nonmedical factors—such things as diet, exercise, and environment—on people’s health continues to grow.

For all these advances, a gaping hole in information still exists. Relative to knowledge about health care expenditure and medical science, much less is known about the return that individuals, and society in general, receive for the investment in health. Given the massive amount of resources that are spent publicly and privately, it is astonishing that so little effort has been made to systematically assess what we are buying for this investment.

At the heart of this information chasm is the need for data on how inputs into medical care translate into outputs—completed treatments and procedures—that, in combination with other factors, ultimately affect the population’s health. While some studies have suggested that productivity growth in medical care is reasonable in aggregate (Cutler and McClellan, 2001; Cutler, Rosen, and Vijan, 2006), others argue that there is substantial waste at the margin (Fisher et al., 2003; Skinner, Staiger, and Fisher, 2006). In this report, we provide guidance about what data are needed to measure the outputs produced by the medical care sector. Without this kind of information, it is impossible to credibly assess whether the nation spends too much or too little on medical care relative to, say, public health measures, and, perhaps more importantly, whether we purchase something close to the right mix of medical care goods and services for a given level of resources expended. In order for policy makers to pursue actions that reduce costs sensibly, improve performance, and, in general, enhance the efficiency of the national approach to health and medical care, a more systematic approach to compiling data for the purpose of tracking productivity in the sector is needed.

The National Income and Product Accounts (NIPAs) produced by the Bureau of Economic Analysis (BEA) and the National Health Expenditure Accounts (NHEAs) produced by the Centers for Medicare & Medicaid Services (CMS) are the foundational components of the U.S. health care data infrastructure. While the virtues and utility of these data sources are well known, they are not sufficient on their own to inform policy. The national accounts have particular difficulty decomposing medical spending increases into price, quantity, and quality change elements. For example, an increase (or decrease) in the observed price of treating a disease may reflect a change in the price of unchanged treatment inputs, a change in the amount of inputs (e.g., a surgeon’s time) required, the development and use of new drugs or procedures that alter outcomes, or simultaneous changes in more than one of these factors (National Research Council, 2005, pp. 117-118).

In this report, we offer guidance for extending these important data sources, at first in an experimental or satellite account setting, to better inform national decisions about resource allocations to health care. A health data system built on

respond by prescribing statins to as many as 7 million more patients—at a cost of about $9.7 billion annually (Light, 2008).

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