Standardizing Reporting of Glucose and Insulin Data for Patients on Multiple Daily Injections Using Connected Insulin Pens and Continuous Glucose Monitoring

Abstract

Background: Recent development and availability of several connected insulin pens with digital memory are likely to expand the availability of glucose and insulin metrics that previously had been available only for the much smaller number of people using insulin pumps. It would be highly desirable to standardize data presentations to avoid the chaotic emergence of multiple formats that might reduce the clinical utility of connected pens. Methods: We reviewed the literature and analyzed data displays from multiple blood glucose monitoring, continuous glucose monitoring (CGM), insulin pump, and automated insulin delivery systems, and methods for combination of glucose and insulin data. We examined multiple forms of presentation and now propose a prototype for a standardized method for data analysis and display, focusing on the content and format of a onepage dashboard summary for patients on multiple daily injection (MDI) insulin regimens. Results: We propose the following metrics to be included in the one-page report: (A) glucose metrics: simplified glucose distribution in the form of a stacked bar chart showing percentages of time below-, above-, or within-target ranges overall and (optionally) by date, by time of day, or day of the week; (B) insulin metrics: types and doses, and timing of basal and bolus insulin; (C) an enhanced ambulatory glucose profile or ''AGP+'' showing glucose data points and/or distributions (10th to 90th percentiles), dosages and timing of basal and bolus insulins and (optionally) graphical display of risk of hypoglycemia and hyperglycemia; and (D) user experience regarding technology usage, frequency of alerts for hypo-and hyperglycemia, and information regarding lifestyle, meals, exercise, and sleep, if available; and (E) clinical insights and interpretation. Conclusion:We propose a prototype for a dashboard summary report of glucose, insulin, meals, and activity data intended for providers and patients on MDI using connected pens and CGM. Our goal is to stimulate development of a standardized approach.

Emerging Diabetes Technologies: Continuous Glucose Monitors/Artificial Pancreases

“…Some of these smart pens are already available in Europe. There is an attempt to standardize the reporting of smart pens, CGM data, and HCL systems so that the report appears like an EKG 187 – 189 . There are many platforms that are available to download these reports such as, Care Link, Glooko, Clarity, and Libre view.…”

Connected Insulin Pens and Caps: An Expert’s Recommendation from the Area of Diabetes of the Spanish Endocrinology and Nutrition Society (SEEN)

“…Standardization of integrated insulin therapy and glucose data analysis and reports is needed to facilitate decision making. Rodbard and Garg [ 46 ] have developed the first standardised report proposal for users of connected pens and caps. In 2021, Bergenstal [ 47 ] presented another proposal for a standardized report that includes (see Table 5 ): Graph of stacked bars with TIR, TAR and TBR goals, either standard or personalized, depending on the patient; Glucometric data: mean glucose levels, glucose management indicator (GMI), coefficient of variation; Insulin metrics: mean total daily dose of insulin, mean dose of basal insulin, mean dose of prandial insulin, mean boluses per day and use of the bolus calculator (also indicating whether the dose administered has been higher or lower than calculated); Ambulatory Glucose Profile (AGP) with personalized data on insulin ratios, insulin sensitivity factor and personalized glycaemic target for different time slots throughout the day; Basal insulin analysis, including mean dose of basal insulin, time of administration, nocturnal blood glucose < 70 mg/dl (3.9 mmol/l) and mean blood glucose from bedtime to rise; Analysis of insulin boluses.…”

Guideline Development for Medical Device Technology: Issues for Consideration

“…Smart insulin pens can accurately capture insulin data that can then be integrated with glucose and dietary (carbohydrate) data by software applications and transmitted to the patient’s HCPs. 32,33…”