A regulators perspective: evidence of anti-selection and experience in addressing risk pooling failures and benefit design Council for Medical Schemes 1
Contents Introduction Anti-selection evidence Experience in risk pool regulation Conclusion Impact analysis 2
Introduction In SA there is limited empirical evidence on the factors influencing member movement between different options and medical schemes. International evidence - Health Insurance (Netherlands, China, Belgium) 5 case studies (2004-2014) These studies describes the impact of anti-selection within particular conditions and circumstances 3
Introduction Anti-selection behaviour can be analysed according to the following categories: Age: young people defer scheme membership Gender: females during child-bearing ages Disease burden: people with expensive illnesses to treat or multiple illnesses Benefit options: members selecting options with comprehensive benefits only when their likelihood of needing those benefits is high Voluntary membership where mandatory participation is not enforced through legislation Employer group preferences and splitting of the risk pools 4
Anti-selection evidence Case study 1 (Chronic Renal Failure) There is anecdotal evidence that older people with chronic renal failure needing dialysis are encouraged to join medical schemes in order to get dialysis in the private sector, as there are limited resources in the public sector. The impact on a medical scheme is substantial. In 2017, the average cost of chronic renal failure was R27 590 per patient per month according the data from the Scheme Risk Measurement (SRM, formerly REF). Such costs have an impact on contribution increases for all members within a benefit option and a scheme as a whole. 5
Anti-selection evidence Case study 2: (Pregnancy) There are instances where medical scheme cover will be taken by couples or single women who are planning to have children. The medical and accommodation costs associated with the pregnancy will be covered by the medical scheme. Because of information asymmetry, plans to start a family are considered privileged information and deliberately not disclosed to the medical scheme. 6
Anti-selection evidence Case Study 3: Age specific anti-selection: Polmed The analysis of Polmed claims data for the years 2006 and 2007 showed that various categories of anti-selection have affected the cost of Polmed options, namely: Buy-downs from the higher to the lower plans by older members. This category of anti-selection shows that the number of members in age categories from 35 upwards remained constant or declined in the higher plan, while growing in the lower plan. The data also showed that the level of hospital costs per beneficiary increased markedly with age. This trend was apparent in all the other benefit categories. 7
Anti-selection evidence Case study 4: Mcleod and Ramjee (2007) Undertook a study which compared the relationship between income, age and gender to expose the anti-selection behaviour that occurs in the voluntary medical schemes environment. This analysis was undertaken in 2007 where CMS Risk Equalisation Fund (REF) data was analysed. This study showed higher numbers of maternities than expected in the REF pricing each year. Furthermore, unpublished scheme investigations also showed substantially higher maternities than expected as well as some evidence of increasing numbers of women who join schemes before giving birth and leaving schemes thereafter (Mcleod & Ramjee, 2007). 8
Anti-selection evidence Case study 5 : Large scheme experience (2014) 16% 14% 12% 10% 8% 6% 4% 2% 0% Duration on Scheme Musculoskeletal conditions 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 > 15 Years on Scheme 14.31% who claimed biologics for musculoskeletal conditions had been on the Scheme for <1 year Medical Scheme presentation to CMS, 2014 9
Anti-selection evidence Duration on Scheme - Multiple Sclerosis (MS) 18% 16% 14% 12% 10% 16.52% who claimed interferon had been on the Scheme for <1 year 8% 6% 4% 2% 0% Years on Scheme Medical Scheme presentation to CMS, 2014 10
Number of lives Anti-selection evidence 16 000 14 000 Duration on the scheme before first maternity admission (2008-2013) 34% join within 9 months of the maternity event 12 000 10 000 8 000 6 000 4 000 7 155 8 933 9 976 8 084 13 424 9 315 11 172 2 000 4 742 1 496-0-3 months 4-6 months 7-9 months 10-12 months 13-18 months 19-24 months 2-3 years 3-4 years 4-5 years 153 >5 years Other underwriting categories 7 155 8 933 9 976 8 084 13 424 9 315 11 172 4 742 1 496 153 11
Withdrawal rate Anti-selection evidence 35,0% 30,0% 1-year withdrawal rate of lives who joined <12 months before maternity admission 32,1% 29,8% 29,9% 25% of these leave the scheme within 12 months of the maternity event 25,0% 25,1% 20,0% 15,0% 10,0% 5,0% 0,0% 0-3 months 4-6 months 7-9 months 10-12 months Underwriting category A 29,8% 32,1% 29,9% 25,1% Duration on scheme before first maternity admission 12
Experience in addressing risk pooling failures 13
Contents Introduction Risk pool size Case studies Benefit option registration Regulatory gaps Conclusion Impact analysis 14
