Relationships Between Socioeconomic Status, Insurance Coverage for Diabetes Technology and Adverse Health in Patients With Type 1 Diabetes

Author:

Everett Estelle M.123ORCID,Wisk Lauren E.2ORCID

Affiliation:

1. Department of Medicine, Division of Endocrinology, Diabetes, & Metabolism, David Geffen School of Medicine, University of California, Los Angeles, CA, USA

2. Department of Medicine, Division of General Internal Medicine & Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, CA, USA

3. VA Greater Los Angeles Healthcare System, Los Angeles, CA, USA

Abstract

Introduction: Insulin pumps and continuous glucose monitors (CGM) have many benefits in the management of type 1 diabetes. Unfortunately disparities in technology access occur in groups with increased risk for adverse effects (eg, low socioeconomic status [SES], public insurance). Research Design & Methods: Using 2015 to 2016 data from 4,895 participants from the T1D Exchange Registry, a structural equation model (SEM) was fit to explore the hypothesized direct and indirect relationships between SES, insurance features, access to diabetes technology, and adverse clinical outcomes (diabetic ketoacidosis, hypoglycemia). SEM was estimated using the maximum likelihood method and standardized path coefficients are presented. Results: Higher SES and more generous insurance coverage were directly associated with CGM use (β = 1.52, SE = 0.12, P < .0001 and β = 1.21, SE = 0.14, P < .0001, respectively). Though SES displayed a small inverse association with pump use (β = -0.11, SE = 0.04, P = .0097), more generous insurance coverage displayed a stronger direct association with pump use (β = 0.88, SE = 0.10, P < .0001). CGM use and pump use were both directly associated with fewer adverse outcomes (β = -0.23, SE = 0.06, P = .0002 and β = -0.15, SE = 0.04, P = .0002, respectively). Both SES and insurance coverage demonstrated significant indirect effects on adverse outcomes that operated through access to diabetes technology (β = -0.33, SE = 0.09, P = .0002 and β = -0.40, SE = 0.09, P < .0001, respectively). Conclusions: The association between SES and insurance coverage and adverse outcomes was primarily mediated through diabetes technology use, suggesting that disparities in diabetes outcomes have the potential to be mitigated by addressing the upstream disparities in technology use.

Funder

National Institute of Diabetes and Digestive and Kidney Diseases

Publisher

SAGE Publications

Subject

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

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