Equity and Health in the Era of ReformsGita SenIndian Institute of Management Bangalore

4th Krishna Raj Memorial Lecture on Contemporary Issues in Health and Social Sciences CEHAT / Anusandhan Trust, Mumbai, April 9, 2010

Acknowledgements• First of all, of course, to Krishna Raj, about

whose contribution to informed public debate in this country, enough can never be said. I am deeply honoured, beyond my ability to adequately express.

• Many thanks to the Anusandhan Trust, eSocialSciences; Dept. of Economics, Mumbai University; P.G. Dept. of Economics, SNDT Women’s University and Tata Institute of Social Sciences (TISS) for inviting me to give this lecture

Acknowledgements• I also want to acknowledge my long intellectual

partnership with Dr Aditi Iyer in our joint work on equity and intersectionality, and all the fun we have had doing it! This lecture is based partly on that previous work, and on our ongoing analysis of the NSS 60th round for which Aditi provides the data and analysis muscle!

• Prof Chandan Mukherjee who has been our great support and colleague in this work from early on.

• And to Vasini Vardhan, many thanks for her hard work on the literature review.

INTRODUCTION

Equity in health – why do we care?

• Isn’t a consideration of the level (average or that of the lowest in the socioeconomic order) enough? Why should we be concerned about relative levels?• 3 approaches: Ethicist / social activist versus

pragmatist /policy administrator▫ Raise the average level▫ Raise the minimum level▫ Reduce inequality

Equity in health – why do we care?

• A problem of communication?• A problem of information?• A problem of politics / ideology?• All the above, BUT• Focusing on the average level or on improving

the health of the worst off also plays safe; it doesn’t always ask hard questions about social structures that a focus on inequality almost inevitably leads to.

Inequality matters – Wilkinson’s answer• Richard Wilkinson: “Almost everyone benefits from

greater equality. Usually the benefits are greatest among the poor but extend to the majority of the population.”

• (Acknowledgement to Prof R Wilkinson for the next slides)

Health and Social Problems are not Related to Average Income in Rich Countries

Index of: • Life expectancy• Math & Literacy • Infant mortality• Homicides• Imprisonment• Teenage births • Trust• Obesity• Mental illness – incl.

drug & alcohol addiction

• Social mobility

Source: Wilkinson & Pickett, The Spirit Level (2009) www.equalitytrust.org.uk

Index of: • Life expectancy• Math & Literacy • Infant mortality• Homicides• Imprisonment• Teenage births • Trust• Obesity• Mental illness – incl.

drug & alcohol addiction

• Social mobility

Health and Social Problems are Worse in More Unequal Countries

Source: Wilkinson & Pickett, The Spirit Level (2009) www.equalitytrust.org.uk

Equity in health – the fallacy of congruence• Yes, inequality matters for health but what kind

of inequality?• Can different dimensions of inequality be viewed

as collapsible into each other?• Does focusing on economic class inequality tell

us enough? Does it tell us the right things?• Does how we look at inequality need to be both

multi-dimensional and intersectional?

Equity in health – the fallacy of congruenceWilkinson & Pickett: “…what matters is the extent

of social class differentiation. No one suggests that it is blackness itself which matters. Rather it is the social meaning attached to it – the fact that it serves as a marker for class and attracts class prejudice – which leads both to worse health and to wider income differences.” (Social Science and Medicine 62 (2006) pp 1778-9)

EQUITY IN HEALTH CARE 1986-87 TO 2004

Health care – 1986-87 to 2004

• Extends our earlier analysis (Sen, Iyer and George, EPW April 6, 2002) of NSS surveys on morbidity and health care (42nd round – 1986-87 and 52nd

round – 1995-96) to the 60th round – 2004• Looks at both economic class & gender –

interpretation draws on insights from our work in Koppal

• Some changes in definitions and reference periods which I will only touch upon in places, and are being discussed in detail in our forthcoming paper

Features of the benchmark period

India’ s health care system already highly inequitable by the mid 1980s prior to the start of economic reforms in 1991

>70% health expenditure out of pocketLarge rural – urban differences in availability of servicesPoor quality and uneven reach of public servicesHighly unregulated private sector

Features of the benchmark period contd

However:Public hospitals (even if doubtful quality) available to the poor especially for inpatient careSignificant drug price control (over 300 drugs) in the essential, controlled price listThriving (pre-WTO) indigenous drug production (through reverse engineering) kept drugs available and competitively

Key Questions• What happened in the period after economic

reforms began?• Important policy shifts:▫ Sharp reduction in the controlled drugs list leading to

significant increases in drug prices▫ Entry of user fees and two-tier services in public

hospitals – those below the poverty line are supposed to get services free including drugs, but this is rarely the case (under the counter payments, and drugs have almost always to be purchased outside)

• Did gender and class inequalities in access to care change?

