Risk Pooling to Achieve Universal Coverage: Ghana

’

s National Health Insurance Scheme

Slavea Chankova Abt Associates Inc.

I I I

In collaboration with:

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

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

Number of households Number of individuals Individuals reporting illness/injury in past 2 weeks Individuals reporting hospitalization in past 12 months Women reporting delivery in past 12 months

Baseline 2004

1,805 9,554 413 203 298

Endline 2007

2,520 11,770 411 208 312

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: Nkoranza Offinso

Total sample Baseline 2004 (Nkoranza CBHI)

35% 0%

23% Endline 2007 (NHIS)

45% 25%

35%

Who Enrolls in NHIS?

 Enrollment increases with wealth quintile  Poorest are 3 times less likely to enroll compared to the richest 60% 52% 50% 40% 39% 40% 30% 30% 18% 20% 10% 0% Poorest Middle-poor Middle Middle-rich Richest

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 99% 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 100% 0-4 5-17 6% 18-34 4% 35-49 11% 50-69 98% 70+

Targeting of NHIS: Premium Exemptions for the Poor

 Exemptions have not benefited primarily those in the lowest wealth quintile 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% 64% 65% 59% 62% 60% 62% Poorest Middle-poor Middle Middle-rich Richest Total

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

100% 90% 80% 70% 60% 50% 40% 30% 20% 50% 36% 10% 0%

Used medication at home (p=0.009)

76% 44%

Sought care from informal providers (p<0.0001)

37% 70% 2004 2007

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

Utilization of Maternal Health Care

60% 50% 40% 30% 20% 10% 0% 100%  No significant changes between 2004 and 2007 in proportion of pregnant women receiving key maternal health services 2004 90% 80% 70% 73% 68% 2007 54% 55% 6% 6%

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

Likelihood of OOP Expenditures for Care

 Significant decrease in probability of incurring OOP expenditures for recent curative care, hospitalization, antenatal care (ANC), and delivery 100% 88% 90% 80% 87% 87% 74% 70% 57% 60% 55% 50% 43% 40% 30% 47% 2004 2007 20% 10% 0%

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

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

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

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

I I I

In collaboration with:

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