(1059) Clinical Decision Making Utilizing Continuous Glucose Monitor Data: How Well Does It Correlate to hba1c?

Objectives: To assess the correlation between time in glycemic range (TIR) and changes in hemoglobin A1c (HbA1c) levels when continuous glucose monitor (CGM) data is used in clinical decision making by a clinical pharmacist-nurse practitioner care team. Current literature is limited to describing the correlation of continuous glucose monitor use and improved HbA1c’s in patients with Type 2 diabetes. However, there is a lack of literature correlating changes in HbA1c with TIR and time above range (TAR) and time below range (TBR). Additionally, the clinical outcomes associated with the use of CGM data in clinical decision making by non-physician providers is limited.

Methods: This retrospective chart review will include adult patients seen in an internal medicine clinic by an interdisciplinary team consisting of a pharmacist and nurse practitioner. Patients with Type 1 and Type 2 diabetes seen by the interdisciplinary team within the last 12 months who used a CGM will be included. Patients will be excluded if their baseline HbA1c is less than 6.5%. Information to be collected will include: demographic information, primary insurance type, diabetes type, and comorbidities that increase risk of diabetes associated complications and presence of diabetes complications. Clinical data will include baseline HbA1c and three months following CGM use, first available TIR, TAR and TBR and at three months, prescribing of guideline directed therapy prior to CMG and following CGM use, number of encounters with interdisciplinary team, and frequency and type of interventions performed by the pharmacists. Pearson’s correlation will be conducted to determine if a statistical relationship exist between HbA1c and CGM endpoints. The change in number of patients achieving goal HbA1c, number and type of interventions performed and all other categorical variables will be analyzed using the Fisher’s exact or Chi-square test. Change in TIR, TAR, and TBR and other continuous variables will be analyzed using the Mann-Whitney U test.

Results: Between January 2023 and January 2024, approximately 80 patients have been identified to have been prescribed a CGM. Of these patients, roughly 95% of them have type 2 diabetes. Clinical data points continue to be collected for all patients meeting inclusion criteria.

Conclusions: The findings of this research will determine if a correlation exist between the CGM data and HbA1c and potentially validate the accuracy of HbA1c values by evaluating the extent of glycemic variability CGM provides. Additionally, findings will provide valuable information to guide pharmacist on how best to identify patients that may benefit the greatest from initiating CGM and the frequency at which the data is utilized to guide optimization of medication therapies to achieve glycemic control.