Efficiency in the health care industries: a view from the outside.

THE HEALTH SCIENCE/HEALTH CARE INDUSTRY AND THE microchip industry are similar in some important ways: both are populated by extremely dedicated and well-trained individuals, both are based on science, and both are striving to put to use the result of this science. But there is a major difference between them, with a wide disparity in the efficiency with which results are developed and then turned into widely available products and services. To be sure, there are additional fundamental differences between the 2 industries. One industry deals with the welldefined world of silicon, the other with living human beings. Humans are incredibly complex biological systems, and working with them has to be subject to safety, legal, and ethical concerns. Nevertheless, it is helpful to mine this comparison for every measure of learning that can be found. First, there are important differences between health care and microchip industries in terms of research efficiency. This year marks the 40th anniversary of a construct widely known as Moore’s Law, which predicts that the number of transistors that can be practically included on a microchip doubles every year. This law has been a guiding metric of the rate of technology development. According to this metric, the microchip industry has reached a state in which microchips containing many millions of transistors are shipped to the worldwide electronics industry in quantities that are measured in the billions per month. By contrast, a Fortune magazine article suggested that the rate of progress in the “war on cancer” during the same 40 years was slow. The dominant cause for this discrepancy appears to lie in the disparate rates of knowledge turns between the 2 industries. Knowledge turns are indicators of the time it takes for an experiment to proceed from hypothesis to results and then lead to a new hypothesis and a new result. The importance of rapid knowledge turns is widely recognized in the microchip industry. Techniques for early evaluation are designed and implemented throughout the development process. For example, simple electronic structures, called test chips, are incorporated alongside every complex experiment. The test chips are monitored as an experiment progresses. If they show negative results, the experiment is stopped, the information is recorded, and a new experiment is started. This concept is also well known in the health sciences. It is embodied in the practice of futility studies, which are designed to eliminate drugs without promise. A recent example of the use of futility studies for this purpose is the exercise of narrowing the list of putative neuroprotective agents before launching a major randomized clinical trial. The difference is this: whereas the surrogate “end point” in the case of microchip development—the test chip failure—is well defined, its equivalent in the health sciences is usually not. Most clinical trials fall back on an end point that compares the extent by which a new drug or therapy extends life as compared with the current standard treatment. Reaching this end point usually takes a long time; thus, knowledge turns are slow. In many instances, a scientist’s career can continue only through 2 or 3 such turns. The result is wide-scale experimentation with animal models of dubious relevance, whose merit principally lies in their short lifespan. If reliable biomarkers existed that track the progression of disease, their impact on knowledge turns and consequently on the speed of development of treatments and drugs could be dramatic. Even though such biomarkers could have a profound effect on medical research efficiency, biomarker development efforts seem far too low. Although precise numbers are difficult to come by, in my estimation, in the microchip industry, research into development, test, and evaluation methods represents about 10% of total research and development budgets. This 10% is taken off the top, resulting in less actual product development than the engineers, marketers, or business managers would like. But an understanding that this approach will lead to more rapid knowledge turns protects this allocation from the insatiable appetite of the business. The National Institutes of Health (NIH) budget is about $28 billion a year. It seems unlikely that anywhere near 10%—$2.8 billion—is spent on biomarker development.