Othman Laraki, Cofounder and CEO of Color, discusses how technology won't save healthcare, but it will redefine it paid intel
hen companies first try to explore the potential of new technology, they tend to think within current frameworks, but often miss its deep implications. Echoing theattributed to Henry Ford—“If I had asked people what they wanted, they would have said faster horses”—we start using new technology to improve what we already do before realizing that we should question what we do in the first place.
As it has done in other industries, technology will remake the definition of healthcare itself. At the center of this transformation is data and how we harness uncertainty through machine learning. It will progress non-linearly, rapidly quickening after a painfully long buildup. And most importantly, this transformation won’t fix what is broken about our current system—it will redefine the system itself.
"Once a technology is assimilated into culture and people almost forget its presence, the real value of the technology can emerge."This principle applies to healthcare. The introduction of big technological building blocks into healthcare is still early, which is why we think of many of these in a first-order way.
Similarly, the emergency room will soon morph into something very different. Rather than waiting for symptomatic escalation, many medical events will be detected and intercepted upstream. For example, we know that rapid weight gain in certain populations precedes heart failure. But instead of a heart attack bringing you to the ER, tomorrow’s ER should come to you before it happens. You’ll just expect that from new emergency services powered by AI, wearables, IoT, and tons of streaming data.
"In healthcare, we treat doctors a bit like old rotary phones. They remain the core building blocks of health delivery, but haven’t been given an opportunity to redefine their functionality through technology."Scores of health practices are designed around managing these scarcities—a physician’s time and her tools, such as MRI machines; and her limitations, such as how much data the human brain can process.
These are just two examples of what will soon be a long list of functions doctors can offload to technology over the coming years, and in doing so, dramatically scale the powerful insights medicine has accumulated over the years.The value of data is driven by utility, not scarcity. But EHRs were conceived in a world that predated the current generation of digital technologies, which I believe will completely change where the “critical mass” of health data resides in the first place. Today, for most consumers, unless they are in treatment for a disease, there is far more health information outside the health system than inside it.
In a pre-digital environment, the two sides of a marketplace are subject to physical constraints—atoms instead of bits. In a digital one, pools of supply and demand can be connected virtually. Advertisers once needed to purchase billboards to help generate demand for a product, but billboards offered little visibility into how they actually drove purchases.
This is no longer a valid assumption, given we can use machine learning to effectively stratify risks for diseases such as breast cancer through a combination of genetics , physical attributes , and behavior . Up to now, most of these risk factors were considered sporadically and in isolation, but can now be combined into a more uniform view of risk.
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