Evidence map›Paper›PMID 38327575›Full record

ArticleFrontiers in public health2024

Cross-sectional comparison of health care delivery and reimbursement between segregated and nonsegregated communities in Hungary.

Feras Kasabji, Ferenc Vincze, Kinga Lakatos, Anita Pálinkás, László Kőrösi, László Ulicska, Karolina Kósa, Róza Ádány, János Sándor

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
3.4field-weighted citation impact, top 9% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 4 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 2 institutions in 1 country.

Feras KasabjiDepartment of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Ferenc VinczeDepartment of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Kinga LakatosDepartment of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Anita PálinkásELKH-DE Public Health Research Group, Department of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
László KőrösiNational Health Insurance Fund, Budapest, Hungary.
László UlicskaDeputy State Secretariat for Social Inclusion, Ministry of Interior, Budapest, Hungary.
Karolina KósaDepartment of Behavioral Sciences, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
Róza ÁdányDepartment of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
János SándorDepartment of Public Health and Epidemiology, Faculty of Medicine, University of Debrecen, Debrecen, Hungary.
University of Debrecen · HUMinistry of Interior · HU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Spatially segregated, socio-economically deprived communities in Europe are at risk of being neglected in terms of health care. In Hungary, poor monitoring systems and poor knowledge on the health status of people in these segregated areas prevent the development of well-informed effective interventions for these vulnerable communities. Aims: We used data available from National Health Insurance Fund Management to better describe health care performance in segregated communities and to develop more robust monitoring systems. Methods: A cross-sectional study using 2020 health care data was conducted on each general medical practice (GMP) in Hungary providing care to both segregated and nonsegregated (complementary) adult patients. Segregated areas were mapped and ascertained by a governmental decree that defines them as within settlement clusters of adults with low level of education and income. Age, sex, and eligibility for exemption certificate standardized indicators for health care delivery, reimbursement, and premature mortality were computed for segregated and nonsegregated groups of adults and aggregated at the country level. The ratio of segregation and nonsegregation specific indicators (relative risk, RR) was computed with the corresponding 95% confidence intervals (95% CI). Results: Broad variations between GMPs were detected for each indicator. Segregated groups had a significantly higher rate of health care service use than complementary groups (RR = 1.22, 95% CI: 1.219;1.223) while suffering from significantly reduced health care reimbursement (RR = 0.940, 95% CI: 0.929;0.951). The risk of premature mortality was significantly higher among segregated patients (RR = 1.184, 95% CI: 1.087;1.289). Altogether, living in a segregated area led to an increase in visits to health care services by 18.1% with 6.6% less health spending. Conclusion: Adults living in segregated areas use health care services more frequently than those living in nonsegregated areas; however, the amount of health care reimbursement they receive is significantly lower, suggesting lower quality of care. The health status of segregated adults is remarkably lower, as evidenced by their higher premature mortality rate. These findings demonstrate the need for intervention in this vulnerable group. Because our study reveals serious variation across GMPs, segregation-specific monitoring is necessary to support programs sensitive to local issues and establish necessary benchmarks.

Indexed as

Delivery of Health CareGuanosine MonophosphateThionucleotidesAdultCross-Sectional StudiesEuropeHumansHungaryguanosine 5'-monophosphorothioateGuanosine MonophosphateThionucleotidescross-sectionalgeneral medical practitionerhealthcarehealth reimbursementHungaryinequalitysegregation

Identifiers

PMID38327575
PMCPMC10847262
OpenAlexW4391172457

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

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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.