Reduction in Diabetes-Related Hospitalizations and Medical Costs After Dexcom G6 Continuous Glucose Monitor Initiation in People with Type 2 Diabetes Using Intensive Insulin Therapy

INTRODUCTION

Some people with type 2 diabetes (T2D) require intensive insulin therapy to manage their diabetes. This can increase the risk of diabetes-related hospitalizations. We hypothesize that initiation of real-time continuous glucose monitoring (RT-CGM), which continuously measures a user's glucose values and provides threshold- and trend-based alerts, will reduce diabetes-related emergency department (ED) and inpatient hospitalizations and concomitant costs.

METHODS

A retrospective analysis of US healthcare claims data using Optum's de-identified Clinformatics® Data Mart database was performed. The cohort consisted of commercially insured, CGM-naïve individuals with T2D who initiated Dexcom G6 RT-CGM system between August 1, 2018, and March 31, 2021. Twelve months of continuous health plan enrollment before and after RT-CGM initiation was required to capture baseline and follow-up rates of diabetes-related hospitalizations and associated healthcare resource utilization (HCRU) costs. Analyses were performed for claims with a diabetes-related diagnosis code in either (1) any position or (2) first or second position on the claim.

RESULTS

A total of 790 individuals met the inclusion criteria. The average age was 52.8 (10.5) [mean (SD)], 53.3% were male, and 76.3% were white. For claims with a diabetes-related diagnosis code in any position, the number of individuals with ≥ 1 ED visit decreased by 30.0% (p = 0.01) and with ≥ 1 inpatient visit decreased by 41.5% (p < 0.0001). The number of diabetes-related visits and average number of visits per person similarly decreased by at least 31.4%. Larger relative decreases were observed for claims with a diabetes-related diagnosis code in the first or second position on the claim. Total diabetes-related costs expressed as per-person-per-month (PPPM) decreased by $341 PPPM for any position and $330 PPPM for first or second position.

CONCLUSION

Initiation of Dexcom G6 among people with T2D using intensive insulin therapy was associated with a significant reduction in diabetes-related ED and inpatient visits and related HCRU costs. Expanded use of RT-CGM could augment these benefits and result in further cost reductions.

Continuous Glucose Monitoring and Reduced Diabetes-Related Hospitalizations in Patients with Type 2 Diabetes and CKD

Key Points

Patients with diabetes and CKD have a heightened risk of glycemic variability, which can lead to severe hypoglycemic or hyperglycemic events, potentially resulting in hospitalization. This study describes the results of a retrospective claims analysis of people with insulin-requiring type 2 diabetes and stage 3–5 CKD who initiated continuous glucose monitoring. Continuous glucose monitoring could help patients with type 2 diabetes and CKD control their glucose and avoid potentially dangerous glycemic events.

Background

There is a heightened risk of glycemic variability in patients with diabetes and CKD. This glycemic variability could lead to hypoglycemic or hyperglycemic crises. We hypothesized that initiation of continuous glucose monitoring (CGM), which provides a glucose measurement every 1–5 minutes, could reduce the incidence of hospitalizations for patients with type 2 diabetes (T2D) and CKD.

Methods

A retrospective analysis of US administrative claims data from the Optum Clinformatics database was conducted. People with T2D, using insulin, not receiving dialysis, and living with stage 3–5 CKD who initiated CGM between January 1, 2016, and March 31, 2022, were identified. National Drug Codes and Healthcare Common Coding Procedure System codes were used to identify CGM device use, and International Classification of Diseases 10th revision codes were used to identify CKD diagnosis and categorize health care encounters. Rates of diabetes-related hospitalizations were obtained, and multivariable logistic regression analyses revealed predictors of hypoglycemic and hyperglycemic encounters.

Results

A total of 8,959 insulin-using patients with T2D and CKD were identified. Most were White (72.3%), had Medicare insurance coverage (82.2%), were using intensive insulin (91.3%), and had stage 3 CKD (86.0%). After CGM initiation, rates of hospitalizations for hyperglycemia or hypoglycemia decreased by 18.2% and 17.0%, respectively (P < 0.0001 for both). The proportion hospitalized with at least one hypoglycemic or hyperglycemic event also significantly decreased after CGM initiation. Significant predictors of both hypoglycemic and hyperglycemic encounters included a previous encounter of that type, age 30–59 years and depression (for hypoglycemia), and age 30–49 years and neuropathy (for hyperglycemia). Use of CGM or glucagon-like peptide-1 receptor agonists was significantly protective against hypoglycemic encounters.

