The Karlsburg Diabetes Management System: translation from research to eHealth application

Patient-Tailored Decision Support System Improves Short- and Long-Term Glycemic Control in Type 2 Diabetes

BACKGROUND

The increasing prevalence of type 2 diabetes mellitus (T2D) and specialist shortage has caused a healthcare gap that can be bridged by a decision support system (DSS). We investigated whether a diabetes DSS can improve long- and/or short-term glycemic control.

METHODS

This is a retrospective observational cohort study of the Diabetiva program, which offered a patient-tailored DSS using Karlsburger Diabetes-Management System (KADIS) once a year. Glycemic control was analyzed at baseline and after 12 months in 452 individuals with T2D. Time in range (TIR; glucose 3.9-10 mmol/L) and Q-Score, a composite metric developed for analysis of continuous glucose profiles, were short-term and HbA1c long-term measures of glycemic control. Glucose variability (GV) was also measured.

RESULTS

At baseline, one-third of patients had good short- and long-term glycemic control. Q-Score identified insufficient short-term glycemic control in 17.9% of patients with HbA1c <6.5%, mainly due to hypoglycemia. GV and hyperglycemia were responsible in patients with HbA1c >7.5% and >8%, respectively. Application of DSS at baseline improved short- and long-term glycemic control, as shown by the reduced Q-Score, GV, and HbA1c after 12 months. Multiple regression demonstrated that the total effect on GV resulted from the single effects of all influential parameters.

CONCLUSIONS

DSS can improve short- and long-term glycemic control in individuals with T2D without increasing hypoglycemia. The Q-Score allows identification of individuals with insufficient glycemic control. An effective strategy for therapy optimization could be the selection of individuals with T2D most at need using the Q-Score, followed by offering patient-tailored DSS.

Stratification of Patients with Diabetes Using Continuous Glucose Monitoring Profiles and Machine Learning

Background. Continuous glucose monitoring (CGM) offers an opportunity for patients with diabetes to modify their lifestyle to better manage their condition and for clinicians to provide personalized healthcare and lifestyle advice. However, analytic tools are needed to standardize and analyze the rich data that emerge from CGM devices. This would allow glucotypes of patients to be identified to aid clinical decision-making.Methods. In this paper, we develop an analysis pipeline for CGM data and apply it to 148 diabetic patients with a total of 8632 days of follow up. The pipeline projects CGM data to a lower-dimensional space of features representing centrality, spread, size, and duration of glycemic excursions and the circadian cycle. We then use principal components analysis and k -means to cluster patients' records into one of four glucotypes and analyze cluster membership using multinomial logistic regression.Results. Glucotypes differ in the degree of control, amount of time spent in range, and on the presence and timing of hyper- and hypoglycemia. Patients on the program had statistically significant improvements in their glucose levels.Conclusions. This pipeline provides a fast automatic function to label raw CGM data without manual input.

Economic evaluations of big data analytics for clinical decision-making: a scoping review

OBJECTIVE

Much has been invested in big data analytics to improve health and reduce costs. However, it is unknown whether these investments have achieved the desired goals. We performed a scoping review to determine the health and economic impact of big data analytics for clinical decision-making.

MATERIALS AND METHODS

We searched Medline, Embase, Web of Science and the National Health Services Economic Evaluations Database for relevant articles. We included peer-reviewed papers that report the health economic impact of analytics that assist clinical decision-making. We extracted the economic methods and estimated impact and also assessed the quality of the methods used. In addition, we estimated how many studies assessed "big data analytics" based on a broad definition of this term.

RESULTS

The search yielded 12 133 papers but only 71 studies fulfilled all eligibility criteria. Only a few papers were full economic evaluations; many were performed during development. Papers frequently reported savings for healthcare payers but only 20% also included costs of analytics. Twenty studies examined "big data analytics" and only 7 reported both cost-savings and better outcomes.

