Evidence map›Paper›PMID 40264139›Full record

ArticleBMC medicine2025

Exploring patterns in pediatric type 1 diabetes care and the impact of socioeconomic status.

Christopher Nussbaum, Anna Novelli, Amelie Flothow, Leonie Sundmacher

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Article in BMC medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Christopher NussbaumDepartment of Health Economics, School of Medicine and Health, Technical University of Munich, Georg-Brauchle-Ring 60/62, Munich, 80992, Germany. Christopher.Buehler@tum.de.
Anna NovelliDepartment of Health Economics, School of Medicine and Health, Technical University of Munich, Georg-Brauchle-Ring 60/62, Munich, 80992, Germany.
Amelie FlothowDepartment of Health Economics, School of Medicine and Health, Technical University of Munich, Georg-Brauchle-Ring 60/62, Munich, 80992, Germany.
Leonie SundmacherDepartment of Health Economics, School of Medicine and Health, Technical University of Munich, Georg-Brauchle-Ring 60/62, Munich, 80992, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundManaging pediatric type 1 diabetes is complex and requires substantial parental involvement. Adherence to clinical guidelines is often inconsistent, and lower parental socioeconomic status is associated with worse outcomes in affected children. However, few studies have examined these children's care pathways multidimensionally over time. This study aims to identify latent clusters in the care pathways of pediatric patients with type 1 diabetes mellitus, evaluate guideline adherence and disease management within these clusters, and assess the influence of socioeconomic status on cluster membership.

methodsWe analyzed care pathways for pediatric patients with type 1 diabetes from 2017 to 2019 in the German health system, which provides universal coverage. Using state sequence analysis and clustering algorithms from the TraMineR R package, we identified patient clusters based on healthcare utilization patterns. To assess care quality within these clusters, we compared observed care patterns to clinical guideline recommendations. Our analysis was based on health insurance claims data from Techniker Krankenkasse, a statutory health insurer. From the dataset, which encompassed more than three million patients under the age of 25 years, we derived an age-homogeneous cohort of continuously insured children aged 11 to 14 years with type 1 diabetes in 2017 and extracted relevant healthcare events over a 3-year period.

resultsBased on care patterns, we identified two clusters of children, which we designated as the "guideline-adherent" and "care-with-gaps" clusters. Roughly 25% of our cohort (n = 890) fell into the latter cluster, consistently receiving care that fell short of guideline recommendations. For example, these patients had less than half as many quarters with hemoglobin A1c measurement. Lower parental educational attainment and unemployment were predictors of this suboptimal care. We also found that the average number of hospitalizations per child was almost 40% higher in the cluster with less guideline-adherent care.

conclusionsDespite universal health coverage and frequent contact with the outpatient healthcare system, a substantial proportion of pediatric type 1 diabetes patients in Germany experience suboptimal care, particularly in glycemic diagnostics and screening for complications, leading to worse health outcomes. Higher socioeconomic status is associated with care that more closely adheres to clinical guidelines.

Indexed as

Diabetes Mellitus, Type 1Guideline AdherenceSocial ClassAdolescentChildCluster AnalysisFemaleGermanyHumansMaleCare pathwaysClustering algorithmsInsurance claims dataPediatric health dataSocioeconomic statusState sequence analysisType 1 diabetes mellitus

Identifiers

PMID40264139
PMCPMC12016072

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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.