A Three-Step Data-Driven Methodology to Assess Adherence to Basal Insulin Therapy in Patients With Insulin-Treated Type 2 Diabetes

Author:

Nørlev Jannie Toft Damsgaard12ORCID,Kronborg Thomas12ORCID,Jensen Morten Hasselstrøm13,Vestergaard Peter245,Hejlesen Ole1,Hangaard Stine12ORCID

Affiliation:

1. Department of Health Science and Technology, Faculty of Medicine, Aalborg University, Gistrup, Denmark

2. Steno Diabetes Center North Denmark, Aalborg, Denmark

3. Data Science, Novo Nordisk A/S, Søborg, Denmark

4. Department of Clinical Medicine, Aalborg University, Aalborg, Denmark

5. Department of Endocrinology, Aalborg University Hospital, Aalborg, Denmark

Abstract

Background: While health care providers (HCPs) are generally aware of the challenges concerning insulin adherence in adults with insulin-treated type 2 diabetes (T2D), data guiding identification of insulin nonadherence and understanding of injection patterns have been limited. Hence, the aim of this study was to examine detailed injection data and provide methods for assessing different aspects of basal insulin adherence. Method: Basal insulin data recorded by a connected insulin pen and prescribed doses were collected from 103 insulin-treated patients (aged ≥18 years) with T2D from an ongoing clinical trial (NCT04981808). We categorized the data and analyzed distributions of correct doses, increased doses, reduced doses, and missed doses to quantify adherence. We developed a three-step model evaluating three aspects of adherence (overall adherence, adherence distribution, and dose deviation) offering HCPs a comprehensive assessment approach. Results: We used data from a connected insulin pen to exemplify the use of the three-step model to evaluate overall, adherence, adherence distribution, and dose deviation using patient cases. Conclusion: The methodology provides HCPs with detailed access to previously limited clinical data on insulin administration, making it possible to identify specific nonadherence behavior which will guide patient-HCP discussions and potentially provide valuable insights for tailoring the most appropriate forms of support.

Publisher

SAGE Publications

Subject

Biomedical Engineering,Bioengineering,Endocrinology, Diabetes and Metabolism,Internal Medicine

Reference28 articles.

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