DISCUSSION

The promised potential of big data is not yet reflected in the literature, partly since only a few full and properly performed economic evaluations have been published. This and the lack of a clear definition of "big data" limit policy makers and healthcare professionals from determining which big data initiatives are worth implementing.

Identifying and managing osteoporosis before and after COVID-19: rise of the remote consultation?

The COVID-19 pandemic is influencing methods of healthcare delivery. In this short review, we discuss the evidence for remote healthcare delivery in the context of osteoporosis.

INTRODUCTION

The COVID-19 pandemic has undoubtedly had, and will continue to have, a significant impact on the lives of people living with, and at risk of, osteoporosis and those caring for them. With osteoporosis outpatient and Fracture Liaison Services on pause, healthcare organisations have already moved to delivering new and follow-up consultations remotely, where staffing permits, by telephone or video.

METHODS

In this review, we consider different models of remote care delivery, the evidence for their use, and the possible implications of COVID-19 on osteoporosis services.

RESULTS

Telemedicine is a global term used to describe any use of telecommunication systems to deliver healthcare from a distance and encompasses a range of different scenarios from remote clinical data transfer to remote clinician-patient interactions. Across a range of conditions and contexts, there remains unclear evidence on the acceptability of telemedicine and the effect on healthcare costs. Within the context of osteoporosis management, there is some limited evidence to suggest telemedicine approaches are acceptable to patients but unclear evidence on whether telemedicine approaches support informed drug adherence. Gaps in the evidence pertain to the acceptability and benefits of using telemedicine in populations with hearing, cognitive, or visual impairments and in those with limited health literacy.

CONCLUSION

There is an urgent need for further health service evaluation and research to address the impact of remote healthcare delivery during COVID-19 outbreak on patient care, and in the longer term, to identify acceptability and cost- and clinical-effectiveness of remote care delivery on outcomes of relevance to people living with osteoporosis.

Cost and cost-effectiveness of mHealth interventions for the prevention and control of type 2 diabetes mellitus: A systematic review

The prevalence of type 2 diabetes mellitus continues to rise and simultaneously technology has contributed to the growth of MHealth interventions for its prevention, monitoring and management. This systematic review aimed to summarize and evaluate the quality of the published evidence on cost and cost-effectiveness of mHealth interventions for T2DM. A systematic literature search of PubMed, EMBASE, and Web of Science was conducted for papers up to end of April 2019. We included all partial or full economic evaluations providing cost or cost-effectiveness results for mHealth interventions targeting individuals diagnosed with, or at risk of, type 2 diabetes mellitus. Twenty-three studies met the inclusion criteria. Intervention cost varied substantially based on the type and numbers or combination of technologies used, ranging from 1.8 INT $ to 10101.1 INT $ per patient per year. The studies which presented cost effectiveness results demonstrated highly cost-effective interventions, with cost per QALY gained ranging from 0.4 to 62.5 percent of GDP per capita of the country. The quality of partial economic evaluations was on average lower than that of full economic evaluations. Cost of mHealth interventions varied substantially based on type and combination of technology used, however, where cost-effectiveness results were reported, the intervention was cost-effective. PROSPERO registration number: CRD42019123476; Registered: 27/01/2019.

Model-Based Tool for Personalized Adjustment of Basal Insulin Supply in Patients With Intensified Conventional Insulin Therapy

BACKGROUND

The decisive factor in successful intensive insulin therapy is the ability to deliver need-based-adjusted nutrition-independent insulin dosages at the closest possible approximation to the physiological insulin level. Because this basal insulin requirement is strongly influenced by the patient's lifestyle, its subtlety is of great importance. This challenge is very different between patients with type 1 diabetes and those with insulin-dependent type 2 diabetes. Furthermore, it is more difficult to finetune a basal insulin dosage with intensified conventional insulin therapy (ICT), due to delayed insulin delivery, compared to insulin pump therapy, which provides continuous delivery of small doses of exclusively short-acting insulin. In all cases, the goal is to achieve an optimal basal delivery rate.

