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Health alth Mark rket et Inquir quiry y Semina nar 1 Fe 1 Februar uary 2018 18

We are not where we were meant to be

2 Source: Ministerial Task Team on SHI, July 2005 Taken from IPASA research at https://goo.gl/xkR8DY

Medical schemes operate in an unbalanced incomplete regulatory

• framework. We have stopped part

way through point 3 on the intended trajectory. Purpose of solidarity based reforms was to prevent the industry excluding those in need of care.

“South Africa is unusual in having open enrolment and community rating without risk equalisation. This was not a policy oversight, but a question of timing, and the South African Department of Health considers that the environment is now ready for the introduction of a Risk Equalisation Fund (REF).”

Source: Prof Heather McLeod, 2005. (Emphasis added) Quoted by Minister of Health in the same year

Given the time that has passed, this point can be recharacterised as indeed being a policy oversight.

That the current regulatory environment permits anti selection should not be in question, but the extent and effect of the behavior is subject to some debate.

4

Three levels of anti-selection

5

1

Anti-selection into and out of the medical scheme environment

2

Anti-selection between schemes

3

Anti-selection between benefit options

6

1

Anti-selection into and out of the medical scheme environment

0,0% 2,0% 4,0% 6,0% 8,0% 10,0% 12,0% < 1 1-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Total population Current medical scheme Population earning above the tax threshold 0% 2% 4% 6% 8% 10% 12% <01 01-04 05-09 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75+ 2002 2016

The dip and the heavy tail in scheme membership indicate selective behavior. Both increase the cost base Its getting worse over time which increases costs over time. We estimate 1.3% - 1.9% pa

Stats SA, CMS data Medical scheme membership profile

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1

Anti-selection into and out of the medical scheme environment

Behaviour goes beyond ‘age only’. Maternity selection is good needs-based example

Stats SA, CMS data 0% 10% 20% 30% 40% 50% 60% 70% Under 1 1-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85+ Perentage female Total population Current medical scheme Population earning above the tax threshold 0% 5% 10% 15% 20% 25% 30% 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75+ Pro roportio tion n covered 2002 2016

While coverage overall is around 16% of the population, its closer to 25% for those over 40.

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1

Anti-selection into and out of the medical scheme environment

‘Dip’ in membership seen even in higher deciles, which suggests selection, compounded by affordability.

Stats SA 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75+ Proportion covered Decile 7 Decile 8 Decile 9 Decile 10

9

1

Anti-selection into and out of the medical scheme environment

CMS data

Long term trend of open schemes needing higher contribution increase than restricted schemes, including pre-GEMS, whilst in the same operating environment. Noting that

• pen schemes also have some employer

based membership. In 2017 restricted schemes had roughly 15% lower contributions and 5% richer benefits.

Average Annual GCI Increase pbpa (2000 - 2016) Average Annual GCI Increase pbpa (2000 - 2006) Average Annual GCI Increase pbpa (2007 - 2016) All open schemes 9.8% 11.4% 8.9% All restricted schemes 8.0% 8.3% 7.9% Open schemes excluding DHMS 9.8% 10.8% 9.2% Restricted schemes excluding GEMS 8.0% 8.3% 7.8%

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1

Anti-selection into and out of the medical scheme environment

Mitigation options: Some level of compulsion or means based fine for non participation. Mandated income cross subsidy Employer subsidies (noting family size issues) More stringent penalties for late joiners Stronger underwriting Positive solidarity Eases burden on public sector Directionally towards NHI Penalises those who need care Penalties at the time seem not to be effective

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2

Anti-selection between schemes

CMS data

<table of Mcleod>

(15,00) (10,00) (5,00)

