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Open-source automated insulin delivery: international consensus statement and practical guidance for health-care professionals.

ABSTRACT: Open-source automated insulin delivery systems, commonly referred to as do-it-yourself automated insulin delivery systems, are examples of user-driven innovations that were co-created and supported by an online community who were directly affected by diabetes. Their uptake continues to increase globally, with current estimates suggesting several thousand active users worldwide. Real-world user-driven evidence is growing and provides insights into safety and effectiveness of these systems. The aim of this consensus statement is two-fold. Firstly, it provides a review of the current evidence, description of the technologies, and discusses the ethics and legal considerations for these systems from an international perspective. Secondly, it provides a much-needed international health-care consensus supporting the implementation of open-source systems in clinical settings, with detailed clinical guidance. This consensus also provides important recommendations for key stakeholders that are involved in diabetes technologies, including developers, regulators, and industry, and provides medico-legal and ethical support for patient-driven, open-source innovations.

SUBMITTER: Braune K

PROVIDER: S-EPMC8720075 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Open-source automated insulin delivery: international consensus statement and practical guidance for health-care professionals.

Braune Katarina K Lal Rayhan A RA Petruželková Lenka L Scheiner Gary G Winterdijk Per P Schmidt Signe S Raimond Linda L Hood Korey K KK Riddell Michael C MC Skinner Timothy C TC Raile Klemens K Hussain Sufyan S

The lancet. Diabetes & endocrinology 20211113 1

Open-source automated insulin delivery systems, commonly referred to as do-it-yourself automated insulin delivery systems, are examples of user-driven innovations that were co-created and supported by an online community who were directly affected by diabetes. Their uptake continues to increase globally, with current estimates suggesting several thousand active users worldwide. Real-world user-driven evidence is growing and provides insights into safety and effectiveness of these systems. The ai ...[more]

PMID: 34785000

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Project description:Background: Loop is an open-source automated insulin delivery (AID) system, used by more than 9,000 people with type 1 diabetes. Understanding the pros and cons of Loop use may help improve disease management and support population level innovation. Methods: Focus groups revealed 72 new and existing users' perspectives on Loop uptake, use, and persistence. A subsample of participants from a mixed-methods, observational cohort study shared first-hand accounts of their experiences using Loop. Participants were predominately white (95%), male (50%), privately insured (94%), and reported annual household income ≥$100K (73%) and education exceeding a bachelor's degree (87%) with a mean HbA1c of 6.6% ± 0.8%. Data were analyzed and synthesized by a multidisciplinary team. Results: Participants detailed their experiences with (1) Loop technical support and troubleshooting, (2) decreased mental/behavioral burden, (3) technical issues with parts of the system, (4) glycemic control, (5) personalizing settings, and (6) providers while using Loop. Decreased burden was the most endorsed benefit defined by less worry, stress, and cognitive effort and less time spent on diabetes management tasks. Participants highlighted the benefits of Loop overnight and their introduction to "Loop communities" during use. The most discussed challenges involved technical issues. A range of provider attitudes and knowledge about Loop complicated users' clinical experiences and disclosure. Conclusions: This sample of new and experienced Loop users reported benefits to quality of life and glycemic control that outweighed challenges of setting up system components, customizing the system to suit one's lifestyle and habits, and adjusting system settings. Challenges related to system setup and calibrating settings are remediable and, if addressed, may better serve Loop users. Users reported feeling empowered by the customizability of and the educational effects facilitated by the open-source AID system. Loop helped users learn more about their chronic illness and physiology in an acceptable format. Clinical Trial Registration number: NCT03838900.

Dataset Information

Open-source automated insulin delivery: international consensus statement and practical guidance for health-care professionals.

Publications

Open-source automated insulin delivery: international consensus statement and practical guidance for health-care professionals.

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