Evidence

•We will look through gender and economic class lenses at:▫ untreated morbidity ▫ reasons for non-treatment ▫ the shifting public – private mix ▫ the cost of care• Simple gradient – gap methodology to

examine inequality

But first a word about self-reported illness

Concerns about under-reporting of illness especially by the poor and women led the National Sample Survey to try to improve coverage through better training and instructions to enumerators etc.

Q: what was the result?

Rates of perceived morbidity: All India

Rates of perceived morbidity: Male versus Female (Rural)

0

5

10

15

20

25

Quintile 1(poorest)

Quintile 2 Quintile 3 Quintile 4 Quintile 5(richest)

Rural

No.

per

100

per

sons

Male (1986-87) Female (1986-87)Male (1995-96) Female (1995-96)Male (2004) Female (2004)

Rates of perceived morbidity: Male versus Female (Urban)

0

5

10

15

20

25

Quintile 1(poorest)

Quintile 2 Quintile 3 Quintile 4 Quintile 5(richest)

Urban

No.

per

100

per

sons

Male (1986-87) Female (1986-87)Male (1995-96) Female (1995-96)Male (2004) Female (2004)

• What does the pattern over time in self-reported morbidity tell us? NSS made a serious attempt to improve its capture of illness; yet a class gradient has emerged in both rural and urban areas, and more for women than men. Very little gender gap among rural poor.• Not plausible that the rich are more ill• Under-reporting due to ‘normalisation’ of illness by

poor (both men and women) even more sharp in relative terms?

Q: whose ill-health is the NSS capturing better?

Summary Results – Morbidity ReportingMorbidity• 1986-87 (pre-reform benchmark, 42nd round)

– No significant class gradient (based on MPCE fractiles) or major gap in self-reported morbidity for either women or men

• 1995-96 (52nd round)– Across the board increase in self-reported morbidity,

with the emergence of significant class differences in reporting; also some more gender differences

• 2004 (60th round)▫ Even further sharpened class gradient for both women

and men; sharper gender differences but at the upper end

Rates of persons never treated: All India

Never treated vs discontinued treatment?• Difference between those never treated and

those who discontinued treatment?• Apparently - an increase in those discontinuing

treatment, becoming greater by 2004 and with a sharper gradient• May indicate a shift from never being treated to

discontinuing treatment even though illness continued

Persons ‘never treated’and ‘discontinuing treatment’

Rates of persons never treated: Gender divide (Rural)

0

5

10

15

20

25

Quintile 1(poorest)

Quintile 2 Quintile 3 Quintile 4 Quintile 5(richest)Rural

No.

per

100

aili

ng p

erso

ns

Male (1986-87) Female (1986-87)

0

5

10

15

20

25

Quintile 1(poorest)

Quintile 2 Quintile 3 Quintile 4 Quintile 5(richest)Rural

No.

per

100

aili

ng p

erso

ns

Male (1995-96) Female (1995-96)

0

5

10

15

20

25

Quintile 1(poorest)

Quintile 2 Quintile 3 Quintile 4 Quintile 5(richest)Rural

No.

per

100

aili

ng p

erso

ns

Male (2004) Female (2004)

Rates of persons never treated: Gender divide (Urban)

0

5

10

15

20

Quintile 1(poorest)

Quintile 2 Quintile 3 Quintile 4 Quintile 5(richest)

Urban

No.

per

100

aili

ng p

erso

ns

Male (1986-87) Female (1986-87)

0

5

10

15

20

Quintile 1(poorest)

Quintile 2 Quintile 3 Quintile 4 Quintile 5(richest)

Urban

No.

per

100

aili

ng p

erso

ns

Male (1995-96) Female (1995-96)

0

5

10

15

20

Quintile 1(poorest)

Quintile 2 Quintile 3 Quintile 4 Quintile 5(richest)

Urban

No.

per

100

aili

ng p

erso

ns

Male (2004) Female (2004)

Summary Results – Untreated morbidity

Untreated Morbidity• 1986-87 (pre-reform benchmark, 42nd round)

– Significant class gradient and gender differences in untreated morbidity – women and the poor worse off; gender gap mainly at the bottom (rationing?)

• 1995-96 (52nd round)– The class gradient worsened for all groups– Some improvement in rates for poorest women (not sure why) ,

but sharp worsening for poorest men – perverse catch up?– Gender gap tended to close at the bottom

• 2004 (60th round)▫ Not much change but some worsening of the gradient for rural

men – gender gap almost closed – perverse catch up at the bottom?