METHOD

We hypothesized that this goal could be achieved with a modeling tool that determined the optimal basal insulin supply based on the patient's anamnestic data and monitored glucose values. This type of modeling tool has been used in health insurance programs in Germany to improve insulin control in patients that receive ICT.

RESULTS

Our retrospective data analysis showed that this modeling tool provided a significant improvement in metabolic control, significant reductions in HbA1c and Q scores, and improved time-in-range values, with reduced daily insulin levels.

CONCLUSION

The model-based basal rate test could provide additional data of the actual effect of the basal insulin adjustment in intensified insulin treated diabetes to the physician or treatment team.

Continuous Glucose Monitoring: Current Use in Diabetes Management and Possible Future Applications

The recent announcement of the production of new low-cost continuous glucose monitoring (CGM) sensors, the approval of marketed CGM sensors for making treatment decisions, and new reimbursement criteria have the potential to revolutionize CGM use. After briefly summarizing current CGM applications, we discuss how, in our opinion, these changes are expected to extend CGM utilization beyond diabetes patients, for example, to subjects with prediabetes or even healthy individuals. We also elaborate on how the integration of CGM data with other relevant information, for example, health records and other medical device/wearable sensor data, will contribute to creating a digital data ecosystem that will improve our understanding of the etiology and complications of diabetes and will facilitate the development of data analytics for personalized diabetes management and prevention.

The impact of telehealth remote patient monitoring on glycemic control in type 2 diabetes: a systematic review and meta-analysis of systematic reviews of randomised controlled trials

Background

There is a growing body of evidence to support the use of telehealth in monitoring HbA1c levels in people living with type 2 diabetes. However, the overall magnitude of effect is yet unclear due to variable results reported in existing systematic reviews. The objective of this study is to conduct a systematic review and meta-analysis of systematic reviews of randomised controlled trials to create an evidence-base for the effectiveness of telehealth interventions on glycemic control in adults with type 2 diabetes.

Methods

Electronic databases including The Cochrane Library, MEDLINE, EMBASE, HMIC, and PsychINFO were searched to identify relevant systematic reviews published between 1990 and April 2016, supplemented by references search from the relevant reviews. Two independent reviewers selected and reviewed the eligible studies. Of the 3279 references retrieved, 4 systematic reviews reporting in total 29 unique studies relevant to our review were included. Both conventional pairwise meta-analyses and network meta-analyses were performed.

Results

Evidence from pooling four systematic reviews found that telehealth interventions produced a small but significant improvement in HbA1c levels compared with usual care (MD: -0.55, 95% CI: -0.73 to − 0.36). The greatest effect was seen in telephone-delivered interventions, followed by Internet blood glucose monitoring system interventions and lastly interventions involving automatic transmission of SMBG using a mobile phone or a telehealth unit.

Conclusion

Current evidence suggests that telehealth is effective in controlling HbA1c levels in people living with type 2 diabetes. However there is need for better quality primary studies as well as systematic reviews of RCTs in order to confidently conclude on the impact of telehealth on glycemic control in type 2 diabetes.

Electronic supplementary material

The online version of this article (10.1186/s12913-018-3274-8) contains supplementary material, which is available to authorized users.

Economic evaluation of chronic disease self-management for people with diabetes: a systematic review

AIMS

To systematically review the evidence on the costs and cost-effectiveness of self-management support interventions for people with diabetes.

BACKGROUND

Self-management support is the provision of education and supportive interventions to increase patients' skills and confidence in managing their health problems, potentially leading to improvements in HbA_1c levels in people with diabetes.

METHODS

Randomized controlled trials, observational studies or economic modelling studies were eligible for inclusion in the review. The target population was adults with diabetes. Interventions had to have a substantial component of self-management support and be compared with routine care. Study quality was evaluated using the Consensus on Health Economic Criteria and International Society of Pharmacoeconomic Outcomes Research questionnaires. A narrative review approach was used.

