 The 2002 Healthcare Conference Surviving or Thriving ? 29 September-1 October 2002 Scarman House, The University of Warwick, Coventry

Plenary 1b Trends in Critical Illness nOverview of the work of the Critical Illness Trends Research Group nNeil Robjohns Head of Pricing Munich Reinsurance (UK Life Branch)

Trends in Critical Illness n CI : A good story so far ? n Overview of CI Trends research n Simplistic Model of Disease Timeline n Illustrate Possible Future Scenarios n Implications : Storm Clouds or Clear Skies ?

Sales of New Individual Critical Illness Policies 1990 – 2001, plus 1 st Half of 2002

Sales of New Individual Critical Illness Policies 1994 – 2001, by Type of Cover

The CI Story So Far n Strong Sales and Sales Growth n Standardised Definitions nHelped sales by improving consumer and IFA confidence in the cover provided nBut also a “straightjacket” and possible constraint and drag on product evolution

CI Insured Experience n Early signs seemed encouraging, but … n Warning signs now emerging nExposure still very select nShape and duration of initial selection unknown nUnexpectedly long claim reporting delays nLarge, and difficult to rationalise, differences in experience between offices nOverall experience higher than expected (and ultimate still unknown) ? nPricing uncertainty as high as ever ! n CMI reports on CI experience eagerly awaited !

The CI Story So Far n Strong Sales and Sales Growth n Standardised Definitions n Warning Signs in Emerging Experience ? n High Prevalence of Premium Guarantees

Extract from Healthcare Conference 2001 Healthcare Guarantees : Current State of Play TAIPCILTCPMI 4 key sources of pricing error CredibilityHighMed/LowLow High AppropriatenessHighMediumLow High TrendsDownUp???Up ShocksRareSomeMany ?? Robustness of Definitions against medical advancesGoodGood ?Poor ? against social changeGoodPoorMediumPoor ? Prevalence of Guarantees 100%30%60%Low Typical Charge for Guarantees Nil25%10% ? ?

The CI Story So Far n Strong Sales and Sales Growth n Standardised Definitions n Warning Signs in Emerging Experience ? n High Prevalence of Premium Guarantees n Almost Universal Guarantees of CI Definitions n Growing move away from premium guarantees and also moves in favour of significant cover re-design

Trends in Critical Illness n CI : A good story so far ? n Overview of CI Trends research n Simplistic Model of Disease Timeline n Illustrate Possible Future Scenarios n Implications : Storm Clouds or Clear Skies ?

Critical Illness Trends Research Group Our Aims : n To examine underlying trends in the factors influencing UK Insured Critical Illness claim rates, and from these, to assess : nThe historic trend in incidence and death rates for the major CI’s nAny pointers for future trends in Standalone CI, Mortality and hence Accelerated CI. n Formed in March 2001

Group Members and our Current Focus Heart AttackMS Cancer & Stroke& TPD n Actuaries Azim Dinani Scott ReidSue Elliott Richard Morris Joanne WellsHamish Galloway Neil RobjohnsDaniel Ryan n Medical Experts Professor Rubens Richard Croxson Consultant Oncologist Consultant Cardiologist n Links : nActuaries Panel on Medical Advances nCMIB CI experience investigation nABI CI definitions group

Summary of Trends in CI Incidence and Mortality Best Estimate Avg Change % pa, England & Wales, Men, aged

Summary of Trends in Cancer Incidence and Mortality Average Change % pa, for Males, aged , over Size of Balls Indicates Relative Importance of Cancer Site, measured by Incidence Rates in 1997.

Summary of Trends in CI Incidence and Mortality Best Estimate Avg Change % pa, England & Wales, Men, aged

Summary of Trends in CI Incidence and Mortality Best Estimate Avg Change % pa, England & Wales, Women, aged

Critical Illness Trends Research Group Overview n Population Trends in England & Wales n Population Trends in Scotland nScottish data is far better than E&W !! n Further international comparisons n Modelling Trends neg: The impact of changes in smoking habits nAnd so also a view of trends for separate insured smoker and non-smoker categories

Smoker Proportion England and Wales, Adults,

Summary of Trends in Cancer Incidence and Mortality Average Change % pa, England & Wales, 1980 to 2000 Men, aged

Summary of Trends in Cancer Incidence and Mortality Average Change % pa, England & Wales, 1980 to 2000 Women, aged

Critical Illness Trends Research Group Overview n Population Trends in England & Wales n Population Trends in Scotland n Further international comparisons n Modelling Trends neg: The impact of changes in smoking habits n Variations within the population neg: by Deprivation Category (Scotland)

Relative CI Rates by Deprivation Category Scotland, 1989 – 93, Ages 40 – 59, Males

Relative CI Rates by Deprivation Category Scotland, 1989 – 93, Ages 40 – 59, Females

Trends in Critical Illness n CI : A good story so far ? n Overview of CI Trends research n Simplistic Model of Disease Timeline n Illustrate Possible Future Scenarios n Implications : Storm Clouds or Clear Skies ?

Simplistic Model of Disease Timeline

Simplistic Model of Disease Timeline Prevention - Examples n Standard of Living n Government targets to reduce health inequalities n Falling prevalence of smoking n “Slip, Slap, Slop !” n Early intervention (eg: hypertension, angioplasty, stomach ulcers, …) n Genetics ??

