Pan-European Economic Analysis to Identify Cost Savings for the Health Care Systems as a Result of Integrating Glucose Monitoring Based Telemedical Approaches Into Diabetes Management

Economic Evaluations of mHealth Interventions for the Management of Type 2 Diabetes: A Scoping Review

BACKGROUND

There is plenty of evidence supporting the clinical benefits of mHealth interventions for type 2 diabetes, but despite often being promoted as cost-effective or cost-saving, there is still limited research to support such claims. The objective of this review was to summarize and critically analyze the current body of economic evaluation (EE) studies for mHealth interventions for type 2 diabetes.

METHODS

Using a comprehensive search strategy, five databases were searched for full and partial EE studies for mHealth interventions for type 2 diabetes from January 2007 to March 2022. "mHealth" was defined as any intervention that used a mobile device with cellular technology to collect and/or provide data or information for the management of type 2 diabetes. The CHEERS 2022 checklist was used to appraise the reporting of the full EEs.

RESULTS

Twelve studies were included in the review; nine full and three partial evaluations. Text messages smartphone applications were the most common mHealth features. The majority of interventions also included a Bluetooth-connected medical device, eg, glucose or blood pressure monitors. All studies reported their intervention to be cost-effective or cost-saving, however, most studies' reporting were of moderate quality with a median CHEERS score of 59%.

CONCLUSION

The current literature indicates that mHealth interventions for type 2 diabetes can be cost-saving or cost-effective, however, the quality of the reporting can be substantially improved. Heterogeneity makes it difficult to compare study outcomes, and the failure to report on key items leaves insufficient information for decision-makers to consider.

Evaluation of an mHealth-enabled hierarchical diabetes management intervention in primary care in China (ROADMAP): A cluster randomized trial

BACKGROUND

Glycemic control remains suboptimal in developing countries due to critical system deficiencies. An innovative mobile health (mHealth)-enabled hierarchical diabetes management intervention was introduced and evaluated in China with the purpose of achieving better control of type 2 diabetes in primary care.

METHODS AND FINDINGS

A community-based cluster randomized controlled trial was conducted among registered patients with type 2 diabetes in primary care from June 2017 to July 2019. A total of 19,601 participants were recruited from 864 communities (clusters) across 25 provinces in China, and 19,546 completed baseline assessment. Moreover, 576 communities (13,037 participants) were centrally randomized to the intervention and 288 communities (6,509 participants) to usual care. The intervention was centered on a tiered care team-delivered mHealth-mediated service package, initiated by monthly blood glucose monitoring at each structured clinic visit. Capacity building and quarterly performance review strategies upheld the quality of delivered primary care. The primary outcome was control of glycated hemoglobin (HbA1c; <7.0%), assessed at baseline and 12 months. The secondary outcomes include the individual/combined control rates of blood glucose, blood pressure (BP), and low-density lipoprotein cholesterol (LDL-C); changes in levels of HbA1c, BP, LDL-C, fasting blood glucose (FBG), and body weight; and episodes of hypoglycemia. Data were analyzed using intention-to-treat (ITT) generalized estimating equation (GEE) models, accounting for clustering and baseline values of the analyzed outcomes. After 1-year follow-up, 17,554 participants (89.8%) completed the end-of-study (EOS) assessment, with 45.1% of them from economically developed areas, 49.9% from urban areas, 60.5 (standard deviation [SD] 8.4) years of age, 41.2% male, 6.0 years of median diabetes duration, HbA1c level of 7.87% (SD 1.92%), and 37.3% with HbA1c <7.0% at baseline. Compared with usual care, the intervention led to an absolute improvement in the HbA1c control rate of 7.0% (95% confidence interval [CI] 4.0% to 10.0%) and a relative improvement of 18.6% (relative risk [RR] 1.186, 95% CI 1.105 to 1.267) and an absolute improvement in the composite ABC control (HbA1c <7.0%, BP <140/80 mm Hg, and LDL-C <2.6 mmol/L) rate of 1.9% (95% CI 0.5 to 3.5) and a relative improvement of 21.8% (RR 1.218, 95% CI 1.062 to 1.395). No difference was found on hypoglycemia episode and weight gain between groups. Study limitations include noncentralized laboratory tests except for HbA1c, and caution should be exercised when extrapolating the findings to patients not registered in primary care system.

CONCLUSIONS

The mHealth-enabled hierarchical diabetes management intervention effectively improved diabetes control in primary care and has the potential to be transferred to other chronic conditions management in similar contexts.