Conclusions

Initiation of CGM was associated with significant reductions in diabetes-related hospitalizations among insulin-using individuals with T2D and moderate-to-severe CKD. CGM could help patients with T2D and CKD control their glucose and avoid potentially dangerous glycemic events.

Association Between Adherence, A1C Improvement, and Type of Continuous Glucose Monitoring System in People with Type 1 Diabetes or Type 2 Diabetes Treated with Intensive Insulin Therapy

INTRODUCTION

Use of continuous glucose monitoring (CGM) systems by people with diabetes is associated with improved glycemic outcomes, including lower glycated hemoglobin (A1C). Less is known about adherence to CGM systems, whether glycemic outcomes are impacted by levels of adherence, or whether adherence rates differ between types of CGM systems-intermittently scanned CGM (isCGM) or real-time CGM (rtCGM).

METHODS

A retrospective analysis of de-identified US administrative health claims and linked laboratory data was conducted using the Merative™ MarketScan® Research Database. The cohort included CGM-naïve people with type 1 diabetes (T1D) or type 2 diabetes treated with intensive insulin therapy (T2D-IIT) who initiated rtCGM or isCGM between August 1, 2019 and March 31, 2021 (defined as the index date). Adherence was calculated over a 12-month period using the proportion of days covered (PDC) with PDC ≥ 0.8 defined as adherent. A1C values were obtained within 6 months of the index date.

RESULTS

A total of 7669 individuals were identified. Subgroups included T1D using isCGM (n = 1578), T1D using rtCGM (n = 1244), T2D-IIT using isCGM (n = 3567), and T2D-IIT using rtCGM (n = 1280). After 12 months, PDC was 0.71 (0.30)-0.72 (0.31) (mean(SD)) for T1D and T2D-IIT rtCGM users and 0.55 (0.34)-0.56 (0.34) for T1D and T2D-IIT isCGM users. The proportion of adherent users (PDC ≥ 0.8) was 56.8-59.7% for rtCGM users and 36.3-37.6% for isCGM users. Overall, regardless of diabetes type, the odds of adherence were over two times higher for rtCGM users compared to isCGM users. For those with available A1C information (T1D n = 213; T2D-IIT n = 346), independent of CGM type, adherence to CGM was associated with a greater reduction in A1C and more people reaching A1C targets of < 7.0% or < 8.0%.

CONCLUSION

For people with T1D or T2D-IIT, higher adherence to CGM is associated with greater reductions in A1C, and higher adherence rates were observed with rtCGM systems than with isCGM systems.

Assessing and predicting drug-induced anticholinergic risks: an integrated computational approach

Background:

Anticholinergic (AC) adverse drug events (ADEs) are caused by inhibition of muscarinic receptors as a result of designated or off-target drug–receptor interactions. In practice, AC toxicity is assessed primarily based on clinician experience. The goal of this study was to evaluate a novel concept of integrating big pharmacological and healthcare data to assess clinical AC toxicity risks.

Methods:

AC toxicity scores (ATSs) were computed using drug–receptor inhibitions identified through pharmacological data screening. A longitudinal retrospective cohort study using medical claims data was performed to quantify AC clinical risks. ATS was compared with two previously reported toxicity measures. A quantitative structure–activity relationship (QSAR) model was established for rapid assessment and prediction of AC clinical risks.

Results:

A total of 25 common medications, and 575,228 exposed and unexposed patients were analyzed. Our data indicated that ATS is more consistent with the trend of AC outcomes than other toxicity methods. Incorporating drug pharmacokinetic parameters to ATS yielded a QSAR model with excellent correlation to AC incident rate (R² = 0.83) and predictive performance (cross validation Q² = 0.64). Good correlation and predictive performance (R² = 0.68/Q² = 0.29) were also obtained for an M2 receptor-specific QSAR model and tachycardia, an M2 receptor-specific ADE.

Conclusions:

Albeit using a small medication sample size, our pilot data demonstrated the potential and feasibility of a new computational AC toxicity scoring approach driven by underlying pharmacology and big data analytics. Follow-up work is under way to further develop the ATS scoring approach and clinical toxicity predictive model using a large number of medications and clinical parameters.