Subsequent pages may have a background colour that is a tint of that on the title page

Britain overtakes Germany...

... t o head Europe‘s Fat League

Obesity n “Obesity will become the norm” n “Obesity will overtake smoking as Britain’s top preventable killer” n “Obesity epidemic warning” n “Diet changes have increased cancer risk” n Obesity leads to increased rates of heart disease, some cancers, diabetes, blindness, kidney failure, …

Simplistic Model of Disease Timeline Prevention - Examples n Standard of Living n Government targets to reduce health inequalities n Falling prevalence of smoking n “Slip, Slap, Slop !” n Early intervention (eg: hypertension, angioplasty, stomach ulcers, …) n Genetics ?? But … n Obesity Epidemic

Simplistic Model of Disease Timeline Prevention - Possible Outlook for Trends n Generally positive, n… but beware obesity n Likely steady trend, n… but possible leaps forward (eg: Genetics ??) n Positive impact of falling prevalence of smoking will run out of steam n Reduced impact on insured lives ? n Little impact on cancer ?

Simplistic Model of Disease Timeline Detection - Examples Cancer Detection n “Dogs to sniff out cancer !” n “Gene test hope for bowel cancer” n “Colorectal screening cost-effective” n Breast Cancer Screening n PSA / Prostate Cancer

Breast Cancer Screening

Prostate Cancer “Screening”

Simplistic Model of Disease Timeline Detection - Examples n Cancer Screening nMedical / health value uncertain, … n… but new tests very likely to be commercially available n Troponin / redefining “Acute MI” n MRI scans / “Silent Strokes”

Simplistic Model of Disease Timeline Detection - Possible Outlook for Trends n Almost all negative (earlier claims with less severity) n… but could prevent claim event occurring n Probable step change / shocks n Even if not developed into national screening programmes, unleashes clear scope for anti-selective behaviour by insureds n CI definitions without a severity underpin are clearly vulnerable

nCancer Any malignant tumour characterised by the uncontrolled growth and spread of malignant cells and invasion of tissue. The term cancer includes … but the following are excluded : [pre-malignant] tumours ; [early stage] prostate cancers ; … nHeart Attack The death of a portion of heart muscle, due to inadequate blood supply, that has resulted in all of the following evidence of AMI : Typical chest pain ; New ECG changes ; The characteristic rise of cardiac enzymes, troponins or other biochemical markers….….. nStroke A cerebrovascular incident resulting in permanent neurological damage. Transient ischaemic attacks are specifically excluded CI Definitions

Simplistic Model of Disease Timeline Treatment - Possible Outlook for Trends n Expect improvements in mortality / morbidity, but after CI claim event n May reduce CI rates where CI definitions have a credible, effective severity underpin n If morbidity post CI-event is reduced, benefits become nearer to “windfall” status

Simplistic Model of Disease Timeline Non-Medical Factors n Interpretation of CI definitions nPolicyholder expectations nOmbudsman nLegal challenge nAttitudes of society at large to ill-health

Trends in Critical Illness n CI : A good story so far ? n Overview of CI Trends research n Simplistic Model of Disease Timeline n Illustrate Possible Future Scenarios n Implications : Storm Clouds or Clear Skies ?

Implications Storm Clouds or Clear Skies ? n Governments Health Policy is primarily aimed at : nSaving Lives nReducing health inequality n Our Healthier Nation nTarget for Cancer nTo reduce the death rate from cancer in people under 75 years by at least a fifth by saving up to 100,000 lives in total nTarget for Coronary Hear Disease / Strokes nTo reduce the death rate from coronary heart disease and stroke and related diseases in people under 75 years by at least two-fifths by saving up to 200,000 lives in total

Implications Storm Clouds or Clear Skies ? n Outlook for mortality remains very positive n But impact of medical advance on CI is far less clear nPotential steady gains from prevention measures nBut likely step-increases from disease / event detection nPossible gains from treatment mainly accrue to insureds under current definitions n… but key issue is high degree of UNCERTAINTY

Implications Storm Clouds or Clear Skies ? n Warning Signs from emerging CI experience n Pricing / Reserving uncertainty over current claim levels is high n Allowing for uncertainty over future trends adds an order of magnitude to pricing difficulty

Implications Storm Clouds or Clear Skies ? n At population level, trends over the last 20 years have been relatively gentle. nEven so, ballpark estimates of overall rate changes of +/- 10% over a decade are indicated. nStronger opposing forces have almost balanced - this will not always be the case n Trend is likely to differ for insured lives, segregated by smoker status n Examples presented earlier indicate possible magnitude of local changes n There are realistic chances of significant loss, … … or profit !

Implications Storm Clouds or Clear Skies ? n On individual CIs : nClaim Rate changes of 20% or more are easy to envisage nChanges of 50% do not feel at all remote nChanges of >> +100% ?? n On all CIs combined : nClaim Rate changes of 10% or more are easy to envisage nChanges of 25% sadly do not feel remote enough n How big a change should we conceive of at 1:100 or 1:1000 ? n High uncertainty will require high levels of theoretical Risk Based Capital

Implications Storm Clouds or Clear Skies ? n Availability of long-term premium guarantees has reduced and the cost has increased n Does the market need to go further ? neg: limiting duration of CI definition lock-ins neg: adding more effective severity underpins

Plenary 1b Trends in Critical Illness nOverview of the work of the Critical Illness Trends Research Group nNeil Robjohns