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

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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

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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)

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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

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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

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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

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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

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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

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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

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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

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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

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