RESULTS

A total of 16 costing and 21 cost-effectiveness studies of a range of self-management support interventions were identified. There was reasonably consistent evidence across 22 studies evaluating education self-management support programmes suggesting these interventions are cost-effective or superior to usual care. Telemedicine-type interventions were more expensive than usual care and potentially not cost-effective. There was insufficient evidence regarding the other types of self-management interventions, including pharmacist-led and behavioural interventions. The identified studies were predominantly of poor quality, with outcomes based on short-term follow-up data and study designs at high risk of bias.

CONCLUSIONS

Self-management support education programmes may be cost-effective. There was limited evidence regarding other formats of self-management support interventions. The poor quality of many of the studies undermines the evidence base regarding the economic efficiency of self-management support interventions for people with diabetes.

Does nutritional counseling in telemedicine improve treatment outcomes for diabetes? A systematic review and meta-analysis of results from 92 studies

BACKGROUND

A growing number of studies and reviews have documented the impact of telemedicine on diabetes management. However, no meta-analysis has assessed whether including nutritional counseling as part of a telemedicine program has a significant impact on diabetes outcomes or what kind of nutritional counseling is most effective.

METHODS

Original research articles examining the effect of telemedicine interventions on HbA1c levels in patients with Type 1 or Type 2 diabetes were included in this study. A literature search was performed and 92 studies were retained for analysis. We examined stratified results by differentiating interventions using no nutritional counseling from those that used nutritional counseling. We further compared between nutritional counseling administered via short message systems (SMS) such as email and text messages, and nutritional counseling administered via telephone or videoconference.

RESULTS

Telemedicine programs that include a nutritional component show similar effect in diabetes management as those programs that do not. Furthermore, subgroup analysis reveals that nutritional intervention via SMS such as email and text messages is at least as equally effective in reducing HbA1c when compared to personal nutritional counseling with a practitioner over videoconference or telephone.

CONCLUSION

The inclusion of nutritional counseling as part of a telemedicine program does not make a significant difference to diabetes outcomes. Incorporating nutritional counseling into telemedicine programs via SMS is at least as effective as counseling via telephone or videoconference.

Managing diabetes mellitus using information technology: a systematic review

Objective

To review published evidences about using information technology interventions in diabetes care and determine their effects on managing diabetes.

Design

Systematic review of information technology based interventions.

Research design and methods

MEDLINE®/PubMed were electronically searched for articles published between 2004/07/01 and 2014/07/01. A comprehensive, electronic search strategy was used to identify eligible articles.

Inclusion criteria were defined based on type of study and effect of information technology based intervention in relation to glucose control and other clinical outcomes in diabetic patients. Studies must have used a controlled design to evaluate an information technology based intervention.

A total of 3613 articles were identified based on the searches conducted in MEDLINE from PubMed. After excluding duplicates (n = 6), we screened titles and abstracts of 3607 articles based on inclusion criteria. The remaining articles matched with inclusion criteria (n = 277) were reviewed in full text, and 210 articles were excluded based on exclusion criteria. Finally, 67 articles complied with our eligibility criteria and were included in this study.

Results

In this study, the effect of various information technology based interventions on clinical outcomes in diabetic patients extracted and measured from selected articles is described and compared to each other.

Conclusion

Information technology based interventions combined with the usual care are associated with improved glycemic control with different efficacy on various clinical outcomes in diabetic patients.

The empirical evidence for the telemedicine intervention in diabetes management

OBJECTIVE

The research presented here assesses the scientific evidence for the telemedicine intervention in the management of diabetes (telediabetes), gestational diabetes, and diabetic retinopathy. The impetus derives from the confluence of high prevalence of these diseases, increasing incidence, and rising costs, while telemedicine promises to ameliorate, if not prevent, type 2 diabetes and its complications.

