Dataset Information

Automated Insulin Delivery in Real Life (AID-IRL): Real-World User Perspectives on Commercial AID.

ABSTRACT: Commercial automated insulin delivery (AID) systems are usually assessed based on clinical outcomes, ignoring uptake. A qualitative study evaluated user experiences when switching to currently available commercial AID. Interview feedback was coded on key themes including the adoption experience with regards to quality of life, clinical outcomes, and users' expectations. Most felt their learning curve was easy. Most saw reduced hypoglycemia and increased time in range, although there were outliers. Many mentioned post-meal hyperglycemia as an improvement area for commercial AID. Users with one particular continuous glucose monitor (CGM) type reported sleep disruption. Companies should consider real-world user feedback with regards to improving training materials for new users with less CGM experience and by improving target flexibility and postprandial algorithm performance, plus reducing manual interventions required by users.

SUBMITTER: Lewis D

PROVIDER: S-EPMC8861778 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Automated Insulin Delivery in Real Life (AID-IRL): Real-World User Perspectives on Commercial AID.

Lewis Dana D

Journal of diabetes science and technology 20200916 2

Commercial automated insulin delivery (AID) systems are usually assessed based on clinical outcomes, ignoring uptake. A qualitative study evaluated user experiences when switching to currently available commercial AID. Interview feedback was coded on key themes including the adoption experience with regards to quality of life, clinical outcomes, and users' expectations. Most felt their learning curve was easy. Most saw reduced hypoglycemia and increased time in range, although there were outlier ...[more]

PMID: 32935554

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Project description:Objective: Pivotal trials of automated insulin delivery (AID) closed-loop systems have demonstrated a consistent picture of glycemic benefit, supporting approval of multiple systems by the Food and Drug Administration or Conformité Européenne mark receipt. To assess how pivotal trial findings translate to commercial AID use, a systematic review of retrospective real-world studies was conducted. Methods: PubMed and EMBASE were searched for articles published after 2018 with more than five nonpregnant individuals with type 1 diabetes (T1D). Data were screened/extracted in duplicate for sample size, AID system, glycemic outcomes, and time in automation. Results: Of 80 studies identified, 20 met inclusion criteria representing 171,209 individuals. Time in target range 70-180 mg/dL (3.9-10.0 mmol/L) was the primary outcome in 65% of studies, with the majority of reports (71%) demonstrating a >10% change with AID use. Change in hemoglobin A1c (HbA1c) was reported in nine studies (range 0.1%-0.9%), whereas four reported changes in glucose management indicator (GMI) with a 0.1%-0.4% reduction noted. A decrease in HbA1c or GMI of >0.2% was achieved in two-thirds of the studies describing change in HbA1c and 80% of articles where GMI was described. Time below range <70 mg/dL (<3.9 mmol/L) was reported in 16 studies, with all but 1 study showing stable or reduced levels. Most systems had >90% time in automation. Conclusion: With larger and more diverse populations, and follow-up periods of longer duration (∼9 months vs. 3-6 months for pivotal trials), real-world retrospective analyses confirm pivotal trial findings. Given the glycemic benefits demonstrated, AID is rapidly becoming the standard of care for all people living with T1D. Individuals should be informed of these systems and differences between them, have access to and coverage for these technologies, and receive support as they integrate this mode of insulin delivery into their lives.

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

Automated Insulin Delivery in Real Life (AID-IRL): Real-World User Perspectives on Commercial AID.

Publications

Automated Insulin Delivery in Real Life (AID-IRL): Real-World User Perspectives on Commercial AID.

Similar Datasets

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