International evidence on medical spending Robert Lieberthal October 6, 2011

Acknowledgements Funding from the Agency for Healthcare Research and Quality Lots of great input  My thesis committee  Casualty Actuarial Society review committee  Participants at the following conferences 2011 CAS Reinsurance Conference 2011 American Risk and Insurance Association Annual Meeting 47 th Actuarial Research Conference

Outline I would like to predict the effect of the PPACA on medical spending growth  Use health systems in other countries as a model U.S. and other countries aren’t so different Modeling medical spending across countries is challenging Common trade-off—degree of model fit versus flexibility of prediction

Foreign data may not help predict U.S. spending High spending in the U.S.  Absolute spending  Percent of GDP  Per capita (Still) no universal health insurance in the U.S.  Significant uninsured minority  Most developed countries have universal or near universal coverage Large private sector in U.S. healthcare  Relative to other countries  Public companies concentrated in pharmaceuticals  Some countries have physician private practice

U.S. spending is high and growing Medical spending as a share of GDP in four OECD countries

U.S. and other countries face similar challenges Unsustainable rates of spending growth  Especially for government budgets Multiple rounds of health reform  Serially address access, cost, quality Defining the role of insurance  PPACA was centered on this Health insurance, long term care insurance  Medical malpractice next?

U.S. spending growth is ordinary but unsustainable Per capita spending growth rates in 11 OECD countries

U.S. spending volatility is low Per capita spending growth rates in 11 OECD countries

Public spending drives a lot of the volatility

Better models require a lot more data Each country has approximately 50 data points  Not like price, which is monthly  Quantity is more important than price in determining total spending Many moving parts  Multiple policy changes  Demography  Macroeconomic shocks Strong unit roots  In overall spending  In the growth in spending in many countries High autoregressivity?  It’s hard to tell  Possible spuriously low standard errors Forecast effects  1-2 years is ok  5-10 or more is a problem

Solutions to forecast errors in medical spending Liability side—better predictions  Better modeling of spending growth  Prediction markets Asset side—find a hedge  TIPS inflation hedging bonds  Macromarkets  May not exist—incomplete securities market Public policy  Government reinsurance for health insurance  Could exacerbate problems in other lines linked to medical care

Many problems with medical spending are out of our hands Medical spending is linked to overall economic growth GDP growth, demography even less controllable Medical trend is not outrageous in the U.S.  Trend = GDP growth + Rate of aging  Fits average prior trend well  Same for other countries PPACA  May fix some problems  Some fixes may cause spill overs

The best solutions involve humility Challenges involve an uncertain future  Will we get more volatility like other countries with publicly funded healthcare?  Significant trend volatility to deal with here and abroad  Trend breaks and implications for long-term forecasts Public policy implication—exercise caution  In changing the healthcare system  In writing long tailed insurance and reinsurance tied to medical claims  Government is a large health insurer

Could health policy be responsible for volatile trend? Paper is available in the CAS E-Forum Future work on this problem  Convergence of systems over time  Figure out if public systems, systems with universal insurance are causing volatility How Disentangle public provision effect from universal coverage effect  Will trend in the U.S. get more volatile?