Insights from Koppal on untreated morbidity• Traditional analysis too simplistic and may

actually mask what is actually going on, not only in terms of gender, but even in terms of class• Apparent class results may actually be

gendered results

2. Method:Illustration of hypotheses testing

• Illustrative evidence from cross-sectional household health survey in Koppal district– 60 villages, 1920 households, 12,328 individuals– Health seeking and expenditures during pregnancy,

for short- and long-term illness

• Illustration of intersectional analysis for long-term illness: non-treatment and discontinued treatment

Non-treatment of long-term ailments

Likelihood of non-treatment of long-term ailments: Differences by gender and economic class

Poorestw omen

Poorw omen

Non-poorw omen

Poor men Non-poormen

Poorestmen

Odd

s ra

tios

6.00

4.00

2.00

1.00

3.00

5.00

■ p < 0.05 □ p > 0.05 □ Reference group

Discontinued treatment for long-term ailments

Likelihood of discontinued treatment for long-term ailments: Differences by gender & economic class

Odd

s ra

tios

1.75

1.50

1.25

1.00Poorest w omen

Poorest men

Poor w omen

Non-poor men

Non-poor w omen

Poor men

■ p < 0.05 □ p > 0.05 □ Reference group

Continued treatment for long-term ailments

Likelihood of continued treatment for long-term ailments: Differences by gender & economic class

Odd

s ra

tios

0.40

0.50

0.60

0.70

0.800.901.00

■ p < 0.05 □ p > 0.05 □ Reference group

Poorest w omen

Poor w omen

Poorest men

Non-poor w omen

Non-poor men

Poor men

Distribution of reasons for non-treatment: Rural India

0

20

40

60

80

100

Male (1995-96) Female (1995-96) Male (2004) Female (2004)

Rural

Perc

enta

ge

Medical facility unavailable Financial barriers Illness not "serious" Other reasons

0

20

40

60

80

100

Q1 Q2 Q3 Q4 Q5

Male (2004)

Distribution of reasons for non-treatment: Rural India

0

20

40

60

80

100

Q1 Q2 Q3 Q4 Q5

Male (1995-96)

Financial barriers Illness not "serious" Other reasons

0

20

40

60

80

100

Q1 Q2 Q3 Q4 Q5

Female (1995-96)

Financial barriers Illness not "serious" Other reasons

0

20

40

60

80

100

Q1 Q2 Q3 Q4 Q5

Female (2004)

Distribution of reasons for non-treatment: Urban India

0

20

40

60

80

100

Male (1995-96) Female (1995-96) Male (2004) Female (2004)

Urban

Perc

enta

ge

Medical facility unavailable Financial reasons Illness not "serious" Other reasons

0

20

40

60

80

100

Q1 Q2 Q3 Q4 Q5

Male (2004)

Distribution of reasons for non-treatment: Urban India

0

20

40

60

80

100

Q1 Q2 Q3 Q4 Q5

Male (1995-96)

Financial barriers Illness not "serious" Other reasons

0

20

40

60

80

100

Q1 Q2 Q3 Q4 Q5

Female (1995-96)

Financial barriers Illness not "serious" Other reasons

0

20

40

60

80

100

Q1 Q2 Q3 Q4 Q5

Female (2004)

Summary results – reasons for non-treatment• 1995-96 (52nd round)

– Gender difference – men more likely to say ‘financial reasons’ than ‘illness not serious’

–Significant class gradient in all groups• 2004 (60th round)▫ Even worse at the bottom in terms of

financial reasons; 40% of women in quintile 1 (rural), and almost similar for men▫ Yes; health care costs have increased for

everyone but more damaging for the poor

Health providers used for outpatient care: Rural India

Health providers used for outpatient care: Urban India

Health providers used for inpatient care: Rural India

Health providers used for inpatient care: Urban India

Summary results – public-private mix

1986-87• Private-public mix

–70% of outpatient (OP)care was in the private sector (private doctors), but

–60% of inpatient (IP)care was in the publicsector (largely public hospitals) – both rural and urban

• Cost of care–Private : public cost of care practically

equal in OP, but a little over double for IP

Hospitalised patients in public hospitals - Rural Class Distribution: 1986-87, 1995-96, 2004

y = 2.8802x + 2.7649

y = -0.6619x + 16.933 y = 1.1377x + 9.7351

0.0

10.0

20.0

30.0

40.0

00 to 10 10 to 20 20 to 40 40 to 60 60 to 80 80 to 90 90 to 100

MPCE Fractiles

1986-87 1995-96 2004Linear (1995-96) Linear (1986-87) Linear (2004)