TRIAL REGISTRATION

Chinese Clinical Trial Registry (ChiCTR) IOC-17011325.

Efficacy of telemedicine on glycaemic control in patients with type 2 diabetes: A meta-analysis

BACKGROUND

Telemedicine is defined as the delivery of health services via remote communication and technology. It is a convenient and cost-effective method of intervention, which has shown to be successful in improving glyceamic control for type 2 diabetes patients. The utility of a successful diabetes intervention is vital to reduce disease complications, hospital admissions and associated economic costs.

AIM

To evaluate the effects of telemedicine interventions on hemoglobin A1c (HbA1c), systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), post-prandial glucose (PPG), fasting plasma glucose (FPG), weight, cholesterol, mental and physical quality of life (QoL) in patients with type 2 diabetes. The secondary aim of this study is to determine the effect of the following subgroups on HbA1c post-telemedicine intervention; telemedicine characteristics, patient characteristics and self-care outcomes.

METHODS

PubMed Central, Cochrane Library, Embase and Scopus databases were searched from inception until 18^th of June 2020. The quality of the 43 included studies were assessed using the PEDro scale, and the random effects model was used to estimate outcomes and I² for heterogeneity testing. The mean difference and standard deviation data were extracted for analysis.

RESULTS

We found a significant reduction in HbA1c [-0.486%; 95% confidence interval (CI) -0.561 to -0.410, P < 0.001], DBP (-0.875 mmHg; 95%CI -1.429 to -0.321, P < 0.01), PPG (-1.458 mmol/L; 95%CI -2.648 to -0.268, P < 0.01), FPG (-0.577 mmol/L; 95%CI -0.710 to -0.443, P < 0.001), weight (-0.243 kg; 95%CI -0.442 to -0.045, P < 0.05), BMI (-0.304; 95%CI -0.563 to -0.045, P < 0.05), mental QoL (2.210; 95%CI 0.053 to 4.367, P < 0.05) and physical QoL (-1.312; 95%CI 0.545 to 2.080, P < 0.001) for patients following telemedicine interventions in comparison to control groups. The results of the meta-analysis did not show any significant reductions in SBP and cholesterol in the telemedicine interventions compared to the control groups. The telemedicine characteristic subgroup analysis revealed that clinical treatment models of intervention, as well as those involving telemonitoring, and those provided via modes of videoconference or interactive telephone had the greatest effect on HbA1c reduction. In addition, interventions delivered at a less than weekly frequency, as well as those given for a duration of 6 mo, and those lead by allied health resulted in better HbA1c outcomes. Furthermore, interventions with a focus on biomedical parameters, as well as those with an engagement level > 70% and those with a drop-out rate of 10%-19.9% showed greatest HbA1c reduction. The patient characteristics investigation reported that Hispanic patients with T2DM had a greater HbA1c reduction post telemedicine intervention. For self-care outcomes, telemedicine interventions that resulted in higher post-intervention glucose monitoring and self-efficacy were shown to have better HbA1c reduction.

CONCLUSION

The findings indicate that telemedicine is effective for improving HbA1c and thus, glycemic control in patients with type 2 diabetes. In addition, telemedicine interventions were also found to significantly improved other health outcomes as well as QoL scores. The results of the subgroup analysis emphasized that interventions in the form of telemonitoring, via a clinical treatment model and with a focus on biomedical parameters, delivered at a less than weekly frequency and 6 mo duration would have the largest effect on HbA1c reduction. This is in addition to being led by allied health, through modes such as video conference and interactive telephone, with an intervention engagement level > 70% and a drop-out rate between 10%-19.9%. Due to the high heterogeneity of included studies and limitations, further studies with a larger sample size is needed to confirm our findings.

Costs and its drivers for diabetes mellitus type 2 patients in France and Germany: a systematic review of economic studies

BACKGROUND

Type 2 diabetes represents an increasingly critical challenge for health policy worldwide. It absorbs massive resources from both patients and national economies to sustain direct costs of the treatment of type 2 diabetes and its complications and indirect costs related to work loss and wages. More recently, there are innovations based on remote control and personalised programs that promise a more cost-effective diabetes management while reducing diabetes-related complications. In such a context, this work attempts to update cost analysis reviews on type 2 diabetes, focusing on France and Germany, in order to explore most significant cost drivers and cost-saving opportunities through innovations in diabetes care. Although both countries approach care delivery differently, France and Germany represent the primary European markets for diabetes technologies.

