The impact of mandatory

membership on healthcare

affordability

Discussion points

Context

One approach

Another approach

Some conclusions

Context

1. High cost of cover relative to the public sector

2. Trend of above inflation contribution increases

3. Slow expansion of coverage

4. Scheme consolidation

5. Regulatory pathway

The income problem

0%

2%

4%

6%

8%

10%

12%

14%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

100.0%0

833

1 6

67

2 5

00

3 3

33

4 1

67

5 0

00

5 8

33

6 6

67

7 5

00

8 3

33

10 0

00

11 6

67

13 3

33

15 0

00

16 6

67

18 3

33

20 0

00

21 6

67

23 3

33

25 0

00

29 1

67

33 3

33

37 5

00

41 6

67

Pro

po

rtio

n o

f h

e p

op

ula

tio

n

Perc

en

tag

e o

f p

op

ula

tio

n b

elo

ng

ing

to a

med

ical sc

hem

e

Household monthly income

Medical Scheme % Fancy model People

Stats SA, IES, 2006

Health system reflects the broader economy

Mirrored in other sectors (education, food, housing, transport,

amenities)

Two Paths to Universal Coverage

1994 to 2007

Gradual, begin with highest paid

workers and their families.

Subsidies for workers earning below

tax threshold.

Medical Schemes are vehicles for

SHI, buy from private and

(increasingly) public providers.

Open enrolment, minimum benefits

(PMBs), community-rating, income

cross-subsidies, risk cross-subsidies,

mandatory contribution.

Competitive purchasers, with Risk

Equalisation Fund.

“Post-Polokwane” Dec 2007

ANC election promise: immediate

“within 5 years”

Tax and progressive social security

contribution.

Central buyer, with public and private

providers.

Role for medical schemes undefined

Package not yet defined.

Through SHI to NHI Direct to NHI

H McLeod, 2009 presentation

to the actuarial society

Forgotten medical schemes

amendment bill – with REF,

LIMS, etc

Regulatory Balance (Medical Schemes)

Open

enrollment

Guaranteed

benefits

Community

rating

Risk

equalisation

Mandatory

cover

Social Protection Sustainability

Risk

based

solvency

Price UtilisationAccess Equity

40

45

50

55

60

65

70

75

80

85

90

0 500 1000 1500 2000 2500 3000 3500 4000

Health spend per capita US$, 2010

Some more context – Outcomes & MDGs

SA

SA Public sector

SA Private sector

SA excluding HIV

Life Expectancy

*WHO, RGA Re

0

20

40

60

80

100

120

140

0 500 1000 1500 2000 2500 3000 3500 4000

Health spend per capita, US$, 2010

Some more context – Outcomes & MDGs

SA

SA Public sector

SA Private sector

Infant Mortality

*WHO, RGA Re

0

100

200

300

400

500

600

700

800

0 500 1000 1500 2000 2500 3000 3500 4000

Health spend per capita, US$, 2010

Some more context – Outcomes & MDGs

SA

SA Public sector

SA Private sector

Maternal Mortality

*WHO, Discovery

Onto mandatory membership

The traditional approach – look at age distributions

0

200

400

600

800

1 000

1 200

1 400

1 600

Female

Male

Yes - Male Yes - Female

No - Male No - Female

Prof H McLeod Preferred 2010 REF tables GHS 2010, Medical scheme member Y/N by age, gender

Medical Scheme Pensioner Ratio Avg Age

Yes 7.2% 31.63

No 5.1% 26.33

Results

Industry PMB Rate (2010) 345.15

Derived from GHS data 348.13

Based on 2002 industry statutory returns 320.00

Non Medical Schemes (2010 GHS) 294.22

GHS data provides a

good estimate

8.8% increases in

demographic costs

over 8 years

15% lower PMB

plpm for currently

uncovered lives

2010 PMB Reduction

Weighting 70/30 331.95 -4.6%

Weighting 80/20 337.34 -3.1%

Combining with current medical scheme population:

But

This approach has some shortcomings – only

captures age related section, and gender to some

extent

Ignores burden of disease, and selection timing,

actual state of health

Also, have a look at restricted scheme age profiles…

If only we had a control study without (or with much

less, anti selection)

Which brings me to another approach

Another approach

Consider whether Restricted scheme could provide a

control study versus Open schemes

– Similar / Same - provider issues, administration requirements,

managed care requirements, regulatory requirements, solvency,

community rating, PMBs

– Main differences – commission, marketing, open enrollment

We now have 11 years of data under these regulations to

review the impacts

Looking over time

0

200

400

600

800

1 000

1 200

Open

Restricted

Open schemes

relatively cheaper in

1990‟s (12%)

Open schemes

progressively more

expensive during the

2000‟s (14%)

True extent of

differences hidden by

the scale.

Now we consider from

2000 in more detail…

Gross Contributions, plpm

*CMS annual returns

Looking more closely

50

100

150

200

250

300

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Open

Restricted

Gross Contributions, plpm, indexed

30% higher contribution

increases over 10 years

Increases 2000-2010 Per annum

Open schemes 182% 10.9%

Restricted Schemes 118% 8.1%

CPI 79% 6.0%

Open scheme

contributions increased

2.6% faster than

restricted schemes,

which increased 2%

faster than inflation

*CMS annual returns

What has driven this divergence?

Is it GEMS and DHMS?

50

100

150

200

250

300

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Open

Restricted

Open Excl DHMS

Restricted excl GEMS

Gross Contributions, plpm, indexed

*CMS annual returns

Two largest schemes make almost no difference

Considering the components

Health care costs, plpm, indexed Non Health care costs, plpm, indexed

50

100

150

200

250

300

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Open

Restricted

Open excl DHMS

Restricted excl GEMS

50

100

150

200

250

300

350

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Open

Restricted

Open excl DHMS

Restricted excl GEMS

Main driver is health care costs, with

non health care costs also

contributing for open schemes

DHMS has had a significant impact on

overall healthcare costs (from 2005,

Keycare) , while GEMS has had only a

minor effect. DHMS has had little effect on

open scheme NHC costs while GEMS had

a significant impact. *CMS annual returns

Components

Average Increases pa

2000-2010

Contribution to GCI

increase

Open Restricted Open Restricted

GCI plpm 10.9% 8.1%

Healthcare costs plpm 9.2% 7.6% 67.6% 83.5%

Non Health plpm 12.5% 6.5% 15.4% 7.1%

What about sustainability

0

10

20

30

40

50

60

70

80

90

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Open

Restricted

Surplus, plpm Reserve levels, plpm

Restricted schemes making more surpluses, and have

higher reserve levels, despite having had lower

contribution inflation

0

1 000

2 000

3 000

4 000

5 000

6 000

7 000

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010

Open

Restricted

Open excl DHMS

Restricted excl GEMS

*CMS annual returns

Don‟t„ forget

Real price inflation is only a part of the cost

escalation issue – utilisation is a much bigger force

Don‟t let Regulation 8 take your focus away from

issues that are even more important, like continuing

to lobby for other reforms such as mandatory

membership, solvency reform, risk equalisation

Summary

Open versus restricted schemes provide a case study of

the effect of anti selection

Open scheme contributions could be lower by 23% if we

had had no anti selection

This equates to R13.5 bn in 2010

Which is:

– R234 plpm for open schemes

– R517 pmpm for open schemes

– At least 14% lower contributions for the whole industry (open

and restricted)