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Cited by 121Diabetes Management and ResearchDiabetes Management and EducationHealth disparities and outcomes

Barriers to Technology Use and Endocrinology Care for Underserved Communities With Type 1 Diabetes

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Walker, Ashby F., Hood, Korey K., Gurka, Matthew J., Filipp, Stephanie L., Anez-Zabala, Claudia, Cuttriss, Nicolas, Haller, Michael J., Roque, Xanadu +11 more·2021·Diabetes Care
DOI 10.2337/dc20-2753PMC PMC8323174
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Abstract

OBJECTIVE: Disparities in type 1 diabetes related to use of technologies like continuous glucose monitors (CGMs) and utilization of diabetes care are pronounced based on socioeconomic status (SES), race, and ethnicity. However, systematic reports of perspectives from patients in vulnerable communities regarding barriers are limited. RESEARCH DESIGN AND METHODS: To better understand barriers, focus groups were conducted in Florida and California with adults ≥18 years old with type 1 diabetes with selection criteria including hospitalization for diabetic ketoacidosis, HbA1c >9%, and/or receiving care at a Federally Qualified Health Center. Sixteen focus groups were conducted in English or Spanish with 86 adults (mean age 42 ± 16.2 years). Transcript themes and pre–focus group demographic survey data were analyzed. In order of frequency, barriers to diabetes technology and endocrinology care included 1) provider level (negative provider encounters), 2) system level (financial coverage), and 3) individual level (preferences). RESULTS: Over 50% of participants had not seen an endocrinologist in the past year or were only seen once including during hospital visits. In Florida, there was less technology use overall (38% used CGMs in FL and 63% in CA; 43% used pumps in FL and 69% in CA) and significant differences in pump use by SES (P = 0.02 in FL; P = 0.08 in CA) and race/ethnicity (P = 0.01 in FL; P = 0.80 in CA). In California, there were significant differences in CGM use by race/ethnicity (P = 0.05 in CA; P = 0.56 in FL) and education level (P = 0.02 in CA; P = 0.90 in FL). CONCLUSIONS: These findings provide novel insights into the experiences of vulnerable communities and demonstrate the need for multilevel interventions aimed at offsetting disparities in diabetes.

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  • Health care providers may be less likely to recommend insulin pump therapy or AID to socially disadvantaged groups, fearing these groups may not use these devices safely and develop DKA.

    “Health care providers may be less likely to recommend insulin pump therapy or AID to socially disadvantaged groups, fearing these groups may not use these devices safely and develop DKA.”

    From Social disadvantage and technology use among adults with type 1 diabetes in Quebec: A cross‐sectional study using data from the Canadian <scp>T1D</scp> ( <scp>BETTER</scp> ) Registry (2025) · cites this paper as [13]

    The Results (focus-group findings; page unavailable) report that endocrinologists sometimes blocked or discouraged pump use, citing poor glycemic control or implying that a device would be too difficult for a participant to handle. The paper does not establish that providers feared diabetic ketoacidosis from unsafe device use, and the cited passages do not address AID specifically. (LLM, conf=0.87)

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Research works printed but not linked: 32

