Evidence map›Paper›PMID 40454153›Full record

ArticleFrontiers in medicine2025

Data-driven segmentation of type 2 diabetes mellitus patients: an observational study on health care utilisation prior to an emergency department visit in Germany.

Mirjam Rupprecht, Alessandro Campione, Yves Noel Wu, Antje Fischer-Rosinský, Anna Slagman, Dorothee Riedlinger, Martin Möckel, Thomas Keil, Lukas Reitzle, Cornelia Henschke

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Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Mirjam RupprechtDepartment for Infectious Disease Epidemiology, Robert Koch Institute, Berlin, Germany.
Alessandro CampioneDepartment of Health Care Management, Berlin Centre for Health Economics Research, Technische Universität Berlin, Berlin, Germany.
Yves Noel WuEmergency and Acute Medicine (CVK, CCM), Charité - Universitätsmedizin Berlin, Berlin, Germany.
Antje Fischer-RosinskýEmergency and Acute Medicine (CVK, CCM), Charité - Universitätsmedizin Berlin, Berlin, Germany.
Anna SlagmanEmergency and Acute Medicine (CVK, CCM), Charité - Universitätsmedizin Berlin, Berlin, Germany.
Dorothee RiedlingerEmergency and Acute Medicine (CVK, CCM), Charité - Universitätsmedizin Berlin, Berlin, Germany.
Martin MöckelEmergency and Acute Medicine (CVK, CCM), Charité - Universitätsmedizin Berlin, Berlin, Germany.
Thomas KeilInstitute of Social Medicine, Epidemiology and Health Economics, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Lukas ReitzleDepartment of Epidemiology and Health Monitoring, Robert Koch Institute, Berlin, Germany.
Cornelia HenschkeDepartment of Health Care Management, Berlin Centre for Health Economics Research, Technische Universität Berlin, Berlin, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Potentially avoidable hospital admissions (PAHs) due to type 2 diabetes mellitus (T2DM) occur more frequently in Germany than in the rest of Europe. Emergency departments (EDs) play an important role in understanding cross-sectoral health care utilisation resulting in inpatient admissions. Segmenting T2DM patients in homogenous groups according to their health care utilisation may help to understand the population's needs and to allocate limited resources. The aim of this study was to describe ED use and subsequent inpatient admissions among T2DM patients, and to segment the study population into homogenous subgroups based on disease stage, health care utilisation and process quality of outpatient care prior to an ED visit. Methods: This study was conducted as part of the INDEED project, comprising data on 56,821 ED visits in 2016 attributable to 40,561 patients with T2DM from 13 German EDs, as well as statutory health insurance claims data from 2014 to 2016 retrospectively linked per patient. Descriptive analyses included patient characteristics, ED admission diagnoses and discharge diagnoses in the case of inpatient admission of T2DM patients to the ED. Latent class analysis was conducted to identify different subgroups of T2DM patients based on disease stage, number of physician contacts and medical examinations prior to the ED visit. Results: Almost half of the study population had severe comorbidities (44.3%). In addition to T2DM, multiple cardiovascular diagnoses were among the most frequently documented admission and discharge diagnoses. The proportion of hospitalised ED visits for T2DM patients was higher (59%) than that for the INDEED population (42.8%). We identified three latent classes that were characterised as Conclusion: A substantial share of T2DM patients had not received disease monitoring according to guideline recommendations prior to ED presentation. Improving guideline-adherence in the outpatient sector could help reduce potentially avoidable ED visits. Effective interventions that aim at improving continuity and quality of care as well as reducing the share of PAH need to be identified and evaluated per identified class.

Indexed as

avoidable hospital admissionemergency departmenthealth care utilisationlatent class analysispopulation segmentationtype II diabetes mellitus

Identifiers

PMID40454153
PMCPMC12122753

What Socratic holds

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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 Socratic graph.