Using Digital Health Technology to Prevent and Treat Diabetes

Effectiveness of Telemedicine in Managing Diabetes in Pregnancy: A Systematic Review and Meta-Analysis

BACKGROUND

Strict monitoring of blood glucose during pregnancy is essential for ensuring optimal maternal and neonatal outcomes. Telemedicine could be a promising solution for supporting diabetes management; however, an updated meta-analysis is warranted. This study assesses the effects of telemedicine solutions for managing gestational and pregestational diabetes.

METHODS

PubMed, EMBASE, Cochrane Library Central Register of Controlled Trials, and CINAHL were searched up to October 14, 2020. All randomized trials assessing the effects of telemedicine in managing diabetes in pregnancy relative to any comparator without the use of telemedicine were included. The primary outcome was infant birth weight. A meta-analysis comparing the mean difference (MD) in birth weight across studies was applied, and subgroup and sensitivity analyses were performed. The revised Cochrane tool was applied to assess the risk of bias, and the certainty of evidence was evaluated using the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach.

RESULTS

From a total of 18 studies, ten (totaling 899 participants) were used to calculate the effect on infant birth weight. The results nonsignificantly favored the control (MD of 19.34 g; [95% confidence interval, CI -47.8; 86.47]), with moderate effect certainty. Heterogeneity was moderate (I2 = 37.39%). Statistically significant secondary outcomes included differences in two-hour glucose tolerance postpartum (gestational diabetes; two studies: standardized mean difference 9.62 mg/dL [95% CI: 1.95; 17.28]) that favored the control (GRADE level, very low) and risk of shoulder dystocia (four studies: log odds -1.34 [95% CI: -2.61; -0.08]) that favored telemedicine (GRADE, low).

CONCLUSIONS

No evidence was found to support telemedicine as an alternative to usual care when considering maternal and fetal outcomes. However, further research is needed, including economic evaluations.

The Diabetes teleMonitoring of patients in insulin Therapy (DiaMonT) trial: study protocol for a randomized controlled trial

BACKGROUND

The effect of telemedicine solutions in diabetes remains inconclusive. However, telemedicine studies have shown a positive trend in regards to glycemic control. The telemedicine interventions that facilitate adjustment of medication seems to improve glycemic control more effectively. Hence, it is recommended that future telemedicine studies for patients with diabetes include patient-specific suggestions for changes in medicine. Hence, the aim of the trial is to explore the effect of telemonitoring in patients with type 2 diabetes (T2D) on insulin therapy.

METHODS

The trial is an open-label randomized controlled trial with a trial period of 3 months conducted in two sites in Denmark. Patients with T2D on insulin therapy will be randomized (1:1) to a telemonitoring group (intervention) or a usual care group (control). The telemonitoring group will use a continuous glucose monitor (CGM), an insulin pen, an activity tracker, and smartphone applications throughout the trial. Hospital staff will monitor the telemonitoring group and contact the subjects by telephone repeatedly throughout the trial period. The usual care group will use a blinded CGM the first and last 20 days of the trial and will use a blinded insulin pen for the entire period. The primary endpoint will be changed from baseline in CGM time in range (3.9-10.0 mmol/L) 3 months after randomization. Secondary endpoints include change from baseline in glycated hemoglobin (HbA1c), total daily dose, time above range, and time below range 3 months after randomization. Exploratory endpoints include health-related quality of life, diabetes-related quality of life, etc. DISCUSSION: The DiaMonT trial will test a telemonitoring setup including various devices. Such a setup may be criticized, because it is impossible to determine which element(s) add to the potential effect. However, it is not possible and counterproductive to test the elements individually, since it is the full telemedicine setup that is being evaluated. The DiaMonT trial is the first Danish trial to explore the effect of telemonitoring on patients on insulin therapy. Thus, the DiaMonT trial has the potential to form the basis for the implementation of telemedicine for patients with T2D in Denmark.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04981808. Registered on 8 June 2021.

Impact of Reducing Glycated Hemoglobin on Healthcare Costs Among a Population with Uncontrolled Diabetes

INTRODUCTION

Glycated hemoglobin (A1C) is considered a "gold standard" measure of glycemic control in patients with diabetes and is correlated with a lower risk of diabetes complications and cost savings. This retrospective claims-analysis assessed the impact of A1C reduction on healthcare costs in patients with uncontrolled Type 1 and Type 2 diabetes.

METHODS

Using a large repository of US health plan administrative data linked to A1C values, patients with a diabetes diagnosis and at least two A1C values between 1 January 2009 and 31 December 2014 were selected to identify changes in A1C and associated changes in healthcare expenditure. We used all medical and pharmacy claims to calculate direct healthcare costs from 1 year prior to the index A1C to 2 years after the index A1C. A propensity score method was used to match patients with decreased A1C to patients whose A1C did not decrease, based on potentially confounding variables. Then, a generalized linear model regression was used to estimate the difference-in-difference (DD) effect on costs between the two groups.

RESULTS

Of the 3,197 patients who had a first A1C ≥ 9%, 2,273 patients (71%) had a decrease in A1C (Decreasers) and 924 patients (27%) had an increase in A1C (Non-decreasers). After matching, we compared 912 Decreasers to 912 Non-decreasers. Patients in the former group had average annual healthcare costs that were 24% lower during the first year of follow-up and 17% lower during the second year of follow-up, compared to patients whose A1C did not decrease. This reflected a savings of US$2503 and US$1690, respectively. For both time periods, the outpatient category was the largest contributor to cost savings.

DISCUSSION

In our analysis, A1C reduction among patients with T1DM and T2DM was associated with slower growth in healthcare costs within 1-2 years. These findings suggest that programs aimed at reducing A1C over a short timeframe may lead to substantial savings and may be worth pursuing by health plans and other payers.

Digital Transformation and Disruption of the Health Care Sector: Internet-Based Observational Study

Background

Digital innovation, introduced across many industries, is a strong force of transformation. Some industries have seen faster transformation, whereas the health care sector only recently came into focus. A context where digital corporations move into health care, payers strive to keep rising costs at bay, and longer-living patients desire continuously improved quality of care points to a digital and value-based transformation with drastic implications for the health care sector.

Objective

We tried to operationalize the discussion within the health care sector around digital and disruptive innovation to identify what type of technological enablers, business models, and value networks seem to be emerging from different groups of innovators with respect to their digital transformational efforts.

Methods

From the Forbes 2000 and CBinsights databases, we identified 100 leading technology, life science, and start-up companies active in the health care sector. Further analysis identified projects from these companies within a digital context that were subsequently evaluated using the following criteria: delivery of patient value, presence of a comprehensive and distinctive underlying business model, solutions provided, and customer needs addressed.

Results

Our methodological approach recorded more than 400 projects and collaborations. We identified patterns that show established corporations rely more on incremental innovation that supports their current business models, while start-ups engage their flexibility to explore new market segments with notable transformations of established business models. Thereby, start-ups offer higher promises of disruptive innovation. Additionally, start-ups offer more diversified value propositions addressing broader areas of the health care sector.

Conclusions

Digital transformation is an opportunity to accelerate health care performance by lowering cost and improving quality of care. At an economic scale, business models can be strengthened and disruptive innovation models enabled. Corporations should look for collaborations with start-up companies to keep investment costs at bay and off the balance sheet. At the same time, the regulatory knowledge of established corporations might help start-ups to kick off digital disruption in the health care sector.