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BMC Health Serv Res. 2015 Dec 8;15:543. doi: 10.1186/s12913-015-1179-3.

A systematic review of factors that affect uptake of community-based health insurance in low-income and middle-income countries.

Author information

1
Centre for Evidence-based Health Care, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa. estheradebayo@gmail.com.
2
School of Public Health and Family Medicine, University of Cape Town, Observatory, South Africa. estheradebayo@gmail.com.
3
Centre for Evidence-based Health Care, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa. olalekan.uthman@warwick.ac.uk.
4
Warwick-Centre for Applied Health Research and Delivery (WCAHRD), Division of Health Sciences, Warwick Medical School, The university of Warwick, Coventry, CV4 7AL, UK. olalekan.uthman@warwick.ac.uk.
5
Liverpool School of Tropical Medicine, International Health Group, Liverpool, Merseyside, UK. olalekan.uthman@warwick.ac.uk.
6
Centre for Evidence-based Health Care, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa. charlesw@sun.ac.za.
7
Cochrane South Africa, South African Medical Research Council, Cape Town, South Africa. charlesw@sun.ac.za.
8
Women's Health Research Unit, School of Public Health, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa. erin.a.stern@googlemail.com.
9
Soweto Cardiovascular Research Unit, University of the Witwatersrand, Johannesburg, South Africa. kimmylamont@gmail.com.
10
Health Economics Unit, School of Public Health and Family Medicine, University of Cape Town, Observatory, South Africa. John.Ataguba@uct.ac.za.

Abstract

BACKGROUND:

Low-income and middle-income countries (LMICs) have difficulties achieving universal financial protection, which is primordial for universal health coverage. A promising avenue to provide universal financial protection for the informal sector and the rural populace is community-based health insurance (CBHI). We systematically assessed and synthesised factors associated with CBHI enrolment in LMICs.

METHODS:

We searched PubMed, Scopus, ERIC, PsychInfo, Africa-Wide Information, Academic Search Premier, Business Source Premier, WHOLIS, CINAHL, Cochrane Library, conference proceedings, and reference lists for eligible studies available by 31 October 2013; regardless of publication status. We included both quantitative and qualitative studies in the review.

RESULTS:

Both quantitative and qualitative studies demonstrated low levels of income and lack of financial resources as major factors affecting enrolment. Also, poor healthcare quality (including stock-outs of drugs and medical supplies, poor healthcare worker attitudes, and long waiting times) was found to be associated with low CBHI coverage. Trust in both the CBHI scheme and healthcare providers were also found to affect enrolment. Educational attainment (less educated are willing to pay less than highly educated), sex (men are willing to pay more than women), age (younger are willing to pay more than older individuals), and household size (larger households are willing to pay more than households with fewer members) also influenced CBHI enrolment.

CONCLUSION:

In LMICs, while CBHI schemes may be helpful in the short term to address the issue of improving the rural population and informal workers' access to health services, they still face challenges. Lack of funds, poor quality of care, and lack of trust are major reasons for low CBHI coverage in LMICs. If CBHI schemes are to serve as a means to providing access to health services, at least in the short term, then attention should be paid to the issues that militate against their success.

PMID:
26645355
PMCID:
PMC4673712
DOI:
10.1186/s12913-015-1179-3
[Indexed for MEDLINE]
Free PMC Article

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