Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: Diabetes technology use is associated with favorable type 1 diabetes (T1D) outcomes. American youth with public insurance, a proxy for low socioeconomic status, use less diabetes technology than those with private insurance. We aimed to evaluate the role of insurance-mediated provider implicit bias, defined as the systematic discrimination of youth with public insurance, on diabetes technology recommendations for youth with T1D in the United States.
Methods: Multi-disciplinary pediatric diabetes providers completed a bias assessment comprised of a clinical vignette and ranking exercises ( = 39). Provider bias was defined as providers: (1) recommending more technology for those on private insurance versus public insurance or (2) ranking insurance in the top 2 of 7 reasons to offer technology. Bias and provider characteristics were analyzed with descriptive statistics, group comparisons, and multivariate logistic regression.
Results: The majority of providers [44.1 ± 10.0 years old, 83% female, 79% non-Hispanic white, 49% physician, 12.2 ± 10.0 practice-years] demonstrated bias ( = 33/39, 84.6%). Compared to the group without bias, the group with bias had practiced longer (13.4±10.4 years vs 5.7 ± 3.6 years, = .003) but otherwise had similar characteristics including age (44.4 ± 10.2 vs 42.6 ± 10.1, p = 0.701). In the logistic regression, practice-years remained significant (OR = 1.47, 95% CI [1.02,2.13]; = .007) when age, sex, race/ethnicity, provider role, percent public insurance served, and workplace location were included.
Conclusions: Provider bias to recommend technology based on insurance was common in our cohort and increased with years in practice. There are likely many reasons for this finding, including healthcare system drivers, yet as gatekeepers to diabetes technology, providers may be contributing to inequities in pediatric T1D in the United States.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8442183 | PMC |
http://dx.doi.org/10.1177/19322968211006476 | DOI Listing |
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