Introduction Pooling involves the accumulation of health revenues on behalf of a population for eventual transfer to providers Core objective for pooling arrangements: maximize redistributive capacity, financial protection and equity in service use relative to need for care Size (bigger) and diversity (more) are key characteristics to consider in reform design WHO Advanced Course on Health Financing for Universal Health Coverage, Barcelona, Spain 12-16 June 2017 15
Introduction: SA healthcare system Revenue sources General taxation Medical schemes (voluntary contribution) uninsured VHI Pooling MOH Purchasing 9 provinces 82 medical schemes & 287 benefit options OOPS Provision private & some public Population poor (84%) middle class & rich (16%)
Introduction: SA healthcare system Revenue sources Pooling Purchasing Provision General taxation Fiscal constraints! uninsured Poor central MOH bureaucracy Line-item 9 provinces budgeting Passive purchasing RWOPS High unemployment rate Fragmented risk pools Medical schemes (voluntary Affordability contribution) challenges! VHI 82 medical schemes OOP Duplicated administrative systems S & 287 benefit options Fee-for-service Poorly designed PMBs private & some public Profit motive Up-coding Population poor (84%) middle class & rich (16%)
Some signposts that tell us we have a problem Pooling Is pooling highly fragmented and complex? Benefit design Population not aware of entitlements and obligations? 18
Risk pool size 19
Total number of benefit options Risk pool size Number of benefit options (2006-2015) 450 400 350 300 250 200 150 100 50 0 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Open schemes Restricted schemes All Schemes 20
Number of benefit options Risk pool size 300 Number of loss making options (2006-2015) 250 247 200 231 218 223 (231 150) 192 150 156 145 132 145 150 100 50 0 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 Open schemes Restricted schemes All Schemes 21
Number of options Risk pool size 140 120 Option size (number of beneficiaries) categories, 2015 115 100 80 83 60 48 40 27 20 0 <=1 000 >1 000 & <= 6 000 >6 000 & < = 30 000 >30 000 22
Community rate analysis - schemes Impact analysis 23
1 7 13 19 25 31 37 43 49 55 61 67 73 79 85 91 97 103 109 115 121 127 133 139 145 151 157 163 169 175 181 187 193 199 205 211 217 223 229 235 241 247 253 259 265 271 277 283 289 295 301 Community rate pbpm, Decebmer 2016 Community rate analysis - options Open Restricted Industry Community Rate R3 500 R3 000 R2 500 R2 000 R1 500 R1 000 R 745,6 R 500 R 0 Benefit Options Impact analysis 24
COMMED (2016): Case studies Total membership 7981 Number of option 4 Membership on a per option level: Deluxe 869 Standard 2195 Roots 4894 Shina 23 25
Case studies Naspers Medical Fund (2016): Total membership 16100 Number of option 3 Membership on a per option level Option A: 2900 Option B :3500 Option C : 9700 1 case Gaucher's disease crippling the schemes 26
Benefit option registration Deregistration of an option is normally considered as a last resort, such regulatory intervention has a potential of creating pricing uncertainty and can lead to member dissatisfaction. Close monitoring of loss making options. Impact analysis 27
Benefit option registration If the benefit option continues to be noncompliant as per provisions outlined above, the Registrar reserves the right to deregister those benefit options. 28
Section 63, Section 24 (2) (d), Reg 2 (3) Minimum number of members required for the registration of a medical scheme established after these regulations have come into operation is 6000.. SUREMED case : The judge set aside the decisions of the Registrar and the Appeal Board. The high court held that it was not competent for the Registrar to confirm the exposition because the parties merger agreement was rendered void when Suremed s members voted against the merger. Section 63(11) does not authorise a medical scheme to enter into a transaction that is in conflict with its rules. The high court further held that the Registrar did not have the power to confirm an exposition which was not underpinned by a valid and binding agreement. 29
Regulatory gaps Amendment of the MSA : Regulation 2(3) to explicitly state that all registered medical schemes should always have the minimum of 6000 members whether or not these medical schemes were registered before the amendment of the 1967 Act. Explicitly state corrective measures to be followed by the Regulator in addressing non-compliance. 30
Regulatory gaps Amendment of the MSA: Outline of the required membership base at a benefit option l evel. Section 33 (2) (c) does not permit withdrawal of the benefit option if that option is financially sound, even if that benefit option has low membership. 31
Amendment of the MSA: Regulatory gaps A clear interpretation of public interest as outlined within Section 24 (2) (f) is also required. Such interpretation needs to take into consideration membership growth requirements, consumer preference and the impact of option selection by employer groups 32
Conclusion World Health Organisation recommends that health financing reforms should not only focus on increasing the level of prepayment funding for the risk pools, but should also consider policy options to encourage risk pool consolidation. Implementing such measures without paying proper attention to changes in risk pooling can result in increased fragmentation and compromised equity and efficiency goals (WHO 2010). 33
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