Evidence map›Paper›PMID 32539734›Full record

ArticleBMC public health2020

Tracking socio-economic inequalities in healthcare utilization in Iran: a repeated cross-sectional analysis.

Sajad Vahedi, Vahid Yazdi-Feyzabadi, Mostafa Amini-Rarani, Abolfazl Mohammadbeigi, Ardeshir Khosravi, Aziz Rezapour

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  4. Changes in health-related quality of life and inequality in China: evidence from a nationwide repeated cross-sectional survey (2021-2023).Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
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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

6 authors.

Sajad VahediDepartment of Healthcare Administration, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
Vahid Yazdi-FeyzabadiHealth Services Management Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Mostafa Amini-RaraniHealth Management and Economics Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
Abolfazl MohammadbeigiNeuroscience Research Center, Department of Epidemiology and Biostatistics, Faculty of Health, Qom University of Medical Sciences, Qom, Iran.
Ardeshir KhosraviDeputy for Public Health, Ministry of Health and Medical Education, Tehran, Iran.
Aziz RezapourHealth Management and Economics Research Center, School of Health Management and Information Sciences, Iran University of Medical Sciences, P.O Box: 1996713883, No. 6, Rashid Yasemi St. Vali -e Asr Ave, Tehran, Iran. rezapour.a@iums.ac.ir.ORCID http://orcid.org/0000-0003-4032-0802

Funding

Iran University of Medical Sciences IUMS/SHMIS_20169321504002
6 · The paper itself

Abstract

backgroundAlthough some healthcare reforms such as Health Transformation Plan (HTP) were implemented in Iran to provide required healthcare services, few studies have been conducted to track the impacts of these reforms on socio-economic inequality in healthcare utilization. This study aims to track socio-economic inequalities in healthcare utilization and their changes between 2008 and 2016 in Iran.

methodsRequired data were obtained from two of Iran's utilization of healthcare services survey conducted in 2008 and 2016. Erreygers concentration index (EI) was used to measure inequality in the utilization of outpatient and inpatient healthcare services (UOH and UIH). The decomposition of EI (DEI) was used to explain healthcare utilization inequality. Oaxaca decomposition (OD) was also employed to track the changes in EI in this period.

resultInequality in UOH increased from 0.105 to 0.133 in the studied years, indicating the pro-rich distribution of UOH. Inequality in UIH decreased from 0.0558 to - 0.006. DEI showed that economic status was the main factor that contributed to inequality in the UOH and UIH. OD showed that residence in rural areas and supplementary insurance were the main contributing factors in the increased inequality of UOH. Moreover, OD also showed that economic status was the main contributing factor in the reduced inequality of UIH.

conclusionWhile Iran still suffers from significant socio-economic inequalities in UOH, it seems that healthcare reforms, especially HTP, have reduced UIH inequality. Expanding healthcare reforms into the outpatient sector and also implementing effective health financing policies could be recommended as a remedy against UOH inequality.

Indexed as

Socioeconomic FactorsAdolescentAdultAgedAged, 80 and overAge FactorsCross-Sectional StudiesFemaleHealthcare DisparitiesHealth Services AccessibilityHumansIranMaleMiddle AgedPatient Acceptance of Health CareSex FactorsConcentration indexDecomposition analysisHealthcare servicesHealth inequalityIran

Identifiers

PMID32539734
PMCPMC7296685

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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.