Racial Disparities in Diabetes Technology Use and Outcomes in Type 1 Diabetes in a Safety-Net Hospital

Fantasia, Kathryn L.; Wirunsawanya, Kamonkiat; Lee, Christopher; Rizo, Ivania

doi:10.1177/1932296821995810

Cited by 35 publications

(23 citation statements)

References 40 publications

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“…Our findings are comparable to previously published literature. [22][23][24] The greatest variation was observed with CSII use. A key reason may be the variation observed in structured education uptake; the percentage of people completing structured education in the least deprived group was almost double that of the most deprived group.…”

Section: Discussionmentioning

confidence: 99%

“…These findings support previous literature stating that racial and ethnic minorities are less likely to use healthrelated technology. 8,24,31 Our study has several strengths and is one of few studies to specifically report on the impact of social deprivation on pre-and post-rtCGM and isCGM HbA 1c . Furthermore, this study consisted of a large multi-ethnic cohort living across a wide range of different deprivation quintiles, providing a prime representative population to evaluate deprivation-based health disparities.…”

Section: Discussionmentioning

confidence: 99%

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The impact of socio‐economic deprivation on access to diabetes technology in adults with type 1 diabetes

et al. 2022

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Background With advances in technology, there is an emerging concern that inequalities exist in provision and diabetes outcomes in areas of greater deprivation. We assess the relationship between socio‐economic status and deprivation with access to diabetes technology and their outcomes in adults with type 1 diabetes. Methods Retrospective, observational analysis of adults attending a tertiary centre, comprising three urban hospitals in the UK. Socio‐economic deprivation was assessed by the English Indices of Deprivation 2019. Data analysis was performed using one‐way ANOVAs and chi‐squared tests. Results In total, 1631 adults aged 44 ± 15 years and 758 (47%) women were included, with 391 (24%) using continuous subcutaneous insulin infusion, 312 (19%) using real‐time continuous glucose monitoring and 558 (34%) using intermittently scanned continuous glucose monitoring. The highest use of diabetes technology was in the least deprived quintile compared to the most deprived quintile (67% vs. 45%, respectively; p < 0.001). HbA1c outcomes were available in 400 participants; no association with deprivation was observed (p = 0.872). Participation in structured education was almost twice as high from the most deprived to the least deprived groups (23% vs. 43%; p < 0.001). Adults with white or mixed ethnicity were more likely to use technology compared to black ethnicity (60% vs. 40%; p < 0.001). Conclusions Adults living in the most deprived quintile had less technology use. Irrespective of socio‐economic status or ethnicity, glycaemia was positively affected in all groups. It is imperative that health disparities are further addressed.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

The impact of socio‐economic deprivation on access to diabetes technology in adults with type 1 diabetes

et al. 2022

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“…Additionally, the T1DX‐QI intentionally partners with endocrinology clinics serving diverse populations. Two recently contracted clinics reside in urban safety‐net hospitals which primarily serve underserved and vulnerable populations, including communities of color, families whose primary language is not English, and un‐ or underinsured individuals 20 …”

Section: T1dx‐qi Approaches To Addressing Health Inequities In the Un...mentioning

confidence: 99%

Addressing type 1 diabetes health inequities in the United States: Approaches from the T1D Exchange QI Collaborative

Ebekozien

Mungmode

Odugbesan

et al. 2021

Journal of Diabetes

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Approximately 1.6 million people in the United States have type 1 diabetes (T1D). 1 The incidence of T1D is increasing in the United States across all populations, most significantly among Hispanic and non-Hispanic Black (NHB) patients. 2,3 Unfortunately, widespread inequities exist in health outcomes among patients with T1D in the United States. [4][5][6][7] In 2016, the T1D Exchange Quality Improvement Collaborative (T1DX-QI) was established. 8 T1DX-QI is a learning health network 9 with over 40 centers across the United States. Participating centers use continuous quality improvement (QI) methods [10][11][12] and real-world electronic medical record (EMR) data 4,6 for T1D population health improvement.The T1DX-QI is coordinated by the T1D Exchange, a Boston-based nonprofit coordinating center. The goals of the T1DX-QI were described in a separate commentary. 13 The T1DX-QI has successfully used QI principles and implementation science to improve clinical processes, including increased use of continuous glucose monitors (CGM), insulin pumps, depression screening, improved access to care, and population-level glycemic outcomes. [9][10][11][12] In 2020, the T1DX-QI established its health equity program to address inequities systematically and comprehensively in T1D outcomes. 14 This commentary describes practical approaches being employed by the T1DX-QI to address health inequities. These approaches can be Robert Rapaport and Manmohan Kamboj are co-senior authors.

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“…Access to these technological advances is less than optimal in patients with T1D from racial-ethnic minority populations. [7][8][9] Many study authors report socioeconomic status and insurance as reasons for low use, 7 yet racial-ethnic inequities have been identified when controlling for income and insurance status. 3,9,10 This suggests that additional factors besides socioeconomic status and insurance contribute to the problem.…”

mentioning

confidence: 99%

“…Of concern, not all patients have access to and/or use these technological advances. Access to these technological advances is less than optimal in patients with T1D from racial-ethnic minority populations 7–9 . Many study authors report socioeconomic status and insurance as reasons for low use, 7 yet racial-ethnic inequities have been identified when controlling for income and insurance status 3,9,10 .…”

mentioning

confidence: 99%

Racial-Ethnic Disparities in Technology Use and Healthcare in Persons With Type 1 Diabetes

Martyn‐Nemeth

Hayman

2022

J Cardiovasc Nurs

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Racial Disparities in Diabetes Technology Use and Outcomes in Type 1 Diabetes in a Safety-Net Hospital

Cited by 35 publications

References 40 publications

The impact of socio‐economic deprivation on access to diabetes technology in adults with type 1 diabetes

The impact of socio‐economic deprivation on access to diabetes technology in adults with type 1 diabetes

Addressing type 1 diabetes health inequities in the United States: Approaches from the T1D Exchange QI Collaborative

Racial-Ethnic Disparities in Technology Use and Healthcare in Persons With Type 1 Diabetes

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