MATERIALS AND METHODS

A purposeful review of the literature identified relevant publications from January 2005 to December 2013. These were culled to retain only credible research articles for detailed review and analysis. The search yielded approximately 17,000 articles with no date constraints. Of these, 770 appeared to be research articles within our time frame. A review of the abstracts yielded 73 articles that met the criteria for inclusion in the final analysis. Evidence is organized by research findings regarding feasibility/acceptance, intermediate outcomes (e.g., use of service, and screening compliance), and health outcomes (control of glycemic level, lipids, body weight, and physical activity.)

RESULTS

Definitions of telediabetes varied from study to study vis-à-vis diabetes subtype, setting, technology, staffing, duration, frequency, and target population. Outcome measures also varied. Despite these vagaries, sufficient evidence was obtained from a wide variety of research studies, consistently pointing to positive effects of telemonitoring and telescreening in terms of glycemic control, reduced body weight, and increased physical exercise. The major contributions point to telemedicine's potential for changing behaviors important to diabetes control and prevention, especially type 2 and gestational diabetes. Similarly, screening and monitoring for retinopathy can detect symptoms early that may be controlled or treated.

CONCLUSIONS

Overall, there is strong and consistent evidence of improved glycemic control among persons with type 2 and gestational diabetes as well as effective screening and monitoring of diabetic retinopathy.

Q-Score: development of a new metric for continuous glucose monitoring that enables stratification of antihyperglycaemic therapies

BACKGROUND

Continuous glucose monitoring (CGM) has revolutionised diabetes management. CGM enables complete visualisation of the glucose profile, and the uncovering of metabolic 'weak points'. A standardised procedure to evaluate the complex data acquired by CGM, and to create patient-tailored recommendations has not yet been developed. We aimed to develop a new patient-tailored approach for the routine clinical evaluation of CGM profiles. We developed a metric allowing screening for profiles that require therapeutic action and a method to identify the individual CGM parameters with improvement potential.

METHODS

Fifteen parameters frequently used to assess CGM profiles were calculated for 1,562 historic CGM profiles from subjects with type 1 or type 2 diabetes. Factor analysis and varimax rotation was performed to identify factors that accounted for the quality of the profiles.

RESULTS

We identified five primary factors that determined CGM profiles (central tendency, hyperglycaemia, hypoglycaemia, intra- and inter-daily variations). One parameter from each factor was selected for constructing the formula for the screening metric, (the 'Q-Score'). To derive Q-Score classifications, three diabetes specialists independently categorised 766 CGM profiles into groups of 'very good', 'good', 'satisfactory', 'fair', and 'poor' metabolic control. The Q-Score was then calculated for all profiles, and limits were defined based on the categorised groups (<4.0, very good; 4.0-5.9, good; 6.0-8.4, satisfactory; 8.5-11.9, fair; and ≥12.0, poor). Q-Scores increased significantly (P <0.01) with increasing antihyperglycaemic therapy complexity. Accordingly, the percentage of fair and poor profiles was higher in insulin-treated compared with diet-treated subjects (58.4% vs. 9.3%). In total, 90% of profiles categorised as fair or poor had at least three parameters that could potentially be optimised. The improvement potential of those parameters can be categorised as 'low', 'moderate' and 'high'.

CONCLUSIONS

The Q-Score is a new metric suitable to screen for CGM profiles that require therapeutic action. Moreover, because single components of the Q-Score formula respond to individual weak points in glycaemic control, parameters with improvement potential can be identified and used as targets for optimising patient-tailored therapies.

Management of endocrine disease. Effects of telecare intervention on glycemic control in type 2 diabetes: a systematic review and meta-analysis of randomized controlled trials

OBJECTIVE

To review the published literature on the effects of telecare intervention in patients with type 2 diabetes and inadequate glycemic control.

DESIGN AND METHODS

A review of randomized controlled trials on telecare intervention in patients with type 2 diabetes, and a search of electronic databases such as The Cochrane Library, PubMed, EBSCO, CINAHL, Science Direct, Journal of Telemedicine and Telecare, and China National Knowledge Infrastructure (CNKI), were conducted from December 8 to 16, 2013. Two evaluators independently selected and reviewed the eligible studies. Changes in HbA1c, fasting plasma glucose (FPG), post-prandial plasma glucose (PPG), BMI, and body weight were analyzed.