• 5,00

10,00 15,00 20,00 25,00

Spectramed Selfmed Keyhealth Resolution Fedhealth Cape Medical Plan Medshield Topmed Compcare Medihelp Bestmed Suremed Health Sizwe DHMS Bonitas Genesis Momentum Hosmed Medimed Makoti Thebemed Transmed Parmed De Beers BP Sedmed WITS Anglo Tiger Brands Profmed Rhodes UKZN Anglovaal AECI Engen Grintek Lonmin Medipos Metropolitan SABC Motohealh Golden Arrow Quantum Nedgroup Barloworld Malcor PG Group Old Mutual Platinum Health Alliance-Midmed Libcare Rand Water TFG SAMWUMed Sisonke Bankmed Sasolmed GEMS Wooltru Pick n Pay CAMAF Massmart Witbank Netcare Impala SABC Naspers LA-Health Retail Imperial Remedi MBMed Umvuzo BMW Horizon POLMED Tsogo Sun Fishmed Glencore Open Restricted

Scheme risk profiles vary widely, which translates to different levels of claims. Open schemes worse on average. Perilous to ignore income dynamics.

Average age versus industry average

12

2

Anti-selection between schemes

24 schemes, 40 options, 3m lives, overall loss ratio 93%

Income cross subsidies within, and between schemes are important. Generally, restricted schemes are better able to cross subsidise on

• income. Previous reform pathways

included consideration of broader income cross subsidies.

0% 50% 100% 150% 200% 250% 5 000 10 000 15 000 20 000 25 000 Loss Ratio Grouped income band

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2

Anti-selection between schemes

Risk Equalisation or virtual pooling, along with income cross subsidies Stronger underwriting when moving between schemes Balance quick, easy and practical with what’s necessary Taking care to avoid unintended harm to those in need of care Sequencing of any such reforms are important so as to avoid adverse consequences Mitigation options:

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3

Anti-selection within schemes

CMS data

Illustrative example of option selection dynamics that are not evident when looking at high level data only.

15

3

Anti-selection within schemes

CMS data

Buydown behavior is evident over time, and costs schemes 1-2% per

• annum. Effect is higher for open

schemes than restricted schemes.

0% 5% 10% 15% 20% 25% 30% 35% 40% 2008 2009 2010 2011 2012 2013 2014 2015 1 2 3 4 Benefit option quartiles Percentage of medical scheme beneficaireis

16

3

Anti-selection within schemes

200 400 600 800 1 000 1 200 1 400 1 600

• 36 -33 -30 -27 -24 -21 -18 -15 -12 -9
• 6
• 3

3 6 9 12 15 18 21 24 27 30 33 36

Downgrades

Claims PLPM, inflation-adjusted Time of change Months Sample of Insight data, 2016

Drop in claims post downgrade less than the drop in contribution

17

3

Anti-selection within schemes

Upgrades

500 1 000 1 500 2 000 2 500

• 36 -33 -30 -27 -24 -21 -18 -15 -12 -9
• 6
• 3

3 6 9 12 15 18 21 24 27 30 33 36 Time of change Months Claims PLPM, inflation-adjusted Sample of Insight data, 2016

Sharp increases in claims (for PMB and non PMB claims) post upgrade, suggests selective behavior.

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3

Anti-selection within schemes

Sample of Insight data, 2016

Loss ratio impact in first year of option

• change. Both upgrades and

downgrades leave a scheme worse off.

50,0% 60,0% 70,0% 80,0% 90,0% 100,0% 110,0% 120,0% 130,0% Upgrade Downgrade Before After

Comments on other risk pooling issues raised

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Variety, choice and innovation trade off against solidarity and cross subsidy. Restricted schemes

• ffer less choice, greater solidarity and better cross subsidy; Open schemes offer more choice

and innovation. Important to get the balance right based on societal objectives. Benefit designs should be more directly comparable through some standardized templates. Self sustaining options are a self inflicted fragmentation of risk pools and unnecessary. The requirement could be relaxed or removed, with the CMS continuing to monitor scheme

• subsidies. Circular 8 of 2006 may be viable subject to allowing for income subsidies.