1
|
Simonson GD, Criego AB, Battelino T, Carlson AL, Choudhary P, Franc S, Gershenoff D, Grunberger G, Hirsch IB, Isaacs D, Johnson ML, Kerr D, Kruger DF, Mathieu C, Martens TW, Nimri R, Oser SM, Peters AL, Weinstock RS, Wright EE, Wysham CH, Bergenstal RM. Expert Panel Recommendations for a Standardized Ambulatory Glucose Profile Report for Connected Insulin Pens. Diabetes Technol Ther 2024. [PMID: 38758213 DOI: 10.1089/dia.2024.0107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/18/2024]
Abstract
Background: Connected insulin pens capture data on insulin dosing/timing and can integrate with continuous glucose monitoring (CGM) devices with essential insulin and glucose metrics combined into a single platform. Standardization of connected insulin pen reports is desirable to enhance clinical utility with a single report. Methods: An international expert panel was convened to develop a standardized connected insulin pen report incorporating insulin and glucose metrics into a single report containing clinically useful information. An extensive literature review and identification of examples of current connected insulin pen reports were performed serving as the basis for creation of a draft of a standardized connected insulin pen report. The expert panel participated in three virtual standardization meetings and online surveys. Results: The Ambulatory Glucose Profile (AGP) Report: Connected Insulin Pen brings all clinically relevant CGM-derived glucose and connected insulin pen metrics into a single simplified two-page report. The first page contains the time in ranges bar, summary of key insulin and glucose metrics, the AGP curve, and detailed basal (long-acting) insulin assessment. The second page contains the bolus (mealtime and correction) insulin assessment periods with information on meal timing, insulin-to-carbohydrate ratio, average bolus insulin dose, and number of days with bolus doses recorded. The report's second page contains daily glucose profiles with an overlay of the timing and amount of basal and bolus insulin administered. Conclusion: The AGP Report: Connected Insulin Pen is a standardized clinically useful report that should be considered by companies developing connected pen technology as part of their system reporting/output.
Collapse
Affiliation(s)
- Gregg D Simonson
- International Diabetes Center, HealthPartners Institute, Minneapolis, Minnesota, USA
| | - Amy B Criego
- International Diabetes Center, HealthPartners Institute, Minneapolis, Minnesota, USA
| | - Tadej Battelino
- University Medical Center Ljubljana, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Anders L Carlson
- International Diabetes Center, HealthPartners Institute, Minneapolis, Minnesota, USA
| | - Pratik Choudhary
- Diabetes Research Centre, University of Leicester, Leicester, United Kingdom
| | - Sylvia Franc
- Diabetes and Metabolic Diseases Department, Sud Francilien Hospital, Corbeil-Essonnes, France
| | | | - George Grunberger
- Grunberger Diabetes & Endocrinology, Bloomfield Hills, Michigan, USA
| | - Irl B Hirsch
- University of Washington School of Medicine, Seattle, Washington, USA
| | | | - Mary L Johnson
- International Diabetes Center, HealthPartners Institute, Minneapolis, Minnesota, USA
| | - David Kerr
- Center for Health Systems Research, Sutter Health, Santa Barbara, California, USA
| | - Davida F Kruger
- Division of Endocrinology, Diabetes, Bone and Mineral Disease, Henry Ford Health System, Detroit, Michigan, USA
| | - Chantal Mathieu
- Department of Endocrinology, UZ Gasthuisberg, Katholieke Universiteit Leuven, Leuven, Belgium
| | - Thomas W Martens
- International Diabetes Center, HealthPartners Institute, Minneapolis, Minnesota, USA
| | - Revital Nimri
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Faculty of Medical and Health Sciences, Tel-Aviv University, Tel-Aviv, Israel
| | - Sean M Oser
- University of Colorado School of Medicine, Aurora, Colorado, USA
| | - Anne L Peters
- USC Keck School of Medicine, Los Angeles, California, USA
| | | | - Eugene E Wright
- South Piedmont Area Health Education Center, Charlotte, North Carolina, USA
| | | | - Richard M Bergenstal
- International Diabetes Center, HealthPartners Institute, Minneapolis, Minnesota, USA
| |
Collapse
|
2
|
Battelino T, Brosius F, Ceriello A, Cosentino F, Green J, Kellerer M, Koob S, Kosiborod M, Lalic N, Marx N, Nedungadi TP, Rydén L, Rodbard HW, Ji L, Sheu WHH, Standl E, Parkin CG, Schnell O. Guideline Development for Medical Device Technology: Issues for Consideration. J Diabetes Sci Technol 2023; 17:1698-1710. [PMID: 35531901 PMCID: PMC10658688 DOI: 10.1177/19322968221093355] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Advances in the development of innovative medical devices and telehealth technologies create the potential to improve the quality and efficiency of diabetes care through collecting, aggregating, and interpreting relevant health data in ways that facilitate more informed decisions among all stakeholder groups. Although many medical societies publish guidelines for utilizing these technologies in clinical practice, we believe that the methodologies used for the selection and grading of the evidence should be revised. In this article, we discuss the strengths and limitations of the various types of research commonly used for evidence selection and grading and present recommendations for modifying the process to more effectively address the rapid pace of device and technology innovation and new product development.