RESULTS

An analysis of 18 studies with 3798 subjects revealed that telecare significantly improved the management of diabetes. Mean HbA1c values were reduced by -0.54 (95% CI, -0.75 to -0.34; P<0.05), mean FPG levels by -9.00 mg/dl (95% CI, -17.36 to -0.64; P=0.03), and mean PPG levels reduced by -52.86 mg/dl (95% CI, -77.13 to -28.58; P<0.05) when compared with the group receiving standard care. Meta-regression and subgroup analyses indicated that study location, sample size, and treatment-monitoring techniques were the sources of heterogeneity.

CONCLUSIONS

Patients monitored by telecare showed significant improvement in glycemic control in type 2 diabetes when compared with those monitored by routine follow-up. Significant reduction in HbA1c levels was associated with Asian populations, small sample size, and telecare, and with those patients with baseline HbA1c greater than 8.0%.

A physiology-based model describing heterogeneity in glucose metabolism: the core of the Eindhoven Diabetes Education Simulator (E-DES)

Current diabetes education methods are costly, time-consuming, and do not actively engage the patient. Here, we describe the development and verification of the physiological model for healthy subjects that forms the basis of the Eindhoven Diabetes Education Simulator (E-DES). E-DES shall provide diabetes patients with an individualized virtual practice environment incorporating the main factors that influence glycemic control: food, exercise, and medication. The physiological model consists of 4 compartments for which the inflow and outflow of glucose and insulin are calculated using 6 nonlinear coupled differential equations and 14 parameters. These parameters are estimated on 12 sets of oral glucose tolerance test (OGTT) data (226 healthy subjects) obtained from literature. The resulting parameter set is verified on 8 separate literature OGTT data sets (229 subjects). The model is considered verified if 95% of the glucose data points lie within an acceptance range of ±20% of the corresponding model value. All glucose data points of the verification data sets lie within the predefined acceptance range. Physiological processes represented in the model include insulin resistance and β-cell function. Adjusting the corresponding parameters allows to describe heterogeneity in the data and shows the capabilities of this model for individualization. We have verified the physiological model of the E-DES for healthy subjects. Heterogeneity of the data has successfully been modeled by adjusting the 4 parameters describing insulin resistance and β-cell function. Our model will form the basis of a simulator providing individualized education on glucose control.

How Do Interventions That Exemplify the Joint Principles of the Patient Centered Medical Home Affect Hemoglobin A1C in Patients With Diabetes: A Review

Objective:

To review the impact of the Joint Principle of the Patient Centered Medical Home (PCMH) on hemoglobin A1C (HbA1C) in primary care patients with diabetes.

Methods:

Systematic review of English articles using approximate terms for (1) the 7 principles of the PCMH, (2) primary care, and (3) HbA1C. We included experimental and observational studies. Three authors independently extracted data and obtained summary estimates for concepts with more than 2 high-quality studies.

Results:

Forty-three studies published between 1998 and 2012 met inclusion criteria, 33 randomized and 10 controlled before–after studies. A physician-directed medical practice (principle 2) lowered HbA1C values when utilizing nursing (mean difference [MD] −0.36, 95% confidence interval [CI] −0.43 to −0.28) or pharmacy care management (MD −0.76; 95% CI −0.93 to −0.59). Whole-person orientation (principle 3) also lowered HbA1C (MD −0.72, 95% CI −0.98 to −0.45). Studies of coordinated and integrated care (principle 4) and quality and safety interventions (principle 5) did not consistently lower HbA1C when reviewed in aggregate. We did not identify high-quality studies to make conclusions for personal physician (principle 1), enhanced access (principle 6), and payment (principle 7).

