Observational studyBMC health services research2026
Dynamics of healthcare inequalities in type 2 diabetes mellitus across the COVID-19 pandemic: a real-world population-based study.
Observational study in BMC health services research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundhealthcare inequalities have been widely documented, yet the COVID-19 pandemic may have altered their magnitude and direction. This study aimed to analyse the dynamics of healthcare inequalities in patients with type 2 diabetes mellitus (T2DM) before and after the pandemic using a real-world data approach.
methodswe conducted a real-world observational study including T2DM patients aged ≥ 45 from the CARhES cohort, a population-based dataset integrating clinical and administrative information from Aragón (Spain), between 2017 and 2022. Healthcare utilisation was assessed at two levels: Primary Care and specialist care. Socioeconomic, clinical, and healthcare variables were retrieved from electronic health records. We described healthcare utilisation patterns and trends across the study period and estimated adjusted prevalence ratios (PRs) for inequality axes (age, gender, migrant status, socioeconomic level, and rurality) using Poisson regression models at three time points (2017, 2020, 2022), adjusting for multimorbidity.
resultsA total of 86,407 T2DM patients were included. Almost all patients consulted a general practitioner (GP) each year and increased over time, while specialist consultations declined during the pandemic and had not recovered by 2022. Socioeconomic inequalities persisted or widened across most axes. After the pandemic, patients aged ≥ 80 were less likely to visit GP than younger patients, reversing pre-pandemic trends. Women continued to show higher GP use than men but fewer consulted with specialist, although the magnitude of the observed difference was small. Immigrants' access to specialists decreased relative to natives in 2022. active people with low socioeconomic status showed the lowest specialist consultations, while mutualists had the highest during the pandemic. Rural residents maintained greater reliance on Primary Care but fewer specialist visits post-pandemic. The explanatory power of socioeconomic variables declined in GP models, whereas multimorbidity gained influence during and after COVID-19.
conclusionsHealthcare inequalities among T2DM patients persisted and some patterns shifted after 2020. Although GP utilisation increased, nursing and specialist follow-up did not recover to pre-pandemic levels. These patterns underscore the need for targeted interventions to optimise care for older adults, women, migrants, rural residents, and low-income populations, with a focus on promoting digital inclusion and developing tailored healthcare pathways to advance health equity.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.