Table 3.
Summary of survey methodology and participant characteristics in the included studies
| General Information | Study Characteristics | Participant Characteristics | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| First Author | Publication Year | Citation/Title | Study Objectives/Aims | Study Design | Data Source | Sampling Technique | Recall Period | Settinga | Study Population | SESb | Population Size |
| Chankova | 2008 | Chankova S, Sulzbach S, Diop F. Impact of mutual health organizations: evidence from West Africa. Health Policy and Planning. 2008;23(4):264–276. | To answer the following questions: (1) Do MHOs include vulnerable populations. (2) Do they have an impact on the utilization of curative services. (3) On out-of-pocket expenditures | Cross-sectional | 1° | NRc | Twelve months | Household | Three country comparisons; Ghana, Mali, Senegal. (Nkoranza and Offinso districts in Ghana) | SES wealth quintiles, household head, education, occupation, residence(urban-rural), house-hold size | 1806 households (34% NHIS, 66% uninsured) |
| Nguyen | 2011 | Nguyen HT, Rajkotia Y, Wang H. The financial protection effect of Ghana National Health Insurance Scheme: evidence from a study in two rural districts. International Journal for Equity in Health. 2011, 10: 4–10.1186/1475-9276-10-4. | Not clearly stated but evaluated the impact of NHIS on health service utilization and OOPE(s) | Cross-sectional | 1° | Two-stage cluster & random sampling | Two weeks (injury recall period) to twelve months | Household | Households in two districts (Offinso and Nkoranza) in Ghana | SES wealth quintiles, household head, employment status, house-hold size, ethnicity, residence(urban-rural) | 11,617 individuals (35% NHIS, 65% uninsured) |
| Dalaba | 2014 | Dalaba M, Akweongo P, Aborigo R, Awine T, Azongo D, Asaana P et al. Does the national health insurance scheme in Ghana reduce household cost of treating malaria in the Kassena-Nankana districts? Global Health Action. 2014;7(1):23848. | To examine the effect of NHIS in reducing household cost of treating malaria | Cross-sectional | 1° | Convenience random sampling | NRc | Household | Households in the Kassena-Nankana district | SES wealth quintiles, age, occupation | 4226 households (49.1% NHIS, 50.9% uninsured) |
| Abrokwah | 2014 | Abrokwah SO, Moser CM, Norton EC. The effect of social health insurance on prenatal care: the case of Ghana. Int J Health Care Finance Econ. 2014;14(4):385–406. | To describe how Ghana’s health insurance scheme affects prenatal care and out-of-pocket expenditures | Cross-sectional | 2° GLS5 2005–2006 | Random stratified sampling | Twelve months | Household | Women of child bearing age (15–49 years) | SES wealth quintiles, age, education, region, marital status, occupation, employment status, house-hold size | 1032 women from the GLS5 (36% NHIS, 64% uninsured) |
| Abuosi | 2015 | Abuosi A, Adzei F, Anarfi J, Badasu D, Atobrah D, Yawson A. Investigating parents/caregivers financial burden of care for children with non-communicable diseases in Ghana. BMC Pediatrics. 2015;15(1). | To assess the extent to which parents/caregivers of children with NCDs experience financial burden in caring for them | Cross-sectional | 1° | Convenience random sampling | NRc | Inpatient | Parents/caregivers of children hospitalized with NCDs at hospitals in Greater Accra, Ashanti, and the Volta region | Parents’ age, education, income, marital status, religion, residence (urban-rural) | 225 parents/caregivers (87% NHIS 13% uninsured) |
| Kusi | 2015 | Kusi A, Hansen K, Asante F, Enemark U. Does the National Health Insurance Scheme provide financial protection to households in Ghana? BMC Health Services Research. 2015;15(1). | To assess the effect of NHIS on household OOPE(s) and CHE(s) | Cross-sectional | 1° | Random stratified Sampling | Four weeks | Household | Households in three districts in the three ecological zones of Southern (Kwaebibrirem), Middle (Asutifi), and Northern (Savelugu-Nanton) | SES wealth quintiles household size, household head, marital status, residence (urban-rural), education, distance to the nearest facility, mode of transportation | 2430 households (28% NHIS, 46% uninsured, & 26% partially insured) |
| Aryeetey | 2016 | Aryeetey G, Westeneng J, Spaan E, Jehu-Appiah C, Agyepong I, Baltussen R. Can health insurance protect against out-of-pocket and catastrophic expenditures and also support poverty reduction? Evidence from Ghana’s National Health Insurance Scheme. International Journal for Equity in Health. 2016;15(1). | To examine whether Ghana’s health insurance scheme reduces OOPE(s), CHE(s) and poverty at the household level | Cross-sectional | 1° | Random stratified sampling | Four weeks | Household | Households in the Eastern and Central Region. Baseline study conducted in 2009 and follow-up in 2011 | Household size, marital status, religion, education, residence (urban-rural), occupation, household income, household expenditures | In 2009, 3300 households (31% NHIS 69% uninsured); 2011 3152 households (38% NHIS 62% uninsured) |
1° denotes primary data collection by the authors. 2° is secondary analysis of previously collected data. a Study setting denotes where participants were interviewed
bSES wealth quintile refers to the reporting of wealth-specific results using a principal component analysis of dwelling characteristics, access to utilities and ownership of house-hold items. Further description is available at https://www.dhsprogram.com/topics/wealth-index/Wealth-Index-Construction.cfm
cNR not reported by the studies