2025 Southeastern Residency Conference

Title: Evaluation of Pharmacists’ Impact on Diabetes Care Using Cloud-based Continuous Glucose Monitoring
Author’s names: William L. Kendrick, J. Lindsey Pitt, Shauntá M. Chamberlin, R Eric Heidel, Jeffrey A. Lewis, Kaitlyn P. North
Objective: Describe the effect of pharmacist-led diabetes management for patients using CGM devices linked to a cloud-based service versus those who use CGM devices incompatible to cloud services.
Self Assessment Question: True or False: there was a noticeable difference seen in the management of diabetes using cloud-based CGM devices.
Purpose: When patients share their data over cloud-based software, continuous glucose monitors allow pharmacists to assess glycemic control and make real-time therapy changes for patients participating in virtual or telehealth visits. It is hypothesized that the ability to make these changes in between primary care visits allows for faster glycemic control when compared to patients who utilize readers which are not compatible with cloud-based uploading. However, limited data is published in regard to pharmacist-led diabetes management using continuous glucose monitoring devices utilizing cloud-based services.
Methods: This retrospective cohort study assesses patients from an internal medicine residency clinic and a family medicine clinic at a tertiary academic medical center, where pharmacists have collaborative practice to manage diabetes. Patients were included if they were 18 years or older, had a diagnosis of type 1 or type 2 diabetes, and were current patients of their respective clinic. Patients were excluded if they were pregnant or lactating, if their diabetes was managed by an outside endocrinologist, or if they had not been followed by pharmacist for at least 3 months allowing for a follow-up A1C. Data collected from retrospective chart review included patient age, gender, type of diabetes, associated diabetic comorbidities, date of first and last pharmacist intervention utilizing CGM data, initial A1c, first follow-up A1c, most recent A1c since last pharmacist intervention, type of continuous glucose monitor, and ability for cloud-based monitoring. The two primary outcomes being assessed were the change from baseline A1c to first follow-up A1c, and the change from baseline A1c to most recent A1c since last pharmacist intervention. Consultation with a biostatistician revealed that the study would require at least 79 patients in each arm to achieve 80% power with an alpha of 0.05. Data was analyzed using mixed-effects ANOVA. 
Results: Between the two primary care clinics, 121 patients were reviewed for eligibility, and 49 patients were included in the study. Of the patients enrolled, median age was 55 (IQR 46-65), 20 were female (41%), 20 were enrolled in cloud-based sharing (41%), and seven had type 2 diabetes (14%). The median days between first pharmacist consult and first follow-up A1c was 107 (IQR 66-160), and the median days between first pharmacist consult and most recent A1c was 347 (IQR 206-407). Average baseline A1c for the cloud and non-cloud groups were 9.86% vs 9.92% (p=0.88) respectively, average first follow-up A1c was 8.48 vs 8.56 (p=0.85), and average A1c at most recent follow-up was 8.53 vs 8.58 (p=0.90). The most common type of pharmacist intervention performed for each patient was medication titration (100%) followed by initiating new therapies (49%) and discontinuing therapy (10%).
Conclusion: While the retrospective study did not identify enough patients to meet the pre-specified power, there was no difference in A1c reduction between the cloud-based group and the non-cloud-based group found in the limited number of patients analyzed. Average A1c reduction of -1.4% at first follow-up A1c and -1.3% at most recent A1c for both pharmacist-managed groups. Limitations include variability in pharmacist coverage between the two clinics, poor social determinants of health in the patient population, and lack of timely cloud enrollment. Benefit incurred with cloud-based CGM utilization may come in the form of increased workflow productivity instead of directly from improved patient glycemic control.