Collapse
Affiliation(s)
- Tadej Battelino
- University Medical Center Ljubljana, University of Ljubljana, Ljubljana, Slovenia
| | - Frank Brosius
- University of Arizona College of Medicine–Tucson, AZ, USA
| | | | - Francesco Cosentino
- Cardiology Unit, Department of Medicine, Karolinska Institute, Karolinska University Hospital, Stockholm, Sweden
| | - Jennifer Green
- Duke University Medical Center, Duke Clinical Research Institute, Durham, NC, USA
| | | | | | - Mikhail Kosiborod
- Saint Luke’s Mid America Heart Institute, University of Missouri-Kansas City, Kansas City, MO, USA
- The George Institute for Global Health, University of New South Wales, Sydney, Australia
| | - Nebojsa Lalic
- Clinic for Endocrinology, Diabetes and Metabolic Diseases, University Clinical Center of Serbia, University of Belgrade, Belgrade, Serbia
| | - Nikolaus Marx
- Department of Internal Medicine I, University Hospital Aachen, RWTH Aachen University, Aachen, Germany
| | | | - Lars Rydén
- Department of Medicine K2, Karolinska Institute, Stockholm, Sweden
| | | | - Linong Ji
- Peking University People’s Hospital, Beijing, China
| | - Wayne Huey-Herng Sheu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung City
| | | | | | | |
Collapse
|
3
|
Espinoza JC, Yeung AM, Huang J, Seley JJ, Longo R, Klonoff DC. The Need for Data Standards and Implementation Policies to Integrate Insulin Delivery Data Into the Electronic Health Record. J Diabetes Sci Technol 2023; 17:1376-1386. [PMID: 37232299 PMCID: PMC10563544 DOI: 10.1177/19322968231178549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/27/2023]
Abstract
Integration of insulin dosing data into the electronic health record (EHR), combined with other patient-generated health care data, would facilitate the use of wirelessly connected insulin delivery systems, including smart insulin pens, insulin pumps, and advanced hybrid closed-loop systems. In 2022, Diabetes Technology Society developed the Integration of Continuous Glucose Monitoring Data into the EHR (iCoDE) Project, which is the first consensus standard for integrating data from a wearable device into the EHR. The iCoDE Standard is a comprehensive guide for any health care delivery organization or hospital for automatically integrating continuous glucose monitoring data into the EHR. Diabetes Technology Society is following iCoDE with the Integration of Connected Diabetes Device Data into the EHR (iCoDE-2) Project, to similarly provide guidance for integrating insulin delivery data into the EHR alongside continuous glucose monitoring data.