Hospitalised patients in private hospitals - Rural Class Distribution: 1986-87, 1995-96, 2004

y = 5.2561x - 6.7386

y = 0.8385x + 10.932y = 3.4704x + 0.4043

0.0

10.0

20.0

30.0

40.0

00 to 10 10 to 20 20 to 40 40 to 60 60 to 80 80 to 90 90 to 100

MPCE Fractiles

1986-87 1995-96 2004Linear (1995-96) Linear (1986-87) Linear (2004)

Hospitalised patients in public hospitals - UrbanClass Distribution: 1986-87, 1995-96, 2004

y = 0.3122x + 13.037y = -1.511x + 20.33

y = -1.421x + 19.97

0.0

10.0

20.0

30.0

40.0

00 to 10 10 to 20 20 to 40 40 to 60 60 to 80 80 to 90 90 to 100

MPCE Fractiles

1986-87 1995-96 2004Linear (1995-96) Linear (1986-87) Linear (2004)

Hospitalised patients in private hospitals - Urban Class Distribution: 1986-87, 1995-96, 2004

y = 3.5131x + 0.2334

y = 0.2487x + 13.291

y = 1.7397x + 7.3269

0.0

10.0

20.0

30.0

40.0

00 to 10 10 to 20 20 to 40 40 to 60 60 to 80 80 to 90 90 to 100

MPCE Fractiles

1986-87 1995-96 2004Linear (1995-96) Linear (1986-87) Linear (2004)

Summary results – hospital useService utilization• 1986-87 (pre-reform benchmark, 42nd round)

– No major class gradient in overall hospital use for inpatient (IP) care – both rural and urban

• 1995-96 (52nd round)– Distribution of hospital use tilts sharply towards the

upper end– Those at the top use not only more of the private

hospitals but also of the public hospitals• 2004 (60th round)▫ Some flattening of the slope of the distribution but still

significant (except for public urban hospitals)

Expenditure on inpatient care: All India

0

2000

4000

6000

8000

10000

12000

Public Private

Rural

1986-871995-962004

0

2000

4000

6000

8000

10000

12000

Public Private

Urban

1986-871995-962004

Average medical expenditures on hospitalisation at constant (1986-87) prices

0

500

1000

1500

2000

2500

3000

3500

Public Private

Rural

1986-871995-962004

0

500

1000

1500

2000

2500

3000

3500

Public Private

Urban

1986-871995-962004

Source: Selvaraj and Karan (2009)

Summary results of the comparison

• Overall, reporting on illness, extent of non-treatment and discontinued treatment went up sharply• Serious increases in the costs of care, and in

financial reasons for non-treatment (related largely to drug prices but also possibly to user charges?)• Micro level in-depth studies on reasons for

households falling into poverty (e.g. Anirudh Krishna) show that health expenditures are a major reason (among the top 3)

Summary results of the comparison• Class gradients sharply worse in the mid-1990s with

some moderation in 2004 but still sharp• Gender gaps persist but moderated in some

instances – perverse catch up by poorest men in terms of non-treatment and financial reasons for it• Hospital use for care – the better off are more likely

to go to private hospitals for inpatient care but they use more of both private AND public hospitals (some reversal in urban public hospitals in 2004)• The poorest still depend on public hospitals (>55%

of use) even in 2004 even though they cater more to the rich

Recent policy trends

The only game in policy town is the National Rural Health Mission:

Many pluses – increasing health budget, focus on maternal mortality, strong leadership and management inputs, good technical backstopping, openness to civil society and to third party review

What about health inequality, overall access to the poor, and health costs? Drug prices?

Conclusions

• Health inequalities have both over time and cross sectional dimensions – both gender and class• Period of economic reforms has sharply

worsened access, use and cost of care to the poor• Non-treatment and discontinuation have gone

up

Conclusions• Gender differences are important but poorest men

appear to be catching up with poorest women in perverse ways• Caveat: what about caste?• However, our Koppal work raises larger

methodological issues about how to analyse the intersections between different dimensions of inequality• Simplistic class and gender analysis not enough –

may mask or even distort our analysis of what is happening

Closing words

• Studying inequality is not just about methodology but also politics…• Additional insights from Koppal about

intersectionality - Not just the extremes but what is happening to the groups in the middle – those who may be advantaged on one dimension and disadvantaged on others?

Closing words

• Nuanced, unprejudiced and open analysis is the best tribute we can pay to Krishna Raj’s extraordinary work and life…

• Thank you.