Trial reportDiabetes care2025
Project ECHO Diabetes Trial Improves Outcomes for Medically Underserved People.
Trial report in Diabetes care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Health Service Leaders' Perspectives on Type 1 Diabetes Models of Care for Children and Young Adults in Australia: A Mixed-Methods Study.Journal of diabetes research · 2026Article
- Peer Mentoring Improves Diabetes Technology Use and Reduces Diabetes Distress Among Underserved Communities: Outcomes of a Pilot Diabetes Support Coach Intervention.Journal of diabetes research · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors.
Funding
Abstract
objectiveThe Project Extension for Community Healthcare Outcomes (ECHO) model is used in 180 countries to address chronic disease care through a provider empowerment, tele-education approach. Few studies have rigorously evaluated the impact of the program on patient outcomes using randomized designs. RESEARCH DESIGN AND
methodsImplementation of an ECHO Diabetes program was evaluated using a stepped-wedge design with recruitment of 20 federally qualified health centers (FQHCs) across California and Florida with randomized, phased-in intervention entry. Participating FQHCs (referred to as "spokes") provided aggregate data, including the Healthcare Effectiveness Data and Information Set (HEDIS) and diabetes technology use. Patients were recruited from spokes, and data collection involved historical and prospective HbA1c measures, HEDIS markers, and pre/post surveys. Linear mixed models were used to generate patient-level monthly HbA1c estimates and evaluate change over time; Poisson regression was used to model clinic-level technology use.
resultsThe spoke-level cohort included 32,796 people with type 1 diabetes (T1D; 3.4%) and type 2 diabetes (T2D; 96.6%), of whom 72.7% were publicly insured or uninsured. The patient-level cohort included 582 adults with diabetes (33.0% with T1D, 67.0% with T2D). Their mean age was 51.1 years, 80.7% were publicly insured or uninsured, 43.7% were non-Hispanic White, 31.6% were Hispanic, 7.9% were non-Hispanic Black, and 16.8% were in other race/ethnicity categories. At the spoke level, there were statistically significant reductions before and after the intervention in the proportion of people with HbA1c >9% (range 31.7% to 26.7%; P = 0.033). At the patient level, there were statistically significant increases in those using continuous glucose monitoring (range 25.1% to 36.8%; P < 0.0001) and pump use (range 15.3% to 18.3%; P < 0.001) before and after the intervention.
conclusionsThe ECHO model demonstrates promise for reducing health disparities in diabetes and contributes to our understanding of program benefits beyond the provider level.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.