|General Information||Outcomes||Statistical Analysis|
|First Author||Publication Year||Citation/Title||Outcomes measured||Measures of financial risk protection||Reduction in out of pocket expenditure (OOPE)||Reduction in catastrophic health expenditure (CHE)||Poverty reduction||Type of statistical analysis||Logistic regression (N) number of variables||Key findings|
|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.||Direct OOPE(s) for inpatient, outpatient care, & transportation cost||NR1||
Transportation NS2 IPD OOPE***
(NHIS $4.25USD, uninsured $43.88USD)
|NR1||NR1||Descriptive statistics, logistic regression||(8) Independent variables, dependent variable (OOPE)||
1.) Insurance was associated with lower out of pocket payments for inpatient care.|
2.) No significance difference in outpatient care.
3.) No difference in transportation cost
|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–https://doi.org/10.1186/1475-9276-10-4.||OOPE(s) & CHE(s) for illness, surgery, ANC & inpatient care||4 indicators of CHE(s); (5% & 10% of individual income) and (10% & 20% of SE(s)5||OOPE*** NHIS 21000 GH¢ ($2.3 USD), uninsured 30,000 GH¢ ($ 3.2 USD)||NHIS reduced CHE(s) by 0.5 to 1% depending on the threshold used.||NR1||Descriptive statistics, logistic regression||(6) Independent variables, dependent variable (OOPE)||NHIS reduces the probability of incurring CHE(s).|
|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.||Direct OOPE(s) for malaria treatment, lost wages & transportation cost||NR1||NS2||NR1||NR1||Descriptive statistics||NR1||
1.) NHIS has some protective effect on cost of malaria treatment, however not statistically significant|
2.) Indirect costs of treating malaria were three times higher than direct costs for both insured and uninsured households.
|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.||Prenatal care utilization & OOPE(s) per ANC visit||NR1||OOPE*** NHIS 3600GH¢ ($0.40 USD), uninsured 21,000 GH¢ ($2.40 USD) for the first ANC visit||NR1||NR1||Descriptive statistics, logistic regression||(7) Independent variables, dependent variable (prenatal OOPE)||
1.) Insured women spend less on prenatal care compared to the uninsured.|
2.) Having insurance increases the number of prenatal care visits by 24% relative to being 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).||Financial burden/ OOPE direct inpatient care & perceived financial difficulties||NR1 used an arbitrary threshold of > 50 GH¢. as expensive or burdensome||NR1||NR1||NR1||Descriptive, logistic regression||(11) Independent variables, dependent variable (financial burden of care)||Uninsured respondents were twenty- three times more likely than the insured to make higher out of pocket payments for hospitalizations and more likely to experience financial burden of care.|
|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).||Direct OOPE(s) for inpatient, outpatient care, & transportation cost||10% of total household expenditures & SE(s)5 at (20% & 40% thresholds)||OOPE*** OPD3; NHIS 6.7 GH¢ uninsured 25.5GH¢. IPD4*** NHIS 44.25GH¢ uninsured 86.73 GH¢. Transportation cost NS2||6% of NHIS respondents compared to 23.2% of the uninsured made CHE(s)||NR1||Descriptive statistics, logistic regression||(6) Independent variables, dependent variable (CHE)||
1.) NHIS significantly reduces the probability of a household incurring CHE(s).|
2.) Households with at least one member having a chronic illness were 94% higher than those without a chronic illness to incur CHE.
|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).||Direct OOPE(s) for inpatient, outpatient care, & transportation cost||SE(s)5 at (40% threshold)||IPD4 NS2 2009 OOPE ***OPD3 NHIS GH¢ 19.8 uninsured GH¢ 27.4. 2011 OOPE*** OPD3 NHIS 26.1GH¢ uninsured 53.2GH¢. Transportation cost NR1||In 2009, 18.4% of NHIS respondents made CHE(s), compared to 36.1% uninsured. In 2011 7.1% NHIS & 28.7% Uninsured||NHIS households were 7.5% less likely to fall into poverty.||Descriptive statistics, logistic regression||(9) Independent variable Insurance status, dependent variable (OOPE)||
1.) Enrolment in health insurance reduced household OOPE by 86%.|
2.) Insured households were 3% less likely to make CHE(s).
3.) Being insured reduces households’ probability of falling into poverty by 7.5%.