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Each disruption is composed of three enabling building blocks: a technology, a business model, and a disruptive value network. While Chapter 1 deals with business models, this chapter focuses on the technological enablers that form the backbone of disruptive business models. These technological or methodological enablers allow the basic problems in an industry to be addressed on smaller scale, with lower costs, and with less human skill than historically was needed. These technologies sometimes come from years of work in corporate research and development (R&D) labs. Others are licensed or bought, and, on occasion, technology can be repurposed from an entirely different industry.

The health-care industry is awash with new technologies—but the inherent nature of most is to sustain the current way of practicing medicine. However, the technologies that enable precise diagnosis and, subsequently, predictably effective therapy are those that have the potential to transform health care through disruption. We begin this chapter with a general review of what makes a technology disruptive and how that technology converts complex intuition into rules-based tasks. We then introduce a three-stage framework for characterizing the state of technology in the treatment of various diseases. This framework asserts that the treatment of most diseases initially is in the realm of experimentation based on intuition. Care then transitions into the realm of probabilistic or empirical medicine; and ultimately it becomes rules-based precision medicine. After explaining this framework, we then review the history of infectious diseases to show how technological enablers based on precise diagnosis caused care to pass through these stages. Moving to the present, we show how similar transitions are now afoot in the care of diabetes, breast cancer, and AIDS. Next, we redefine the concept of personalized medicine and show how information technology is enabling facilitated networks to deliver true personalization. Finally, we sketch out a preliminary map of the state of knowledge of a range of diseases, allowing us to project what technological breakthroughs will enable the further disruption of today's health-care business models.1


There is a clear pattern in the long and arduous process by which an industry eventually transforms the body of knowledge upon which it is built from an art into a science. In the earliest stages of most industries, the extent of understanding is little more than an assortment of observations collected over many generations. With so many unknowns, the work to be done is complex and intuitive, and the outcomes are relatively unpredictable. Only skilled experts are able to cobble together adequate solutions, and their work proceeds through intuitive trial-and-error experimentation. This type of problem-solving process can be costly and time-consuming, but there is little alternative when the state of knowledge is still in its infancy.

Over time, however, patterns emerge from these intuitive experiments. Defining these patterns that correlate actions with the outcomes of interest makes it much ...

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