Barriers and Facilitators of Community-Based Health Insurance Policy Renewal in Low- and Middle-Income Countries: A Systematic Review

Figures & data

Figure 1 The PRISMA flowchart diagram of study selection. Note: PRISMA figure adapted from Liberati A, Altman D, Tetzlaff J, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: explanation and elaboration. Journal of clinical epidemiology. 2009;62(10). Creative Commons.¹⁹

Table 1 Summary of the Factors That Influence Policy Renewal of CBHI Schemes Based on Quantitative Studies

Factors	*(+)	*(-)	(+)	(-)	Total N	Summary
Socio-demographic factors
Older age	4	3	2	4	13	Inconclusive
Sex (Female)	3	1	4	3	11	Positive
Marital status (married)	1	1	3	1	6	Inconclusive
Level of education (educated)	7	-	5	2	14	Positive
Economic status (higher)	6	-	7	1	14	Positive
Household size (large)	1	2	5	3	11	Inconclusive
Area of residence (urban)	3	-	-	-	3	Positive
Need and benefit factors
Perceived health status (poor)	3	-	-	1	4	Positive
Recent Illness/injury	1	1	2	1	5	Inconclusive
Chronic illness	3	-	4	2	9	Positive
Hospitalization	-	1	-	3	4	Limited evidence
Use of healthcare	3	-	3	-	6	Positive
Frequency of health facility visit	2	-	-	-	2	Positive
Benefit claims (amount)	3	-	2	-	5	Positive
Quality of health care
Perceived health care quality (good)	2	-	2	1	5	Positive
Distance to health facility (longer)	1	4	3	5	13	Negative
Understanding of scheme	2	-	4	-	6	Positive
Scheme operation and policy
Trust in insurer (yes)	3	-	1	-	4	Positive
Satisfaction with insurer services	2	-	1	-	3	Positive
Long waiting time at scheme office	-	2	-	-	2	Negative
High premium (yes)	-	1	1	2	4	Limited evidence
Convenient premium payment time	2	-	-	-	2	Positive
Exempted family (yes)	3	-	-	-	3	Positive

Notes: *Statistically significant effect; (+), positive correlation; (-), negative correlation; N, number of studies.

Figure 2 A conceptual framework of barriers and facilitators critical to CBHI policy renewal.

Table 2 Heterogeneity Across Studies in Using Education as an Independent Variable During Analysis

	Author and Country	Basis of Categorization
1.	Adu 2019, Ghana^Citation42	No schooling, Primary, JSS/middle School, SSS/Tech/Voc. School, and Tertiary (5 categories)
2.	Dartanto 2019, Indonesia^Citation32	Completed above junior high school, and others (2 categories)
3.	Dong 2009, Burkina Faso^Citation33	No schooling, primary school and Middle school or above (3 categories)
4.	Herberholz 2016, Sudan^Citation41	Household head completed secondary school or higher – yes or no (2 categories)
5.	Iqbal 2017, Bangladesh^Citation31	Years of schooling: 0, 1–5, 6–10, and 11+ (4 categories)
6.	Mebratie 2015, Ethiopia^Citation43	Primary or above vs No education at all (2 categories)
7.	Mladovsky 2014, Senegal^Citation40	No education, Literate, Primary and Secondary or higher (4 categories)
8.	N. Rukundo 2019, Uganda^Citation34	At least of the parents has a secondary education, vs None of the parents have secondary education (2 categories)
9.	Panda 2016, India^Citation30	Illiterate, Primary, Middle, and Secondary or above (4 categories)
10.	Savitha 2017, India^Citation25	Illiterate, Primary (1–7 years), Secondary (8–12 years), 12 years or above (4 categories)
11.	Sinha 2007, India^Citation27	Did not complete secondary school, completed secondary school (10th standard), attended college or university (3 categories)

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