Implicit Racial-Ethnic and Insurance-Mediated Bias to Recommending Diabetes Technology: Insights from T1D Exchange Multicenter Pediatric and Adult Diabetes Provider Cohort

Ori Odugbesan, Ananta Addala, Grace Nelson, Rachel Hopkins, Kristina Cossen, Jessica Schmitt, Justin Indyk, Nana Hawa Yayah Jones, Shivani Agarwal, Saketh Rompicherla, Osagie Ebekozien

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Background: Despite documented benefits of diabetes technology in managing type 1 diabetes, inequities persist in the use of these devices. Provider bias may be a driver of inequities, but the evidence is limited. Therefore, we aimed to examine the role of race/ethnicity and insurance-mediated provider implicit bias in recommending diabetes technology. Method: We recruited 109 adult and pediatric diabetes providers across 7 U.S. endocrinology centers to complete an implicit bias assessment composed of a clinical vignette and ranking exercise. Providers were randomized to receive clinical vignettes with differing insurance and patient names as proxy for Racial-Ethnic identity. Bias was identified if providers: (1) recommended more technology for patients with an English name (Racial-Ethnic bias) or private insurance (insurance bias), or (2) Race/Ethnicity or insurance was ranked high (Racial-Ethnic and insurance bias, respectively) in recommending diabetes technology. Provider characteristics were analyzed using descriptive statistics and multivariate logistic regression. Result: Insurance-mediated implicit bias was common in our cohort (n = 66, 61%). Providers who were identified to have insurance-mediated bias had greater years in practice (5.3 ± 5.3 years vs. 9.3 ± 9 years, P = 0.006). Racial-Ethnic-mediated implicit bias was also observed in our study (n = 37, 34%). Compared with those without Racial-Ethnic bias, providers with Racial-Ethnic bias were more likely to state that they could recognize their own implicit bias (89% vs. 61%, P = 0.001). Conclusion: Provider implicit bias to recommend diabetes technology was observed based on insurance and Race/Ethnicity in our pediatric and adult diabetes provider cohort. These data raise the need to address provider implicit bias in diabetes care.

Original languageEnglish (US)
Pages (from-to)619-627
Number of pages9
JournalDiabetes Technology and Therapeutics
Volume24
Issue number9
DOIs
StatePublished - Sep 1 2022

Keywords

  • Continuous glucose monitoring
  • Insulin pumps
  • Type 1 diabetes

ASJC Scopus subject areas

  • Endocrinology, Diabetes and Metabolism
  • Endocrinology
  • Medical Laboratory Technology

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