Access to Specialty Care for Commercially Insured Youths With Type 1 and Type 2 Diabetes.

Importance: Youths with type 2 diabetes are at higher risk for complications compared with peers with type 1 diabetes, though few studies have evaluated differences in access to specialty care. Objective: To compare claims with diabetes specialists for youths with type 1 vs type 2 diabetes and the association between specialist claims with multidisciplinary and acute care utilization. Design, Setting, and Participants: This cross-sectional study used Optum Clinformatics Data Mart commercial claims. Individuals included in the study were youths younger than 19 years with type 1 or 2 diabetes as determined by a validated algorithm and prescription claims. Data were collected for youths with at least 80% enrollment in a commercial health plan from December 1, 2018, to December 31, 2019. Statistical analysis was performed from September 2022 to January 2024. Main Outcomes and Measures: The primary outcome was the number of ambulatory claims from an endocrine and/or diabetes physician or advanced practice clinician associated with a diabetes diagnosis code; secondary outcomes included multidisciplinary and acute care claims. Results: Claims were analyzed for 4772 youths (mean [SD] age, 13.6 [3.7] years; 4300 [90.1%] type 1 diabetes; 472 [9.9%] type 2 diabetes; 2465 [51.7%] male; 128 [2.7%] Asian, 303 [6.4] Black or African American, 429 [9.0%] Hispanic or Latino, 3366 [70.5%] non-Hispanic White, and 546 [11.4%] unknown race and ethnicity). Specialist claims were lower in type 2 compared with type 1 diabetes (incidence rate ratio [IRR], 0.61 [95% CI, 0.52-0.72]; P < .001) in propensity score-weighted analyses. The presence of a comorbidity was associated with increased specialist claims for type 1 diabetes (IRR, 1.07 [95% CI, 1.03-1.10]) and decreased claims for type 2 diabetes (IRR, 0.77 [95% CI, 0.67-0.87]). Pooling diagnosis groups and adjusted for covariates, each additional specialist claim was associated with increased odds of a claim with a diabetes care and education specialist (odds ratio [OR], 1.31 [95% CI, 1.25-1.36]), dietitian (OR, 1.14 [95% CI, 1.09-1.19]), and behavioral health clinician (OR, 1.16 [95% CI, 1.12-1.20]). For acute care claims, each additional specialist claim was associated with increased odds of admission (OR, 1.17 [95% CI, 1.11-1.24]) but not for emergency claims (OR, 1.03 [95% CI, 0.98-1.82]). Conclusions and Relevance: This cross-sectional study found that youths with type 2 diabetes were significantly less likely to have specialist claims despite insurance coverage, indicating other barriers to care, which may include medical complexity. Access to diabetes specialists influences engagement with multidisciplinary services. The association between increasing ambulatory clinician services and admissions suggests high utilization by a subgroup of patients at greater risk for poor outcomes.

Active surveillance pharmacovigilance for Clostridioides difficile infection and gastrointestinal bleeding: an analytic framework based on case-control studies.

BACKGROUND: Active surveillance pharmacovigilance is an emerging approach to identify medications with unanticipated effects. We previously developed a framework called pharmacopeia-wide association studies (PharmWAS) that limits false positive medication associations through high-dimensional confounding adjustment and set enrichment. We aimed to assess the transportability and generalizability of the PharmWAS framework by using medical claims data to reproduce known medication associations with Clostridioides difficile infection (CDI) or gastrointestinal bleeding (GIB). METHODS: We conducted case-control studies using Optum's de-identified Clinformatics Data Mart Database of individuals enrolled in large commercial and Medicare Advantage health plans in the United States. Individuals with CDI (from 2010 to 2015) or GIB (from 2010 to 2021) were matched to controls by age and sex. We identified all medications utilized prior to diagnosis and analysed the association of each with CDI or GIB using conditional logistic regression adjusted for risk factors for the outcome and a high-dimensional propensity score. FINDINGS: For the CDI study, we identified 55,137 cases, 220,543 controls, and 290 medications to analyse. Antibiotics with Gram-negative spectrum, including ciprofloxacin (aOR 2.83), ceftriaxone (aOR 2.65), and levofloxacin (aOR 1.60), were strongly associated. For the GIB study, we identified 450,315 cases, 1,801,260 controls, and 354 medications to analyse. Antiplatelets, anticoagulants, and non-steroidal anti-inflammatory drugs, including ticagrelor (aOR 2.81), naproxen (aOR 1.87), and rivaroxaban (aOR 1.31), were strongly associated. INTERPRETATION: These studies demonstrate the generalizability and transportability of the PharmWAS pharmacovigilance framework. With additional validation, PharmWAS could complement traditional passive surveillance systems to identify medications that unexpectedly provoke or prevent high-impact conditions. FUNDING: U.S. National Institute of Diabetes and Digestive and Kidney Diseases.