Abt Associates Inc.  In collaboration with:I Aga Khan Foundation I BearingPoint I Bitrán y Asociados I BRAC University I Broad Branch Associates I Forum One Communications I RTI International I Training Resources Group I Tulane University’s School of Public Health

Risk Pooling to Achieve Universal Coverage: Ghana’s National Health

Insurance Scheme

Slavea Chankova

I. BACKGROUND

The National Health Insurance Scheme (NHIS)

Established by legislation in 2003 Goal: equitable and universal access to health care Coverage reached 66% in 2010 Evaluation of NHIS

Designed in anticipation of NHIS implementation Collaboration between Health Systems 20/20 project and

Health Research Unit - Ghana Health Service

Key Features of the NHIS

Managed by district-level mutual health insurance schemes

Providers: all public health facilities and accredited private providers

Benefits: 95% of disease conditions, essential drugs Enrollment

Open to all with sliding-scale premium contributions starting at about $5 per adult

Premium exemptions for children (under 18), elderly (70+), indigent, and pregnant women (as of 2008)

II. EVALUATION DESIGN

Evaluation Questions

Who has enrolled in the NHIS? Do enrollment rates differ among different socio-economic groups? Is there evidence of adverse selection in NHIS enrollment? How well-targeted have premium exemptions been?

What is the impact of the NHIS on the utilization of health services?

What is the impact of the NHIS on out-of-pocket expenditures for health care?

Evaluation Design

Pre-post study design Baseline in September 2004 Endline in September 2007 Implementation of NHIS in study sites started in 2005

Cross-sectional household surveys in 2 districts Nkoranza (had CBHI at baseline) Offinso

Study Sample

Baseline2004

Endline2007

Number of households 1,805 2,520

Number of individuals 9,554 11,770

Individuals reporting illness/injury in past 2 weeks

413 411

Individuals reporting hospitalization in past 12 months

203 208

Women reporting delivery in past 12 months

298 312

Analytic Methods

Pre-post comparison of means for key indicators Regression models

Control for differences in socio-economic characteristics between baseline and endline samples

Probit and logistic regression models Results were robust to analytic methods

III. RESULTS

Sample Characteristics

Poor rural population General improvements in socio-economic characteristics between 2004 and 2007 Health insurance coverage:

Baseline 2004(Nkoranza CBHI)

Endline 2007(NHIS)

Nkoranza 35% 45%

Offinso 0% 25%

Total sample 23% 35%

Who Enrolls in NHIS?

Enrollment increases with wealth quintile Poorest are 3 times less likely to enroll compared to the richest

18%

40% 39%

52%

30%

0%

10%

20%

30%

40%

50%

60%

Poorest Middle-poor Middle Middle-rich Richest

% o

f w

ealt

h q

uin

tile

en

rolle

d in

NH

IS

Who Enrolls in NHIS?

Factors associated with higher likelihood of NHIS enrollment* Richer wealth quintile Education of household head Female headed household Female gender Age: children and the elderly more likely to enroll, compared to

18-49 yr old Self-reported chronic illness At least one household member is part of a community solidarity

scheme

* Results from multivariate regression (variables with statistically significant coefficients)

Targeting of NHIS: Premium Exemptions for Children & Elderly

Age-based exemptions have worked as intended But nearly all enrolled (97%) had paid a registration fee

100%

6% 4%11%

98%99%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-4 5-17 18-34 35-49 50-69 70+

% o

f N

HIS

mem

ber

s ex

emp

t fr

om

pre

miu

m

Targeting of NHIS: Premium Exemptions for the Poor

Exemptions have not benefited primarily those in the lowest wealth quintile

64%59% 62% 60% 62%65%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Poorest Middle-poor Middle Middle-rich Richest Total

% o

f N

HIS

mem

ber

s ex

emp

t fr

om

pre

miu

m

Adverse Selection in Enrollment

Strong evidence of adverse selection based on health status

NHIS-insured almost 3 times as likely to report illness in past 2 weeks, compared to uninsured

55% of those with chronic illness insured, compared to 34% of those without

No evidence of self-selection in enrollment related to pregnancy

36% of women with delivery in the past 12 months were insured at time of delivery, compared to 33% of women who did not have a delivery

Utilization of Care for Recent Illness or Injury

50%

37%

70%76%

44%36%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Used medication at home (p=0.009) Sought care from informalproviders (p<0.0001)

Sought care at a modern healthcare provider (p<0.0001)

Per

cen

t o

f in

div

idu

als

sick

in

pas

t 2

wee

ks

2004

2007

Utilization of Maternal Health Care

No significant changes between 2004 and 2007 in proportion of pregnant women receiving key maternal health services

73%

6% 6%

54%

68%

55%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

4 or more ANC visits (p>0.10) Delivery in health facility (p>0.10) Delivery by c-section (p>0.10)

% o

f w

om

en w

ith

del

iver

y in

pas

t 1

2 m

on

ths

2004

2007

Likelihood of OOP Expenditures for Care

Significant decrease in probability of incurring OOP expenditures for recent curative care, hospitalization, antenatal care (ANC), and delivery

87% 88%

74%

55%

47%

87%

43%

57%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Recent curative care (p<0.01) Hospitalization (p<0.01) ANC (p<0.01) Delivery (p<0.01)

% w

ith

po

sit

ive

OO

P e

xp

en

dit

ure

s f

or

ca

re

2004

2007

Changes in OOP Expenditures for Care

Average expenditures for treatment declined significantly for most services: 41% decrease for curative care (from $2 at baseline) 44% decrease for hospitalization (from $25 at baseline) No significant decrease for ANC (remained at about $3) 30% decrease for delivery (from $8 at baseline)

No significant changes in average amount paid by those who had positive OOP expenditures

Limitations

Results from 2 districts (out of 138) so cannot be generalized to whole country

Changes between 2004 and 2007 likely reflect impact of NHIS, but may also be influenced by other factors (e.g. other socioeconomic or policy changes occurring simultaneously)

Small samples for some indicators (e.g. hospitalization) limit the ability of the study to detect significant changes

IV. CONCLUSIONS & POLICY IMPLICATIONS

NHIS Enrollment

Age-based exemptions from NHIS premiums for children and the elderly have worked as intended But this may have potential implications for NHIS sustainability

Strong wealth effects observed for NHIS enrollment Exemptions for the poorest groups need to be strengthened to ensure

equitable enrollment in NHIS

Evidence of adverse selection: those with poorer health status are more likely to enroll and more likely to utilize care Implications for DMHIS sustainability

Utilization and OOP Expenditures

Substantial increase in use of formal medical services for illness; decrease in self-treatment and informal care-seeking

However, no improvement in maternal care-seeking Need to explore non-financial barriers for seeking care

Insurance has been very effective at reducing out-of-pocket expenditures for curative care and hospitalization, as well as for maternal care

Acknowledgements

Abt Associates -- Health Systems 20/20: Laurel Hatt, Sara Sulzbach, Hong Wang, Ha Nguyen

Ghana Health Service/Health Research Unit: Dr. John Gyapong, Bertha Garshong

USAID: Yogesh Rajkotia, Karen Cavenaugh, Mary Ellen Stanton

Abt Associates Inc.  In collaboration with:I Aga Khan Foundation I BearingPoint I Bitrán y Asociados I BRAC University I Broad Branch Associates I Forum One Communications I RTI International I Training Resources Group I Tulane University’s School of Public Health

Reports related to this presentation are available at: www.HS2020.org

Presentation will be posted at: http://www.abtassociates.com/HSRsymposium