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. 2022 Jul;16(4):887-895.
doi: 10.1177/19322968221093662. Epub 2022 May 9.

The Launch of the iCoDE Standard Project

Nicole Y Xu  1 , Kevin T Nguyen  1 , Ashley Y DuBord  2 , David C Klonoff  2   3 , Julian M Goldman  4 , Shahid N Shah  5 , Elias K Spanakis  6   7 , Charisse Madlock-Brown  8 , Siavash Sarlati  2   9 , Azhar Rafiq  10 , Axel Wirth  11 , David Kerr, Raman Khanna  2 , Scott Weinstein  12 , Juan Espinoza  13
Affiliations

The Launch of the iCoDE Standard Project

Nicole Y Xu et al. J Diabetes Sci Technol. 2022 Jul.

Abstract

Introduction: The first meeting of the Integration of Continuous Glucose Monitor Data into the Electronic Health Record (iCoDE) project, organized by Diabetes Technology Society, took place virtually on January 27, 2022.

Methods: Clinicians, government officials, data aggregators, attorneys, and standards experts spoke in panels and breakout groups. Three themes were covered: 1) why digital health data integration into the electronic health record (EHR) is needed, 2) what integrated continuously monitored glucose data will look like, and 3) how this process can be achieved in a way that will satisfy clinicians, healthcare organizations, and regulatory experts.

Results: The meeting themes were addressed within eight sessions: 1) What Do Inpatient Clinicians Want to See With Integration of CGM Data into the EHR?, 2) What Do Outpatient Clinicians Want to See With Integration of CGM Data into the EHR?, 3) Why Are Data Standards and Guidances Useful?, 4) What Value Can Data Integration Services Add?, 5) What Are Examples of Successful Integration?, 6) Which Privacy, Security, and Regulatory Issues Must Be Addressed to Integrate CGM Data into the EHR?, 7) Breakout Group Discussions, and 8) Presentation of Breakout Group Ideas.

Conclusions: Creation of data standards and workflow guidance are necessary components of the Integration of Continuous Glucose Monitor Data into the Electronic Health Record (iCoDE) standard project. This meeting, which launched iCoDE, will be followed by a set of working group meetings intended to create the needed standard.

Keywords: continuous glucose monitor; data integration; diabetes; digital health; electronic health record; standard.

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Conflict of interest statement

Declaration of Conflicting Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: NYX is a consultant to Abbott Diabetes Care. KTN is a consultant to Abbott Diabetes Care. DCK is a consultant to AI Health, Dexcom, Eli Lilly, EOFlow, Integrity, Lifecare, Medtronic, Novo, Roche Diagnostics, Rockley Photonics, and Thirdwayv. EKS reports that this work was supported in part by a VA MERIT award from the US Department of Veterans Affairs Clinical Sciences Research and Development Service (1I01CX001825). He has received unrestricted research support from Dexcom (to the Baltimore VA Medical Center and to the University of Maryland) for the conduction of clinical trials. SS serves as a clinical director for the Digital Care Delivery Team at Anthem Inc. for which he is compensated with salary and other benefits. DK has received remuneration for participation in Advisory Boards from Sanofi, Novo Nordisk, and Abbott Diabetes Care. He also has received research support from Novo Nordisk and Abbott Diabetes Care and has financial interests in Glooko, Hi.Health, and SNAQ. JE is a paid consultant for AI Health. AI Health played no role in the design, execution, analysis, or write up of this work. AI Health did not play a role in the decision to publish this article and had no editorial input. JE is supported by the Food and Drug Administration (FDA) under award number P50FD006425 for The West Coast Consortium for Technology & Innovation in Pediatrics (PI: Espinoza). The funding sources had no involvement in the development of this article or in the decision to submit the article for publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the FDA. AYD, JMG, SNS, CMB, AR, AW, RK, and SW have nothing relevant to disclose.

Figures

Figure 1.
Figure 1.
Opportunities to adopt, adapt, or develop standards and best practices in the CGM data pipeline. Abbreviations: CCD, Continuity of Care Documents; CDA, Clinical Document Architecture; CGM, continuous glucose monitor; CPT, Current Procedural Terminology; EHR, electronic health record; EMPI, Enterprise Master Patient Index; FHIR, Fast Healthcare Interoperability Resources; HIPAA, Health Insurance Portability and Accountability Act; HL7, Health Level 7; ICD-10, International Classification of Diseases 10th Revision; IEEE, Institute of Electrical and Electronics Engineers; LOINC, Logical Observation Identifiers Names and Codes; NIST CSF, National Institute of Standards and Technology Cybersecurity Framework; NPI, National Provider Identifier; OMOP, Observational Medical Outcomes Partnership; SMART, Substitutable Medical Applications, Reusable Technologies; SNOMED, Systemized Nomenclature of Medicine; SOC2, System and Organization Controls type 2 – Trust Services Criteria; UDI, Unique Device Identifier.
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