Conclusion:

Our review found individual interventions that reduced the HbA1C by up to 2.0% when they met the definitions set by of the Joint Principles of the PCMH. Two of the principles—physician-led team and whole-person orientation—consistently lowered the HbA1C. Other principles had limited data or made little to no impact. Based on current evidence, PCMH principles differentially influence the HbA1C, and there are opportunities for additional research.

The empirical foundations of telemedicine interventions for chronic disease management

The telemedicine intervention in chronic disease management promises to involve patients in their own care, provides continuous monitoring by their healthcare providers, identifies early symptoms, and responds promptly to exacerbations in their illnesses. This review set out to establish the evidence from the available literature on the impact of telemedicine for the management of three chronic diseases: congestive heart failure, stroke, and chronic obstructive pulmonary disease. By design, the review focuses on a limited set of representative chronic diseases because of their current and increasing importance relative to their prevalence, associated morbidity, mortality, and cost. Furthermore, these three diseases are amenable to timely interventions and secondary prevention through telemonitoring. The preponderance of evidence from studies using rigorous research methods points to beneficial results from telemonitoring in its various manifestations, albeit with a few exceptions. Generally, the benefits include reductions in use of service: hospital admissions/re-admissions, length of hospital stay, and emergency department visits typically declined. It is important that there often were reductions in mortality. Few studies reported neutral or mixed findings.

What we can really expect from telemedicine in intensive diabetes treatment: 10 years later

During the last 10 years many new telematic systems aiming at support of diabetes treatment have been designed and developed. Most systems that were applied in clinical randomized trials used the classical approach, with data transfers from patients performed usually once every few days. In the few available meta-analyses of these trials, a significant improvement of the mean hemoglobin A1c was demonstrated in patients using telematic systems. However, the magnitude of this improvement in comparison with the control groups was lower than expected. This conclusion was confirmed by results of the IDEATel study involving more than 1,600 patients over a period of 5 years. It might by hypothesized that in some groups of patients continuous telecare with frequent contacts between patients and the care provider during each day should be required. This hypothesis is confirmed by the results of the clinical trials applying real-time diabetes monitoring systems. However, the increased frequency of the data transfers and checkups requires a new model for technology-supported care. The new model should connect together the ubiquitous data transfer with an automatically selected optimal frequency, the automatic assessment of the data coupled with quicker feedback from the decision support system or from the provider, and selection of the optimal time for the patient's face-to-face visit in the clinic. All this new future implementations together with already confirmed advantages of the telematic support, such as the increase of self-confidence of the patient, will hopefully give real benefits for the patients.

Telemedicine and telecare for older patients--a systematic review

Telemedicine is increasingly becoming a reality in medical care for the elderly. We performed a systematic literature review on telemedicine healthcare concepts for older patients. We included controlled studies in an ambulant setting that analyzed telemedicine interventions involving patients aged ≥60 years. 1585 articles matched the specified search criteria, thereof, 68 could be included in the review. Applications address an array of mostly frequent diseases, e.g. cardiovascular disease (N=37) or diabetes (N=18). The majority of patients is still living at home and is able to handle the telemedicine devices by themselves. In 59 of 68 articles (87%), the intervention can be categorized as monitoring. The largest proportion of telemedicine interventions consisted of measurements of vital signs combined with personal interaction between healthcare provider and patient (N=24), and concepts with only personal interaction (telephone or videoconferencing, N=14). The studies show predominantly positive results with a clear trend towards better results for "behavioral" endpoints, e.g. adherence to medication or diet, and self-efficacy compared to results for medical outcomes (e.g. blood pressure, or mortality), quality of life, and economic outcomes (e.g. costs or hospitalization). However, in 26 of 68 included studies, patients with characteristic limitations for older patients (e.g. cognitive and visual impairment, communication barriers, hearing problems) were excluded. A considerable number of projects use rather sophisticated technology (e.g. videoconferencing), limiting ready translation into routine care. Future research should focus on how to adapt systems to the individual needs and resources of elderly patients within the specific frameworks of the respective national healthcare systems.