METHODS

A systematic review of the literature listed in MEDLINE, Embase and EconLit has been carried out. It covered interventional, observational and modelling studies on expenditures for type 2 diabetes management in France or Germany published since 2012. Included articles were analysed for annual direct, associated and indirect costs of type 2 diabetes patients. An appraisal of study quality was performed. Results were summarised narratively.

RESULTS

From 1260 records, the final sample was composed of 24 papers selected according to predefined inclusion/exclusion criteria. Both France and Germany revealed a predominant focus on direct costs. Comparability was limited due to different study populations and cost categories used. Indirect costs were only available in Germany. According to prior literature, reported cost drivers are hospitalisation, prescriptions, higher HbA1c and BMI, treatment with insulin and complications, all indicators of disease severity. The diversity of available data and included costs limits the results and may explain the differences found.

CONCLUSIONS

Complication prevention and glycaemic control are widely recognized as the most effective ways to control diabetes treatment costs. The value propositions of self-based supports, such as hybrid closed-loop metabolic systems, already implemented in type 1 diabetes management, are the key points for further debates and policymaking, which should involve the perspectives of caregivers, patients and payers.

The effect of remote patient monitoring on the primary care clinic visit frequency among adults with type 2 diabetes

AIMS

Healthcare organizations are increasingly using technology to assist in diabetes management based on telemedicine's proven ability to improve glycemic regulation, decrease cost, and overcome barriers to effective healthcare. Nevertheless, it remains unclear how telemedicine intersects with primary care. We aim to measure the impact of a remote monitoring program for diabetes on primary care delivery through analysis of primary care office visit frequency.

METHODS

Patients eligible to participate in our institution's remote diabetes monitoring program were identified and classified as enrolled or not enrolled (i.e. "usual care"). The number of scheduled and completed primary care office visits in the 12 months prior to and after the index date were measured for both groups. The index date was the enrollment date or, for the patients who received usual care, the next available enrollment session after eligibility screen. Two-sample t-tests were used to examine the change in frequency of office visits prior to and after enrollment for participants, as well as the difference in visit frequency between enrolled patients versus patients receiving usual care.

RESULTS

There was no statistical difference in the number of scheduled or completed primary care clinic visits before or after enrollment in telehealth. Furthermore, there was no difference in the number of scheduled or completed primary care visits between patients enrolled in telehealth versus those receiving usual care.

CONCLUSION

Participation in telehealth has been shown to be associated with significant HbA1c reductions in prior work, yet our data suggest that remote monitoring is not associated with a change in primary care office visit frequency. This suggests that telehealth may improve diabetes management independently of primary care visits.

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.

Budget Impact of Improved Diabetes Management by Utilization of Glucose Meters With a Color-Range Indicator-Comparison of Five European Healthcare Systems

BACKGROUND AND AIM

Costs for the treatment of diabetes and its comorbidities are a major international issue. A recent randomized clinical trial showed that the introduction of color range indicator (CRI)-based glucose meters (GMs) positively affects the HbA1c of patients with type 1 and type 2 diabetes, when compared to GMs without a CRI. This budget impact analysis aimed to translate this beneficial effect of CRI-based GMs, OneTouch Verio Flex and OneTouch Verio, into potential monetary impact for the healthcare systems of five European countries, Germany, Spain, Italy, France, and the United Kingdom.

MATERIAL AND METHODS

Data from a randomized controlled trial, evaluating the effect of CRI-based GMs, were used to estimate the ten-year risk of patients for fatal myocardial infarction (MI) as calculated by the UK Prospective Diabetes Study (UKPDS) risk engine. On the basis of assessed risks for MI, the potential monetary impact for the healthcare systems in five European countries was modeled.

RESULTS

Based on a mean HbA1c reduction of 0.36%, as demonstrated in a randomized controlled trial, the UKPDS risk engine estimated a reduction of 2.4% of the ten-year risk of patients for fatal MI. When applied to our economic model, substantial potential cost savings for the healthcare systems of five European countries were calculated: €547 472 (France), €9.0 million (Germany), €6.0 million (Italy), €841 799 (Spain), and €421 069 (United Kingdom) per year.

CONCLUSION

Improving metabolic control in patients with diabetes by the utilization of CRI-based GMs may have substantial positive effects on the expenditure of the healthcare systems of several European countries.