Study: Trends and Disparities in Technology Use and Glycemic Control in Type 1 Diabetes.
Journal / date: JAMA Network Open (Original investigation published Aug 1, 2025).
What the researchers asked
They wanted to describe national trends over 15 years (2009–2023) in (1) uptake of diabetes technologies (continuous glucose monitors — CGMs — and insulin pumps) and (2) glycemic control (measured by hemoglobin A1c <7%) among U.S. youths and adults with type 1 diabetes (T1D), and whether improvements differed by race/ethnicity or socioeconomic indicators.
Data & methods (brief)
- Data source: Optum Labs Data Warehouse — a large, deidentified national electronic health records (EHR) database.
- Study design: Serial, cross-sectional analysis dividing the 2009–2023 period into 3-year blocks (2009–2011, …, 2021–2023).
- Population: 186,590 people with T1D identified in the database:
- 26,853 youths (mean age ≈12) and 159,737 adults (mean age ≈45).
- Race/ethnicity breakdown reported (≈76% non-Hispanic White, 12% non-Hispanic Black, 7% Hispanic, ~2% Asian)
- Outcomes measured: mean HbA1c and % with HbA1c <7% (glycemic control), and documented use of CGM and/or insulin pump (from labs, prescriptions, procedure/diagnosis codes).
Main quantitative findings
- Large increases in technology use (2009–2011 → 2021–2023):
- CGM use — youths: 4% → 82%; adults: 5% → 57%.
- Insulin pump use — youths: 16% → 50%; adults: 11% → 29%.
- Concurrent use (both CGM + pump) — youths: 1% → 47%; adults: 1% → 22%.
- Improvements in glycemic control (HbA1c <7%):
- Youths: 7% → 19% achieving A1c <7%.
- Adults: 21% → 28% achieving A1c <7%.
- All trends statistically significant (P < .001)
Key equity finding — disparities persisted or grew
- Despite overall gains, Hispanic and non-Hispanic Black patients and those insured through Medicaid consistently had the lowest rates of technology use and the lowest prevalence of glycemic control. The racial/ethnic and socioeconomic gaps did not close — in many cases they widened across the study period. This is a major concern for health equity.
Authors’ interpretation & implications
- Rapid adoption of CGMs and pumps appears linked to measurable improvements in glycemic control at a population level, especially among youths. However, the majority of people with T1D still do not meet glycemic targets, and the benefits of technology are not reaching all groups equally. The authors emphasize the need for policies and interventions that increase equitable access (insurance coverage, affordability, clinician support, education, outreach).
Strengths of the study
- Very large sample (n≈186k) drawn from real-world EHRs across the U.S.
- Long period (15 years) allowing clear trend estimation through major changes in technology availability and clinical practice.
Limitations noted
- EHR data limitations: possible misclassification, incomplete capture of device use (if device prescriptions or external data weren’t recorded), variable lab capture across sites.
- Generalizability: Optum datasets are large but may not perfectly represent uninsured populations or every care setting.
- Unmeasured confounding: Social determinants (education, housing, local access), adherence, diabetes duration and clinical complexity may mediate outcomes but weren’t fully captured.
- Cross-sectional approach: Trends are observed at population level across time blocks, but this does not replace causal inference from randomized trials.
Broader context & related commentary
- The study aligns with other analyses showing CGMs and automated insulin delivery systems improve Time-In-Range and A1c, but access and affordability remain barriers. News and expert commentaries highlight the policy implications — expanding insurance coverage, subsidies, and clinic support to close gaps.
Bottom line (brief)
Over 15 years (2009–2023) there has been a dramatic rise in CGM and pump use and measurable improvements in glycemic control among people with T1D in the U.S. — but glycemic targets are still achieved by a minority, and racial, ethnic and socioeconomic disparities persist or have increased. Policy, payer, and clinical steps are needed to ensure the benefits of diabetes technology are equitably distributed.
