EQUITY PROFILES OF THREE SOCIAL FRANCHISE NETWORKS IN WEST AFRICA Nirali Chakraborty, Ph.D

Research Advisor for Reproductive Health 9 th World Congress on Health Economics, Sydney, Australia

10 July 2013

Outline

    Background – – Franchising Study sites Equity calculation methodology Results – – – Benin Democratic Republic of Congo (DRC) Mali Implications PAGE 2

24 FRANCHISES IN 23 COUNTRIES +10,000 FRANCHISEES 10 MILLION PER YEAR CLIENTS

SOCIAL FRANCHISING AT PSI

Goals of Social Franchising

+

✓

$ Health Impact

Improving population health

Quality

Ensuring adherence to clinical standards for client care

Cost-Effectiveness

Providing services at equal or lower cost to alternatives

Equity

Enabling the poorest to access services

Market Expansion

Delivering services that would not otherwise be provided

Study objectives

  Pilot equity measurement at franchises Justify use of national or sub-national reference population, for program decision making page 5

Study context

  Client exit interviews  Equity benchmarked to reference population Franchises primarily urban and peri urban page 6

Benin

Indicator

CPR among married women Unmet need among married women Under 5 mortality Has electricity Urban residence Private Health Expenditure/THE Out of Pocket/PHE

Total

6.1

27.3

136 27.9

41.4

46.7

91.2

Urban

9.0

Rural

4.5

26.3

116 56.6

27.9

145 8.5

Source: DHS 2006 and WHO Global Health Observatory 2011 data page 7

Benin – ProFam franchise

    Offers Family Planning, SRH/HIV and MNCH services 185 clinic outlets ~33% of providers are MDs ~100,000 clinic visits recorded in 2012 Source: 2013 Social Franchising Compendium, www.sf4health.org

page 8

Democratic Republic of Congo

Indicator

CPR among married women Unmet need among married women Under 5 mortality Has electricity Urban residence Private Health Expenditure/THE Out of Pocket/PHE

Total

5.8

26.9

155 15.2

45.4

66.3

65.7

Urban

9.5

Rural

3.3

28.1

122 36.6

26.1

177 1.1

Source: DHS 2007 and WHO Global Health Observatory 2011 data page 9

DRC – Réseau Confiance

    Offers Family Planning, MNCH and Water Purification services 138 clinic outlets ~15% of providers are MDs ~192,000 clinic visits recorded in 2012 Source: 2013 Social Franchising Compendium, www.sf4health.org

page 10

Mali

Indicator

CPR among married women Unmet need among married women Under 5 mortality Has electricity Urban residence Private Health Expenditure/THE Out of Pocket/PHE

Total

6.9

27.6

215 16.6

33.7

54.9

99.6

Urban

13

Rural

4.2

28.4

158 47.4

27.2

234 3.2

Source: DHS 2006 and WHO Global Health Observatory 2011 data page 11

Mali – ProFam franchise

    Offers Family Planning, SRH/HIV and MNCH services 71 clinic outlets ~42% of providers are MDs ~43,000 clinic visits recorded in 2012 Source: 2013 Social Franchising Compendium, www.sf4health.org

page 12

PAGE 13

Equity measurement methodology

Data collection

Placing clients within reference population

1.

2.

3.

4.

5.

6.

Principal Components Analysis on weighted DHS asset ownership data Capture eigenvector from first principal component for each asset, and quintile cut-points from asset index Standardize Client data to DHS data Multiply each asset by eigenvector Sum (Std value*eigenvector) for each client Place clients within DHS quintiles Calculation done twice: National population Urban only

Mathematically speaking…

     Let A i1 =Asset score for each household

i v i

household

i

in DHS in DHS Let  v = Value of eigenvector from first component for variable

v

Let A i2 =Asset score for each client

i

sampled DHS data Client data page 16

Results: Client wealth profile

 Wealth quintiles of franchising clients, within national reference population

Quintile

1 (Poorest) 2 3 4 5 (Richest)

Benin

n=535 3.4

2.4

4.3

13.1

76.8

DRC

n=242 0 0 0 9.1

90.9

Mali

n=293 0 0 0.3

13.9

85.7

page 17

Results: Client wealth profiles in context

Benin – ProFam Franchise

Quintile

Poorest Quintile 2 Quintile 3 Quintile 4 Richest

National

3.4

2.4

4.3

13.1

76.8

Urban

6.7

8.8

11.4

33.3

39.8

90 80 70 60 50 40 30 20 10 0 National Urban page 18

Results: Client wealth profiles in context

DRC – Réseau Confiance

Quintile

Poorest Quintile 2 Quintile 3 Quintile 4 Richest

National

0 0 0 9.1

90.9

Urban

0 4.6

12.8

40.9

41.7

100 90 80 70 60 50 40 30 20 10 0 National Urban page 19

Results: Client wealth profiles in context

Mali – ProFam Franchise

Quintile

Poorest Quintile 2 Quintile 3 Quintile 4 Richest

National

0 0 0.3

14.0

85.7

Urban

0.3

2.1

4.1

15.0

78.5

90 80 70 60 50 40 30 20 10 0 National Urban page 20

Implications

  Social Franchise community of practice is recommending client equity to be benchmarked against national reference population For program decision making, sub-national reference population may be more informative   In these 3 countries, franchises appear to serve a wealthy population segment Do social franchises serve the poor? Should social franchises aim to serve the poor(est)?

page 21

page 22 Acknowledgements: I gratefully acknowledge the PSI research managers from the three countries where this data was collected: Cyprien Zinsou (Benin), Willy Onema (DRC), and Mamadou Bah (Mali).

Questions?

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