condition reported no differences between groups.

AUTHORS' CONCLUSIONS

The findings in our review indicate that the use of TM in the management of heart failure appears to lead to similar health outcomes as face-to-face or telephone delivery of care; there is evidence that TM can improve the control of blood glucose in those with diabetes. The cost to a health service, and acceptability by patients and healthcare professionals, is not clear due to limited data reported for these outcomes. The effectiveness of TM may depend on a number of different factors, including those related to the study population e.g. the severity of the condition and the disease trajectory of the participants, the function of the intervention e.g., if it is used for monitoring a chronic condition, or to provide access to diagnostic services, as well as the healthcare provider and healthcare system involved in delivering the intervention.

New Directions in Chronic Disease Management

A worldwide epidemic of chronic disease, and complications thereof, is underway, with no sign of abatement. Healthcare costs have increased tremendously, principally because of the need to treat chronic complications of non-communicable diseases including cardiovascular disease, blindness, end-stage renal disease, and amputation of extremities. Current healthcare systems fail to provide an appropriate quality of care to prevent the development of chronic complications without additional healthcare costs. A new paradigm for prevention and treatment of chronic disease and the complications thereof is urgently required. Several clinical studies have clearly shown that frequent communication between physicians and patients, based on electronic data transmission from medical devices, greatly assists in the management of chronic disease. However, for various reasons, these advantages have not translated effectively into real clinical practice. In the present review, we describe current relevant studies, and trends in the use of information technology for chronic disease management. We also discuss limitations and future directions.

Efficacy of the smartphone-based glucose management application stratified by user satisfaction

BACKGROUND

We aimed to assess the efficacy of the smartphone-based health application for glucose control and patient satisfaction with the mobile network system used for glucose self-monitoring.

METHODS

Thirty-five patients were provided with a smartphone device, and self-measured blood glucose data were automatically transferred to the medical staff through the smartphone application over the course of 12 weeks. The smartphone user group was divided into two subgroups (more satisfied group vs. less satisfied group) based on the results of questionnaire surveys regarding satisfaction, comfort, convenience, and functionality, as well as their willingness to use the smartphone application in the future. The control group was set up via a review of electronic medical records by group matching in terms of age, sex, doctor in charge, and glycated hemoglobin (HbA1c).

RESULTS

Both the smartphone group and the control group showed a tendency towards a decrease in the HbA1c level after 3 months (7.7%±0.7% to 7.5%±0.7%, P=0.077). In the more satisfied group (n=27), the HbA1c level decreased from 7.7%±0.8% to 7.3%±0.6% (P=0.001), whereas in the less satisfied group (n=8), the HbA1c result increased from 7.7%±0.4% to 8.1%±0.5% (P=0.062), showing values much worse than that of the no-smartphone control group (from 7.7%±0.5% to 7.7%±0.7%, P=0.093).

CONCLUSION

In addition to medical feedback, device and network-related patient satisfaction play a crucial role in blood glucose management. Therefore, for the smartphone app-based blood glucose monitoring to be effective, it is essential to provide the patient with a well-functioning high quality tool capable of increasing patient satisfaction and willingness to use.

Future prospects of health management systems using cellular phones

BACKGROUND

Cellular phones enable communication between healthcare providers and patients for prevention, diagnosis, and treatment of diseases. However, few studies have examined the user-friendliness or effectiveness of cellular phone-based medical informatics (CPBMI) for healthcare.

MATERIALS AND METHODS

This study investigated the use of CPBMI to identify its current status within the medical field, advantages and disadvantages, practicability, clinical effectiveness, costs, and cost-saving potential.

RESULTS

CPBMI was validated in terms of practicality and provision of medical benefits. It is critical to use CPBMI in accordance with the different features of each disease and condition. Use of CPBMI is expected to be especially useful for patients with chronic disease.

CONCLUSIONS

We discussed the current status of the clinical use, benefits, and risks of CPBMI. CPBMI and information technology-based health management tools are anticipated to become useful and effective components of healthcare management in the future.

Continuous glucose monitoring: current clinical use

Four kinds of subcutaneous continuous glucose monitoring (CGM) machines have been currently introduced in clinical practice. These machines exhibit real-time glucose on the monitor every 5 minutes and have alarms to indicate hypoglycaemia and hyperglycaemia. However, thus far, there is no clear consensus about the clinical indications for CGM in actual clinical practice. CGM should be an ideal and powerful tool for monitoring glucose variability. Glycaemic variability has become a major concern over the years with growing evidence on its detrimental impact with respect to the risk of diabetic complications. Although the HbA1c level is ubiquitously measures in clinical practice, this level does not adequately represent glycaemic variability. Currently available evidence indicates that CGM aids in lowering the HbA1c level without increasing the incidence of severe hypoglycaemic episodes in patients with type 1 diabetes. Thus far, CGM has not been indicated for preventing severe hypoglycaemia or for treating type 2 diabetes because sufficient supporting evidence has not been obtained. Promising results have been obtained for the use of CGM for pregnant women with diabetes and for patients with hospital hyperglycaemia. Predictions regarding the feasibility of the closed-loop system have proven to be optimistic. CGM-integrated communication systems using information technology such as smart phone help controlling blood glucose more easily and effectively.