  1. [1]Foster NC, Beck RW, Miller KM,. State of type 1 diabetes management and outcomes from the T1D Exchange in 2016-2018. Diabetes Technol Ther 2019; 21: 66– 72 30657336 PMC7061293
  2. [2]Secrest AM, Costacou T, Gutelius B, Miller RG, Songer TJ, Orchard TJ. Association of socioeconomic status with mortality in type 1 diabetes: the Pittsburgh epidemiology of diabetes complications study. Ann Epidemiol 2011; 21: 367– 373 21458730 PMC3070912
  3. [4]Cutfield SW, Derraik JG, Reed PW, Hofman PL, Jefferies C, Cutfield WS. Early markers of glycaemic control in children with type 1 diabetes mellitus. PLoS One 2011; 6: e25251 21966469 PMC3180292
  4. [5]Keenan HT, Foster CM, Bratton SL. Social factors associated with prolonged hospitalization among diabetic children. Pediatrics 2002; 109: 40– 44 11773540
  5. [6]Scott A, Chambers D, Goyder E, O’Cathain A. Socioeconomic inequalities in mortality, morbidity and diabetes management for adults with type 1 diabetes: a systematic review. PLoS One 2017; 12: e0177210 28489876 PMC5425027
  6. [7]Hill KE, Gleadle JM, Pulvirenti M, McNaughton DA. The social determinants of health for people with type 1 diabetes that progress to end-stage renal disease. Health Expect 2015; 18: 2513– 2521 24938493 PMC5810664
  7. [8]Scott A, O’Cathain A, Goyder E. Socioeconomic disparities in access to intensive insulin regimens for adults with type 1 diabetes: a qualitative study of patient and healthcare professional perspectives. Int J Equity Health 2019; 18: 150 31604437 PMC6788115
  8. [10]Rawshani A, Svensson AM, Rosengren A, Eliasson B, Gudbjörnsdottir S. Impact of socioeconomic status on cardiovascular disease and mortality in 24,947 individuals with type 1 diabetes. Diabetes Care 2015; 38: 1518– 1527 25972573
  9. [11]Toppe C, Möllsten A, Schön S, Dahlquist G. Socio-economic factors influencing the development of end-stage renal disease in people with type 1 diabetes - a longitudinal population study. Diabet Med 2017; 34: 676– 682 27862276
  10. [12]Anderson SG, Malipatil NS, Roberts H, Dunn G, Heald AH. Socioeconomic deprivation independently predicts symptomatic painful diabetic neuropathy in type 1 diabetes. Prim Care Diabetes 2014; 8: 65– 69 24211151
  11. [14]Saydah S, Imperatore G, Cheng Y, Geiss LS, Albright A. Disparities in diabetes deaths among children and adolescents - United States, 2000. MMWR Morb Mortal Wkly Rep 2017; 66: 502– 505 28520705 PMC5657647
  12. [15]Petitti DB, Klingensmith GJ, Bell RA,.; SEARCH for Diabetes in Youth Study Group. Glycemic control in youth with diabetes: the SEARCH for diabetes in Youth Study. J Pediatr 2009; 155: 668– 72.e1, 3 19643434 PMC4689142
  13. [17]Agarwal S, Kanapka LG, Raymond JK,. Racial-ethnic inequity in young adults with type 1 diabetes. J Clin Endocrinol Metab 2020; 105: e2960– e2969 PMC7457963 32382736
  14. [19]Holman N, Knighton P, Kar P,. Risk factors for COVID-19-related mortality in people with type 1 and type 2 diabetes in England: a population-based cohort study. Lancet Diabetes Endocrinol 2020; 8: 823– 833 32798471 PMC7426091
  15. [20]Riddle MC, Buse JB, Franks PW,. COVID-19 in people with diabetes: urgently needed lessons from early reports. Diabetes Care 2020; 43: 1378– 1381 32409505 PMC7305002
  16. [21]Centers for Disease Control and Prevention. COVID-19. People with Certain Medical Conditions. Accessed 28 September 2020. Available from https://cdc.gov/coronavirus/2019-ncov/need-extra-precautions/people-with-medical-conditions.html#diabetes 34009770
  17. [25]Sherr JL, Hermann JM, Campbell F,.; T1D Exchange Clinic Network, the DPV Initiative, and the National Paediatric Diabetes Audit and the Royal College of Paediatrics and Child Health registries. Use of insulin pump therapy in children and adolescents with type 1 diabetes and its impact on metabolic control: comparison of results from three large, transatlantic paediatric registries. Diabetologia 2016; 59: 87– 91 26546085
  18. [27]Sherr JL, Tauschmann M, Battelino T,. ISPAD clinical practice consensus guidelines 2018: Diabetes technologies. Pediatr Diabetes 2018; 19(Suppl. 27): 302– 325 30039513
  19. [28]Addala A, Auzanneau M, Miller K,. A decade of disparities in diabetes technology use and HbA1c in pediatric type 1 diabetes: a transatlantic comparison. Diabetes Care 2021; 44: 133– 140 32938745 PMC8162452
  20. [29]Pettus JH, Zhou FL, Shepherd L,. Incidences of severe hypoglycemia and diabetic ketoacidosis and prevalence of microvascular complications stratified by age and glycemic control in U.S. adult patients with type 1 diabetes: a real-world study. Diabetes Care 2019; 42: 2220– 2227 31548241
  21. [30]Shenkman E, Tian L, Nackashi J, Schatz D. Managed care organization characteristics and outpatient specialty care use among children with chronic illness. Pediatrics 2005; 115: 1547– 1554 15930215
  22. [31]Alonso GT, Corathers S, Shah A,. Establishment of the T1D Exchange Quality Improvement Collaborative (T1DX-QI). Clin Diabetes 2020; 38: 141– 151 32327886 PMC7164986
  23. [32]Walker AF, Hu H, Cuttriss N,. The neighborhood deprivation index and provider geocoding identify critical catchment areas for diabetes outreach. J Clin Endocrinol Metab 2020; 105: 3069– 3075 PMC7418444 32676640
  24. [33]Cuttriss N, Bouchonville MF, Maahs DM, Walker AF. Tele-rounds and case-based training: Project ECHO telementoring model applied to complex diabetes care. Pediatr Clin North Am 2020; 67: 759– 772 32650871
  25. [35]Hennink MM, Kaiser BN, Weber MB. What influences saturation? Estimating sample sizes in focus group research. Qual Health Res 2019; 29: 1483– 1496 30628545 PMC6635912
  26. [36]Onwuegbuzie AJ, Dickinson WB, Leech NL, Zoran AG. A qualitative framework for collecting and analyzing data in focus group research. Int J Qual Methods 2009; 8: 1– 21
  27. [37]Bronfrenbrenner U. The Ecology of Human Development. Cambridge, Harvard Press, 1979
  28. [38]Reifsnider E, Gallagher M, Forgione B. Using ecological models in research on health disparities. J Prof Nurs 2005; 21: 216– 222 16061168
  29. [39]Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977; 33: 159– 174 843571
  30. [41]Browne JL, Ventura A, Mosely K, Speight J. ‘I'm not a druggie, I'm just a diabetic’: a qualitative study of stigma from the perspective of adults with type 1 diabetes. BMJ Open 2014; 4: e005625 PMC4120421 25056982
  31. [42]Holmes-Truscott E, Ventura AD, Thuraisingam S, Pouwer F, Speight J. Psychosocial moderators of the impact of diabetes stigma: results from the Second Diabetes MILES - Australia (MILES-2) Study. Diabetes Care 2020; 43: 2651– 2659 32887706
  32. [43]Valdovinos EM, Niedzwiecki MJ, Guo J, Hsia RY. The association of Medicaid expansion and racial/ethnic inequities in access, treatment, and outcomes for patients with acute myocardial infarction. PLoS One 2020; 15: e0241785 33175899 PMC7657521

