Progressivity and determinants of Out-of-

Pocket Payments in Zambia Felix Mwenge & John Ataguba

Health Economics Unit, University of Cape Town

Universal Health Coverage (UHC) has become a global policy objective

Achieving UHC depends to a large extent on how health care is financed

Most countries that have achieved UHC rely less on regressive financing mechanism (e.g. South Korea, Chile, Costa Rica)

OOP is one of such financing mechanisms found to be regressive in most countries

Most African countries still rely on OOP as a significant source of health financing

This has important implications on the achievement of UHC

Introduction

To assess the progressivity and determinants of out-of-pocket health care payments

in Zambia

Objectives

METHODOLOGY

Data Sources & Characteristics

Survey Name Year No. Of Households

LCMS I

1998 16,000

LCMS III 2004 18,000

LCMS IV 2006 19,000

Measure of Socio-economic Status• Equivalent household expenditure

Composition of OOP payments• Costs of medicines, fees to medical personnel (e.g.

Doctor / Health Assistant / Midwife / Nurse / Dentist, etc), payments to hospital/health centre/surgery , fees to traditional healer• Excluded health related expenses such as transport costs

and patient care costs

Progressivity of OOP payments

Kπ = C– G

Kπ = Kakwani index of progressivity

C = Concentration index of OOP payments

G= Gini index of equivalent expenditure

If Kπ = 0, OOP payments are proportionalIf Kπ < 0, OOP payments are regressiveIf Kπ > 0, OOP payments are progressive

Determinants of OOP payments (Logistic Regression)Dep variable = OOP payments (binary)Independent variables (hhsize, location, age_hh, sex_hh,

ms_hh, ed_hh, SES)

Determinants of size of OOP payments (Tobit Regression)Dep variable = OOP payments (continuous)Independent variables: (hhsize, location, age_hh, sex_hh, ms_hh, ed_hh, w_hh,SES)

FINDINGS

% of Households Reporting Illness/Injury

Socio-economic Status 1998 2004 2006

Quintile 1 19 19 22

Quintile 2 22 19 20Quintile 3 20 21 20

Quintile 4 20 21 20Quintile 5 20 20 18

Total 100 100 100

% of Households Reporting Paying OOP(OOP>0)

Socio-economic Status 1998 2004 2006

Quintile 1 11 15 13

Quintile 2 18 18 20

Quintile 3 21 21 20

Quintile 4 25 22 23

Quintile 5 25 23 24

Total 100 100 100

Mean Paid OOP per household in Kwacha (US$)

Socio-economic Status

1998 2004 2006

Quintile 1 445 (US$0.2) 3860 (US$0.8) 1076 (US$0.3)

Quintile 2 1165 (US$0.5) 3959 (US$0.8) 2989 (US$0.8)

Quintile 3 2475 (US$ 1.0) 4859 (US$1.0) 4568 (US$1.3)

Quintile 4 4671 (US$2.0) 9402 (US$2.0) 7693 (US$2.1)

Quintile 5 12355( US$5.2) 27287 (US$5.7) 26798( US$7.4)

Total 4219 (US$1.8) 9873 (US$2.1) 8623 (US$2.4)

Progressivity of OOP, 1998

Progressivity of OOP, 2004

Progressivity of OOP, 2006

Kakwani index of progressivity of OOP payments, 1998, 2004 and 2006

Year KπP-value (5% level of

significance Conclusion

1998 0.34 0.000 Progressive

2004 -0.85 0.2264 Proportional

2006 0.14 0.819 Proportional

Determinants of OOP PaymentsVariables Odds of spending OOP

1998 2004 2006

hhsize 1.07*** 1.08*** 1.08***

location_hhold 0.87***

age_hhead 0.94*** 0.96*** 0.98

sex_hhead 0.80*** 0.81*** 0.82***

marital status_hhead 1.35*** 1.35*** 1.44***

eduation_hhead 0.98*** 0.90*** 0.95***

expenditure quintiles 1.32*** 1.20*** 1.32***

n 14 033 16 763 16 331

Prob>F 0.0000 0.0000 0.0000

Determinants of size of OOP PaymentsVariables Size of OOP

Year 1998 2004 2006

hhsize 1543*** 4602*** 6133***

sex_hh -3298** -15715*** -16950**

ms_hh 4811*** 20134*** 32851***

education_hh -2274***

working_hh -11038**

Exp quintiles 7642*** 14129*** 29228***

constant -58162*** -151248*** -251830***

n 14 032 16 763 16 361

Prob>F 0.0000 0.0000 0.0000

CONCLUSION

Equity in health care payments requires that payments be progressive◦ contributions should be made according to ability to pay

Progressivity of OOP payments in 1998 could be due to concentration of payments among richer households compared to poor households

This phenomenon is also common in countries where poor households cannot afford to pay OOP◦ The results should be taken cautiously

OOP payments where proportional in 2004 and 2006o As a percentage of their total resources there was no difference in OOP

contributions between rich and poor households

Living in rural area was significantly associated with less likelihood of incurring OOP in 2006.

◦This could be due to abolition of user fees in all primary rural facilities in early 2006

Likelihood of spending OOP was high among richer compared to poorer households and larger households compared to smaller ones

OOP should be reconsidered as a means of paying for health care in Zambia if UHC is to be achieved

More progressive payment mechanisms should be considered to achieve UHC

Abolition of user fees should be extended to urban areas to achieve UHC

Policy Recommendations

Thank you for your attention

Acknowledge financial support from:NRF (South Africa)