Collapse
Affiliation(s)
- Juan C. Espinoza
- Stanley Manne Children’s Research Institute, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | | | | | | | - Rebecca Longo
- Beth Israel Lahey Health/Lahey Hospital and Medical Center, Burlington, MA, USA
| | - David C. Klonoff
- Diabetes Technology Society, Burlingame, CA, USA
- Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA, USA
| |
Collapse
|
4
|
Baliga BS, Tillman JB, Olson B, Vaughan S, Sheikh FN, Malone JK. First Real-World Experience With Bigfoot Unity: A 6-Month Retrospective Analysis. Clin Diabetes 2023; 41:539-548. [PMID: 37849519 PMCID: PMC10577513 DOI: 10.2337/cd22-0126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/19/2023]
Abstract
The Bigfoot Unity Diabetes Management System, a smart pen cap system cleared by the U.S. Food and Drug Administration in May 2021, incorporates continuous glucose monitoring data, real-time glycemic alerts, and clinician-directed dose recommendations. This study analyzed real-world clinical outcomes data for an initial cohort (n = 58, from 13 clinics) managing multiple daily injection insulin therapy using the pen cap system for 6 months. We examined glycemic control, including hypoglycemia events and interaction with and use of the pen cap system. In a cohort mainly consisting of adults with type 2 diabetes and an average age of 62 years, the results demonstrate close adherence to established glycemic targets, including a relatively short amount of time spent in the hypoglycemic range.
Collapse
|
5
|
Piersanti A, Giurato F, Göbl C, Burattini L, Tura A, Morettini M. Software Packages and Tools for the Analysis of Continuous Glucose Monitoring Data. Diabetes Technol Ther 2023; 25:69-85. [PMID: 36223198 DOI: 10.1089/dia.2022.0237] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
The advancement of technology in the field of glycemic control has led to the widespread use of continuous glucose monitoring (CGM), which can be nowadays obtained from wearable devices equipped with a minimally invasive sensor, that is, transcutaneous needle type or implantable, and a transmitter that sends information to a receiver or smart device for data storage and display. This work aims to review the currently available software packages and tools for the analysis of CGM data. Based on the purposes of this work, 12 software packages have been identified from the literature, published until December 2021, namely: GlyCulator, EasyGV (Easy Glycemic Variability), CGM-GUIDE© (Continuous Glucose Monitoring Graphical User Interface for Diabetes Evaluation), GVAP (Glycemic Variability Analyzer Program), Tidepool, CGManalyzer, cgmanalysis, GLU, CGMStatsAnalyser, iglu, rGV, and cgmquantify. Comparison of available software packages and tools has been done in terms of main characteristics (i.e., publication year, presence of a graphical user interface, availability, open-source code, number of citations, programming language, supported devices, supported data format and organization of the data structure, documentation, presence of a toy example, video tutorial, data upload and download, measurement-units conversion), preprocessing procedures, data display options, and computed metrics; also, each of the computed metrics has been analyzed in terms of its adherence to the American Diabetes Association (ADA) 2017 international consensus on CGM data analysis and the ADA 2019 international consensus on time in range. Eventually, the agreement between metrics computed by different software and tools has been investigated. Based on such comparison, usability and complexity of data management, as well as the possibility to perform customized or patients-group analyses, have been discussed by highlighting limitations and strengths, also in relation to possible different user categories (i.e., patients, clinicians, researchers). The information provided could be useful to researchers interested in working in the diabetic research field as to clinicians and endocrinologists who need tools capable of handling CGM data effectively.
Collapse
Affiliation(s)
- Agnese Piersanti
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
| | - Francesco Giurato
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
| | - Christian Göbl
- Department of Obstetrics and Gynaecology, Medical University of Vienna, Vienna, Austria
| | - Laura Burattini
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
| | - Andrea Tura
- CNR Institute of Neuroscience, Padova, Italy
| | - Micaela Morettini
- Department of Information Engineering, Università Politecnica delle Marche, Ancona, Italy
| |
Collapse
|
6
|
Rodbard D, Garg SK. Standardizing Reporting of Glucose and Insulin Data for Patients on Multiple Daily Injections Using Connected Insulin Pens and Continuous Glucose Monitoring. Diabetes Technol Ther 2021; 23:221-226. [PMID: 33480828 DOI: 10.1089/dia.2021.0030] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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 one-page 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.
Collapse
Affiliation(s)
- David Rodbard
- Biomedical Informatics Consultants LLC, Clinical Biostatistics Department, Potomac, Maryland, USA
| | - Satish K Garg
- Barbara Davis Center for Diabetes, Departments of Medicine and Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| |
Collapse
|