financial protection effect of health insurance evidence from ghana national health insurance scheme...
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Financial Protection Effect of Health Insurance Evidence from Ghana National Health Insurance Scheme
Ha Nguyen, Abt Associates Inc.Yogesh Rajkotia, USAIDHong Wang, Abt Associates Inc.
November 10, 2010APHA Conference, Denver
2
Rational
Background: Increasing interest in health insurance in developing countries Conflicting evidence on insurance’s protective effect against
financial burden of health care
Objectives: Evaluate financial protection effects of insurance in Ghana (2 districts): Amount of out-of-pocket payment (OOP) Likelihood of catastrophic OOP expenditure
3
Health financing in Ghana
Important milestones Free services in public facilities after Independence (1957) Nominal user fees early 1970s Significant user fees starting 1985 Exemption policy for indigents and other disadvantaged groups ~ unfunded
mandate
Implications of the “cash and carry” system Delay in or forego seeking care Low quality, inadequate services High OOP payment (50% vs. sub-Saharan Africa average of 39% - 2006)
4
National Health Insurance Scheme (NHIS)
Timing: Enacted in 2003 and started in 2005
Coverage: Open to all population, covered ~ 45% as of 2008
Revenue collection: 2.5% sales tax, 2.5% from formal sector contribution, premium contribution
from other members Premium exemption for indigenous and other disadvantaged populations
Benefit package: 95% of conditions (inpatient and outpatient care)
Public sector and accredited private facilities Management: centralized financing but decentralized implementation
5
NHIS early experience and impact
Implementation issues Delay in card issuance and provider reimbursement Low incentives to improve quality of insured care Provider discrimination against insured patients Informal payment to providers
Early impact evaluation (Chankova, Atim, and Hatt 2009; Frempong et al., 2009)
Increase service utilization of curative care Conflicting evidence on impact on MCH services
6
Data and variables
Survey of 2500 households in 2 rural districts, Offinso and Nkoranza, in late 2007 (11,617 individuals)
Dependent variables: One year OOP expenditure on curative care Likelihood of having catastrophic expenditure (thresholds: 5% income, 10%
income, 10% non-food consumption, 20% non-food consumption) Independent variables:
Main interest: Membership in NHIS Covariates: Household SES, ethnicity, urbanicity, self-reported health
status and chronic diseases
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Methods
Model specification: Yi = F (HIi, Xi, ei)Y: OOP amount, likelihood of catastrophic expenditureHI: membership in NHISX: covariatesE: error termsF: Two-part model for OOP amount and probit for
catastrophic expenditure
Direction of bias if adverse selection exists:Y=service utilization: positive biasY=OOP exp: negative bias
8
Sample description: breakdowns of OOP expenditure on curative care
Expenditure breakdowns (Amount in Ghana Cedi)
Non-members(N=6,718)
Members (N=4,899)
Acute illnesses and injuries
Informal care 2,839 4,913
Fees 3,854 346
Lab expenses 1,354 1,036
Other expenses 210 989
Unofficial payment to providers 174 472
Drugs purchased at facility 6,500 2,709
Drugs purchased outside facility 2,348 3,743
Antenatal care and delivery 6,442 4,475
Surgery and hospitalization 6,121 2,819
Total 29,843 21,503
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Sample description: incidence of catastrophic expenditure by quintile and HI status
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
1 2 3 4 5
quintile
inci
den
ce o
f ca
tast
roh
pic
ex
pen
dit
ure
(%
)
0
10
20
30
40
50
60
insu
ran
ce c
ove
rag
e (%
)
insurance 10% non-food 20% non-food 10% income 5% income
10
Results: NHIS effects on OOP expenditure
(1) (2)
Has HI from NHIS -33,821 -30,094
(20,379)* -20,157
Chronic health condition 40,605 ---
(38,229)
Bad health (self-assessed) 125,223 ---
(90,323)
District dummy Yes Yes
Individual and household characteristics Yes Yes
Assets and living conditions Yes Yes
N 11,617 11,617
Note: unit is Ghana Cedi. Robust standard errors in parenthesis. *significant at p<0.10. Effects are estimated with a 2-part model
11
Results: NHIS effects on the incidence of catastrophic expenditure
-2.00
-1.80
-1.60
-1.40
-1.20
-1.00
-0.80
-0.60
-0.40
-0.20
0.00
5% income 10% income 10% non-food 20% non-food
red
uct
ion
in p
rob
abili
ty o
f ca
tast
rop
hic
exp
Note: figures represent marginal effects of insurance obtained from probit estimation. Horizontal bars denote 95% CI
12
Results: NHIS effects among poor versus non-poor population
IndicatorsQuintile 1
(poorest)N = 1,762
Rest of population
N = 9,855
Exceeds 5% of income-0.016
(0.005)***-0.007 (0.004)
Exceeds 10% of non-food expenditure
-0.017 (0.005)***
-0.004 (0.004)
Exceeds 10% of income-0.013
(0.005)**-0.004 (0.003)
Exceeds 20% of non-food expenditure
-0.014 (0.005)***
- 0.003 (0.002)*
Note: figures represent marginal effects of insurance obtained from probit estimation. Robust standard errors are in parentheses. * significant at p<0.10; ** p<0.05; *** p<0.01
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Limitations
Potential adverse selection in insurance is not fully addressed
However, bias is likely negative, rendering assurance that effect is truly significant
Survey was conducted in 2 out of 138 districts, so results cannot be generalized
14
Discussion
Small effects on absolute amount of OOP payment raise concerns about implementation issues (informal payment, use of informal care, quality of insured services, etc.)
NHIS confirms function of HI as a safety net, i.e., protect against risk of catastrophic expenditure
Stronger effects among the poor justifies premium subsidies Ghana experience is highly applicable to many developing
countries, especially in sub-Saharan Africa, with similar health system features
Thank you
Reports related to this presentation
are available at www.HealthSystems2020.org
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