Open-source automated insulin delivery systems and formal healthcare: A qualitative study of challenges in the interaction between service-users with type 1 diabetes and healthcare professionals.

OBJECTIVES: To explore the challenges that open-source automated insulin delivery systems pose to the encounter between service-users and healthcare professionals and how these challenges might be addressed in the future. METHODS: Five adult service-users and six healthcare professionals participated in semi-structured interviews. A six-step thematic analysis was conducted, the focus being on challenges and needs for improvement of the interactions. RESULTS: The analysis revealed three overarching challenges and wishes: (1) Lack of exchange of experiences. Service-users are reticent about disclosing their use of the systems to healthcare professionals. (2) Unclear ethical responsibility. Service-users are aware of their responsibility and guidelines can help to alleviate healthcare professional's legal responsibility; however, ambiguities around ethical responsibility for healthcare professionals remain an impediment to meaningful clinical interactions. (3) Unresolved individual and mutual expectations. Service-users expect better access to technology and focus on psychosocial aspects. In contrast, healthcare professionals fear the burden associated with the rising technical expectations. CONCLUSION: Transparency and openness towards open-source systems need to be part of service-user and healthcare professionals interaction. Requirements for future care include improved knowledge about the systems, an openminded approach towards user-driven initiatives among healthcare professionals, and a focus on psychosocial aspects in the interaction.

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

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.

Flash glucose monitoring and automated bolus calculation in type 1 diabetes treated with multiple daily insulin injections: a 26 week randomised, controlled, multicentre trial.

AIMS/HYPOTHESIS: We aimed to compare the effects of intermittently scanned continuous glucose monitoring (isCGM) and carbohydrate counting with automated bolus calculation (ABC) with usual care. METHODS: In a randomised, controlled, open-label trial carried out at five diabetes clinics in the Capital Region of Denmark, 170 adults with type 1 diabetes for ≥1 year, multiple daily insulin injections and HbA1c > 53 mmol/mol (7.0%) were randomly assigned 1:1:1:1 with centrally prepared envelopes to usual care (n = 42), ABC (n = 41), isCGM (n = 48) or ABC+isCGM (n = 39). Blinded continuous glucose monitoring data, HbA1c and patient-reported outcomes were recorded at baseline and after 26 weeks. The primary outcome was change in time in range using isCGM vs usual care. RESULTS: Baseline characteristics were comparable across arms: mean age 47 (SD 13.7) years, median (IQR) diabetes duration 18 (10-28) years and HbA1c 65 (61-72) mmol/mol (8.1% [7.7-8.7%]). Change in time in range using isCGM was comparable to usual care (% difference of 3.9 [-12-23], p = 0.660). The same was true for the ABC and ABC+isCGM arms and for hypo- and hyperglycaemia. Also compared with usual care, using ABC+isCGM reduced HbA1c (4 [95% CI 1, 8] mmol/mol) (0.4 [0.1, 0.7] %-point) and glucose CV (11% [4%, 17%]) and improved treatment satisfaction, psychosocial self-efficacy and present life quality. Treatment satisfaction also improved by using isCGM alone vs usual care. Statistical significance was maintained after multiple testing adjustment concerning glucose CV and treatment satisfaction with ABC+isCGM, and treatment satisfaction with isCGM. Discontinuation was most common among ABC only users, and among completers the ABC was used 4 (2-5) times/day and the number of daily isCGM scans was 5 (1-7) at study end. CONCLUSIONS/INTERPRETATION: isCGM alone did not improve time in range, but treatment satisfaction increased in technology-naive people with type 1 diabetes and suboptimal HbA1c. The combination of ABC+isCGM appears advantageous regarding glycaemic variables and patient-reported outcomes, but many showed resistance towards ABC. TRIAL REGISTRATION: ClinicalTrials.gov NCT03682237. FUNDING: The study is investigator initiated and financed by the Capital Region of Denmark.

Efficacy of Bolus Calculation and Advanced Carbohydrate Counting in Type 2 Diabetes: A Randomized Clinical Trial.

Background: Carbohydrate counting and use of automated bolus calculators (ABCs) can help reduce HbA1c in type 1 diabetes but only limited evidence exists in type 2 diabetes. We evaluated the efficacy of advanced carbohydrate counting (ACC) and use of an ABC compared with manual insulin bolus calculation (MC) in persons with type 2 diabetes. Materials and Methods: A 24-week open-label, randomized clinical study was conducted in 79 persons with type 2 diabetes treated with basal-bolus insulin (mean age 62.5 ± 9.6 years, HbA1c 8.7% ± 1.0% [72 ± 11 mmol/mol], diabetes duration 18.7 ± 7.6 years). Participants were randomized 1:1 into two groups: ABC group received training in ACC and use of an ABC; MC group received training in ACC and manual calculation of insulin bolus. Participants wore blinded continuous glucose monitors for 6 days at baseline and at study end. Primary endpoint was change in HbA1c. Results: After 24 weeks, HbA1c decreased 0.8% (8.8 mmol/mol) in ABC group and 0.8% (9.0 mmol/mol) in MC group with no between-group difference (P = 0.96) and without increase in time in hypoglycemic range (sensor glucose <3.9 mmol/L). Glycemic variability decreased significantly in both groups, whereas the total insulin dose and body mass index (BMI) remained unchanged during the study. Treatment satisfaction increased significantly in both groups after 24 weeks. Conclusion: ACC is an effective, low-cost tool to reduce HbA1c and glycemic variability in persons with basal-bolus insulin-treated type 2 diabetes without increase in hypoglycemia or BMI. Similar effects were seen with use of an ABC and with use of manual bolus calculation. Trial registration: ClinicalTrials.gov NCT02887898.