Hammers and healthcare: technology’s role in modern medicine

Growing up with a handyman father, I learned everything from basic carpentry to how to winterize an engine. Using his cadre of tools to help build a garage or spray fogging oil into the outboard engine on our small boat or through countless other practical chores, I was surrounded by tools and constantly engaged in learning their uses. 

This education sparked a desire to work on complex tasks with my hands and ultimately led me to become an internist (acquiring new skills that gradually replaced the handyman talents of my youth…much to my wife’s dismay). Though I can no longer properly service my own car, my childhood experience remains with me; particularly as I contemplate the current environment surrounding care providers and our era of rapidly advancing technology. 

New tools for complex tasks have taken on mythic status these days. In December, the beverage purveyors known as the Long Island Iced Tea company changed their name to Long Blockchain, and the company’s stock shot up 289%. Thankfully, smarter market minds prevailed, but the hysteria over words like blockchain, artificial intelligence (AI), or machine learning is real. I have observed numerous companies, particularly in the health arena, expounding on their use of AI or machine learning as if that “automagically” gives them value. The fact is that these technologies are not panaceas. They are simply tools-no different in their essence than my father’s screwdriver or pipe wrench. Understanding the usage and implementation is a complex and ongoing challenge that brings with it compelling future set of opportunities.

Tools are implements, not solutions. They are insufficient to the task of medical practice on their own. Sure, algorithms can be run independently to diagnose dermatologic issues, perform retinal scans, or serve as imaging readers. But none of that alone solves for the all of healthcare. Tools and technology require a tinkerer, a craftsman, an implementor. The true benefit from new technology will come when we understand how to produce and wield the best of these tools for the broader job of delivering care that is advanced, technical, and human at the same time. I believe that this will happen in medicine, but we still have a long way to go.

Defining productivity

The productivity gap in healthcare is no secret, and future technological development should be geared toward shrinking it. Great businesses, significant profits, and new drug and device technology have transformed the industry: Yet we still spend too much and produce too little. Some of this is due to the inherent nature of a complex service-there’s a “human” component and information asymmetry in delivery. The lines are blurred in living a life, managing health, and combating disease-each influences the others in a dynamic continuum. And in medicine, while the introduction of new tools seems more often to lead to a decline in caregiver productivity, it can still produce superior outcomes downstream, thus increasing overall societal productivity. 

To wit, before the invention of the stethoscope (celebrating 200 years of existence this year), a physician would visit a patient, take an oral history, listen to the story and consider the symptoms, then give a diagnosis. In aggregate, individuals touched the system with far less frequency and volume. With the advent of the stethoscope, physicians found the new ability to listen to the body as well as the story. The stethoscope in its elegant yet primitive nature as a tool, was a watershed innovation that expanded the medical profession’s understanding of human health, ultimately extending lives and increasing overall societal productivity. This new focus on the collection of objective data to accompany the historically subjective data gathering fueled imagination and innovation. Yet using this transformational tool often leads to additional time, additional spend, and additional personnel-often with the effect of worsening the productivity gap. 

A more modern example is angiography. Prior to its introduction, heart attacks were largely managed with medications, bypass surgery, or no intervention at all. Angiography costs a lot, takes more time to deliver than medications, and expands the population of survivors who may still have other medical requirements. Prevalence of vascular conditions did not change at baseline from basic societal and demographic trends, but angiography increased our ability to employ high-cost interventions that allow people to live longer. No doubt this innovation’s total impact requires consideration in a larger, much more positive context, yet angiography, as a tool, also drove up resource usage, provider training needs, future procedures, and hospital stays.

These examples suggest a paradigm where new tools often, at least historically, produce an immediate decline in productivity as measured by the technical definition (rate of output by unit input). Both inventions increased the time and cost of treatment for a given patient. But they also advanced medical practice, significantly improved health outcomes and lengthened life expectancy. Healthy patients are more productive at work and spend less time in hospitals, thus increasing societal productivity. 

Perhaps the ecological definition of productivity is more apt for healthcare application. I recently learned from a friend running his family’s farm in Michigan that the productivity of the soil is defined by what it is able to produce down to the row and the plant. Water, weather, fertilizer, sprays, and even wind affect soil productivity in this environment-but it’s the outcome that is measured. Such a productivity framework for medicine might hold that health is the “soil” supporting both individuals and the GDP of a country. 

Tooling our tools

Tools in medicine are no different than tools invented for other purposes - utility is often impossible to fully understand at inception. It’s not until you put it in the user’s hands that applications arise, and full potential is realized much farther down the road. The societal impact of tools like stethoscopes and angiography shows that any equation for productivity in healthcare must account for the balance of what happens to overall productivity in an economy as a result of an advancement. 

That tools often drive up the rate of output by unit input has been observed previously across all industries. In fact, a 1985 Harvard Business Review article noted: 

“For all the dollars spent by American companies on [research and development], there often remains a persistent and troubling gap between the inherent value of the technology they develop and their ability to put it to work effectively. At a time of fierce global competition, the distance between technical promise and genuine achievement is a matter of especially grave concern.”

I would argue that it’s even harder to understand the bridges between technical achievement and genuine achievement in the complex space of health. But tools that transform, modify, enhance, and improve the overall ability of a society to take care of its population should continue to develop and improve. AI, machine learning, and blockchain are the new tools of our day that will transform the future of the profession and ultimately enhance our “soil productivity,” just as the health inventions of yesteryear.

It is also true that any new tool, especially in a complex space like healthcare, requires operators who understand how best to use it. Physicians and caregivers are elemental: letting tools drive the entire story depletes the nutrients in our healthcare soil. The care providers, and individuals, must recognize the work that comes with learning how to best utilize the implements we have at our disposal. The lessons I learned growing up are as relevant as ever. You can have a hammer, nails, and a blueprint. But without a competent executor of those tools, your house has little chance of standing. 

Jack Stockert, MD, is a an internal medicine physician and a managing director at Health2047, a Silicon Valley-based business formation and commercialization enterprise developing solutions that address data liquidity, chronic care, radical productivity, and value-based payments.