opinion the end of life is the point when costs are very high and potentially more controllable.

The second area she mentioned is based on her comparison of the United States and other countries. She questioned why the United States gets so little for what it spends. Looking at cross-national comparisons of health status and the associated costs, the United States spends more money and yet has poor health relative to other countries—worse obesity and worse hypertension at a lower age, for example. Part of the expenditure difference results from worse health, but the United States is also spending money that is not buying better health. She concluded that these two examples point to the need to directly study costs.

Darius Lakdawalla (University of Southern California) noted that when thinking about the problem of modeling, for a long time the view was that there would be only one model of the economy. But the experience of the 1970s departed radically from model forecasts and cast considerable doubt on the notion of a single, unified model that could explain all economic phenomena. Similarly, it is no longer thought that one model will unify everything one needs to know about the health care system. But it is important to push the frontiers of the modeling enterprise. Several such areas have surfaced already during the workshop, he observed.

Lakdawalla emphasized three specific areas that need to be pursued. First is to build models that push the frontier in modeling medical technology. Second is to build models that advance the frontier on pricing and in particular understanding all relevant prices, not just explicit prices in the system. Part of the problem in health care, from a modeling point of view, is that all of the relevant prices are not observed. There are many shadow prices that are extremely hard to measure when there is public involvement in the system. For example, when health insurance is publicly provided, it is hard to observe its true price to consumers. So how does one go about thinking through price responses in a mixed public–private system when, as Michael Chernew pointed out, prices are one of the most important brakes on health care spending growth and may be one of the mechanisms by which projections go from being ridiculous to being reasonable. So understanding how to build those mechanisms into the model is another first-order challenge. Third is dealing with uncertainty in a more plausible manner as decision makers are often rightfully skeptical of any given model because they think there are too many assumptions built in that are artificial.

It is hard to push all three frontiers at the same time. It is hard to build a model that, for example, includes a really sophisticated supply-side evolution of technology and sophisticated accounting for prices along with changes in aging and health and takes uncertainty seriously. That seems like a very daunting task and may be fundamentally impossible, but it certainly is possible to take different approaches and get at pieces of the problem.



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