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Authors
Walker, A. F., Hood, K. K., Gurka, M. J., Filipp, S. L., Anez-Zabala, C., Cuttriss, N., Haller, M. J., Roque, X., Naranjo, D., Aulisio, G., Addala, A., Konopack, J., Westen, S., Yabut, K., Mercado, E., Look, S., Fitzgerald, B., Maizel, J., & Maahs, D. M.
Affiliations
  • University of Florida Health (US)
  • Stanford Medicine (US)
  • University of Florida (US)
Corresponding author
Walker, Ashby F.
ORCID
Venue
Diabetes Care
Publisher
American Diabetes Association
Published
2021-05-17
Volume
44
Issue
7
Pages
1480-1490
ISSN
  • 0149-5992 (ISSN-L)
  • 1935-5548
DOI
10.2337/dc20-2753
PMC
PMC8323174
OpenAlex
W3159976361
Cited by
121
References
6
Citations by year
2026: 14 · 2025: 26 · 2024: 28 · 2023: 25 · 2022: 22 · 2021: 6
FWCI
15.12
Type
journal article
Language
en
Open access
Licence
www.diabetesjournals.org/content/license (vor)
Locations
  • Diabetes Care (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • American Diabetes Association
  • Leona M. and Harry B. Helmsley Charitable Trust
  • National Institute of Diabetes and Digestive and Kidney Diseases (K12DK122550)
Topics
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
  • Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Education
  • Social Sciences › Health › Health disparities and outcomes
Keywords
type 1 diabetes, diabetes technology, continuous glucose monitors, insulin pump, health disparities, underserved populations, socioeconomic status, race and ethnicity, diabetic ketoacidosis, federally qualified health centers, patient perspectives
MeSH terms
Adolescent, Adult, Blood Glucose, Diabetes Mellitus, Type 1, Endocrinology, Humans, Middle Aged, Technology, Blood Glucose Self-Monitoring

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