A GDPR-Compliant Dynamic Consent Mobile Application for the Australasian Type-1 Diabetes Data Network

Australia has a high prevalence of diabetes, with approximately 1.2 million Australians diagnosed with the disease. In 2012, the Australasian Diabetes Data Network (ADDN) was established with funding from the Juvenile Diabetes Research Foundation (JDRF). ADDN is a national diabetes registry which captures longitudinal information about patients with type-1 diabetes (T1D). Currently, the ADDN data are directly contributed from 42 paediatric and 17 adult diabetes centres across Australia and New Zealand, i.e., where the data are pre-existing in hospital systems and not manually entered into ADDN. The historical data in ADDN have been de-identified, and patients are initially afforded the opportunity to opt-out of being involved in the registry; however, moving forward, there is an increased demand from the clinical research community to utilise fully identifying data. This raises additional demands on the registry in terms of security, privacy, and the nature of patient consent. General Data Protection Regulation (GDPR) is an increasingly important mechanism allowing individuals to have the right to know about their health data and what those data are being used for. This paper presents a mobile application being designed to support the ADDN data collection and usage processes and aligning them with GDPR. The app utilises Dynamic Consent-an informed specific consent model, which allows participants to view and modify their research-driven consent decisions through an interactive interface. It focuses specifically on supporting dynamic opt-in consent to both the registry and to associated sub-projects requesting access to and use of the patient data for research purposes.

Diabetic Ketoacidosis at Onset of Type 1 Diabetes and Long-term HbA1c in 7,961 Children and Young Adults in the Australasian Diabetes Data Network

OBJECTIVE

The relationship between diabetic ketoacidosis (DKA) at diagnosis of type 1 diabetes and long-term glycemic control varies between studies. We aimed, firstly, to characterize the association of DKA and its severity with long-term HbA1c in a large contemporary cohort, and secondly, to identify other independent determinants of long-term HbA1c.

RESEARCH DESIGN AND METHODS

Participants were 7,961 children and young adults diagnosed with type 1 diabetes by age 30 years from 2000 to 2019 and followed prospectively in the Australasian Diabetes Data Network (ADDN) until 31 December 2020. Linear mixed-effect models related variables to HbA1c.

RESULTS

DKA at diagnosis was present in 2,647 participants (33.2%). Over a median 5.6 (interquartile range 3.2, 9.4) years of follow-up, participants with severe, but not moderate or mild, DKA at diagnosis had a higher mean HbA1c (+0.23%, 95% CI 0.11,0.28; [+2.5 mmol/mol, 95% CI 1.4,3.6]; P < 0.001) compared with those without DKA. Use of continuous subcutaneous insulin infusion (CSII) was independently associated with a lower HbA1c (-0.28%, 95% CI -0.31, -0.25; [-3.1 mmol/mol, 95% CI -3.4, -2.8]; P < 0.001) than multiple daily injections, and CSII use interacted with severe DKA to lower predicted HbA1c. Indigenous status was associated with higher HbA1c (+1.37%, 95% CI 1.15, 1.59; [+15.0 mmol/mol, 95% CI 12.6, 17.4]; P < 0.001), as was residing in postcodes of lower socioeconomic status (most vs. least disadvantaged quintile +0.43%, 95% CI 0.34, 0.52; [+4.7 mmol/mol, 95% CI 3.4, 5.6]; P < 0.001).

CONCLUSIONS

Severe, but not mild or moderate, DKA at diagnosis was associated with a marginally higher HbA1c over time, an effect that was modified by use of CSII. Indigenous status and lower socioeconomic status were independently associated with higher long-term HbA1c.