Examining inequality in utilisation of health management services for the elderly in rural Henan China

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Abstract

Background

The health management plays an important role in improving the quality of life of the elderly and relieving the pressure of health resource consumption. This study aims to assess the income-related inequality in utilisation of health management services (HMS) for the elderly and the contribution of the related factors to inequality in rural Henan China.

Methods

The data from 2015 Henan Rural Residents Health Survey with 1403 elderly people as the final sample were used for analysis. The concentration index (CI) was used to measure inequality in HMS utilisation for the elderly (no HMS, health assessment, physical examination, auxiliary examination, and health guidance). The decomposition of CI was adopted to explain the contribution of various determinants to inequality in HMS utilisation for the elderly.

Results

No HMS utilisation was disproportionately concentrated among the poor ( CI = − 0.0730 , p = 0.0155), utilisation of physical and auxiliary examination was disproportionately concentrated among the rich ( CI = 0.0575 , p = 0.0448; CI = 0.0811 , p = 0.0044). In addition, the pro-poor effects of health assessment and guidance utilisation were not statistically significant ( CI = − 0.0173, p = 0.4617; CI = − 0.0213, p = 0.3900). The results of CI decomposition revealed that household income and family size made positive contributions to inequality while social medical insurance, gender, marital status, and age made negative contributions to inequality. The improved service satisfaction with village clinics could reduce inequality in HMS utilisation, while the improved service satisfaction with township hospitals could increase inequality in HMS utilisation.

Conclusions

Although HMS for the elderly is provided free of charge, its accessibility remains pro-rich due to various factors. Policy makers should adopt effective interventions to resolve the contradiction between these factors and the utilisation of HMS, and redress inequality in the utilisation of HMS.

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Most cited references 22

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The Behavioral Model for Vulnerable Populations: application to medical care use and outcomes for homeless people.

L Gelberg, R Andersen, B. D. LEAKE (2000)

(1) To present the Behavioral Model for Vulnerable Populations, a major revision of a leading model of access to care that is particularly applicable to vulnerable populations; and (2) to test the model in a prospective study designed to define and determine predictors of the course of health services utilization and physical health outcomes within one vulnerable population: homeless adults. We paid particular attention to the effects of mental health, substance use, residential history, competing needs, and victimization. A community-based probability sample of 363 homeless individuals was interviewed and examined for four study conditions (high blood pressure, functional vision impairment, skin/leg/foot problems, and tuberculosis skin test positivity). Persons with at least one study condition were followed longitudinally for up to eight months. Homeless adults had high rates of functional vision impairment (37 percent), skin/leg/foot problems (36 percent), and TB skin test positivity (31 percent), but a rate of high blood pressure similar to that of the general population (14 percent). Utilization was high for high blood pressure (81 percent) and TB skin test positivity (78 percent), but lower for vision impairment (33 percent) and skin/leg/foot problems (44 percent). Health status for high blood pressure, vision impairment, and skin/leg/foot problems improved over time. In general, more severe homeless status, mental health problems, and substance abuse did not deter homeless individuals from obtaining care. Better health outcomes were predicted by a variety of variables, most notably having a community clinic or private physician as a regular source of care. Generally, use of currently available services did not affect health outcomes. Homeless persons are willing to obtain care if they believe it is important. Our findings suggest that case identification and referral for physical health care can be successfully accomplished among homeless persons and can occur concurrently with successful efforts to help them find permanent housing, alleviate their mental illness, and abstain from substance abuse.

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conindex: Estimation of concentration indices.

Brendan Walsh, Owen O'Donnell, Stephen O'Neill … (2016)

Concentration indices are frequently used to measure inequality in one variable over the distribution of another. Most commonly, they are applied to the measurement of socioeconomic-related inequality in health. We introduce a user-written Stata command conindex which provides point estimates and standard errors of a range of concentration indices. The command also graphs concentration curves (and Lorenz curves) and performs statistical inference for the comparison of inequality between groups. The article offers an accessible introduction to the various concentration indices that have been proposed to suit different measurement scales and ethical responses to inequality. The command's capabilities and syntax are demonstrated through analysis of wealth-related inequality in health and healthcare in Cambodia.

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On correcting the concentration index for binary variables.

Ulf-G Gerdtham, Gustav Kjellsson (2013)

This article discusses measurement of socioeconomic inequalities in the prevalence of a health condition, in response to the recent exchange between Guido Erreygers and Adam Wagstaff, in which they discuss the merits of their own corrections to the frequently used concentration index. We first reconcile their debate and discuss the value judgments implicit in their indices. Next, we provide a formal definition of the previously undefined value judgment in Wagstaff's correction. Finally, we show empirically that the choice of index matters, as illustrated by comparisons between countries using data from the European Survey of Health, Ageing and Retirement. Copyright © 2012 Elsevier B.V. All rights reserved.

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Author and article information

Contributors

Yaqing Liu:

ORCID: http://orcid.org/0000-0002-3094-4876

yqxstgzy@163.com

Journal

Journal ID (nlm-ta): BMC Health Serv Res

Journal ID (iso-abbrev): BMC Health Serv Res

Title: BMC Health Services Research

Publisher: BioMed Central (London )

ISSN (Electronic): 1472-6963

Publication date (Electronic): 17 August 2020

Publication date PMC-release: 17 August 2020

Publication date Collection: 2020

Volume: 20

Electronic Location Identifier: 758

Affiliations

[1 ]GRID grid.33199.31, ISNI 0000 0004 0368 7223, School of Medicine and Health Management, Tongji Medical College, , Huazhong University of Science and Technology, ; Wuhan, Hubei China

[2 ]GRID grid.412990.7, ISNI 0000 0004 1808 322X, Management Institute, , Xinxiang Medical University, ; Xinxiang, Henan China

Author information

Yaqing Liu http://orcid.org/0000-0002-3094-4876

Article

Publisher ID: 5630

DOI: 10.1186/s12913-020-05630-7

PMC ID: 7433128

PubMed ID: 32807153

SO-VID: d4c4478a-059c-4af4-a8f1-e8e299e52840

License:

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 19 March 2020

Date accepted : 5 August 2020

Funding

Funded by: This study was funded by Soft Science Research Program of Henan Province

Award ID: 192400410055

Award Recipient : Huan Wu

Funded by: Independent Innovation Fund of Huazhong University of Science and Technology

Award ID: 516-5003516027

Custom metadata

ScienceOpen disciplines: Health & Social care

Keywords: health management services,the elderly,inequality,concentration index,decomposition,china

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ScienceOpen disciplines: Health & Social care

Keywords: health management services, the elderly, inequality, concentration index, decomposition, china

Examining inequality in utilisation of health management services for the elderly in rural Henan China

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Abstract

Background

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Conclusions

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China Occupational Medicine

Most cited references 22

The Behavioral Model for Vulnerable Populations: application to medical care use and outcomes for homeless people.

conindex: Estimation of concentration indices.

On correcting the concentration index for binary variables.

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