by JEFF GOLDSMITH (7)
My career as a “futurist” began in 1986, in response to a request from the Editor of the late Hospitals magazine to write an essay on the US Health System in 2036. You can find that essay here.) Some of the 33 year old forecasts included:
- The patients of the 21st century will be connected to their physicians or hospitals by webs of telemetry similar to those used in cellular communications; perhaps these communication webs will be coordinated or monitored by computer systems that could trigger responses in advance of crises.
- “Intelligent” clinical information systems will become the hospital’s operating core. . . These systems will monitor patient conditions on a real-time basis, tracking physiological signs and incorporating test results, comparing patient responses against profiles gleaned from vast clinical data bases, and assisting the patient care team in evaluating and planning care
Unfortunately, I also talked about “writeable laser disks” and forecast that “by the early 21st century, government financing may be a distant third as a source of U.S. health funds, behind (in order) individual patients and corporate employers.” You can’t win them all!
In this essay, I was following in the footsteps of corporate seers such as Alvin Tofler (Future Shock, 1972) and John Naisbitt (MegaTrends, 1982) who captivated managements and boards with bold and optimistic forecasts of a changing world. Their forecasts were bold but vague, leading some wags to suggest that the three keys to successful futurism were: be optimistic; never make specific numeric forecasts and never give a date by which your forecast is supposed to come true. I violated all three of these rules in my 1986 article.
“The Future Ain’t What it Used to Be”
In the ensuing 33 years, we’ve seen a ton of changes in US healthcare, but often not the ones we futurists forecast. The biggest change has been the relentless and unchecked rise in expense, causing fiscal indigestion for state and national governments and rendering care for tens of millions of Americans into a luxury good.
However, forecasting change in the health system has gotten harder, in part because major technologies expected to reshape healthcare have grossly disappointed both investors and advocates. (See my February Deductible post “The Disruption Distraction” for a discussion of the frustrating pause in healthcare technical innovation). After a lengthy post WWII run that brought us high tech imaging, ambulatory surgery, dialysis, high tech infusion therapy and a raft of useful drugs, from antibiotics to antidepressants to statins, health innovation entered a doldrums in the late 1990’s. Many promising transformative technologies failed to materialize as expected.
The two biggest gaps between promised transformation and actual impact have been clinical genetics and digital health. Both surfaced in the 1990’s and attracted waves of venture and private equity investment amid forecasts of rapid and transformative change. I began writing about the potential of these seemingly fertile areas more than two decades ago, but as of 2019, the promised transformation still seems a long way off.
Despite the plummeting cost of sequencing a person’s genome, personal genomics and gene therapy have yet to have a major impact on the care system. And you cannot say we were not warned by experts. Around the completion of the Human Genome Project (2002), the head of the Stowers Institute for Medical Research, Dr. William Neaves, was asked what stood between us and definitive solutions to genetically linked diseases like cancer. His answer: “About a hundred years of hard work!”.
This disappointment vs, expectations can be traced to the fact that lay analysts, though not the scientists themselves, grossly underestimated the complexity of genetically linked disease. The personalized gene assays popularized by Silicon Valley firms have been derided by scientists as “recreational genomics”, because of the dubious predictive value of the genetic markers they assayed. These firms seemed to have repositioned themselves as seekers of your ethnic roots; they helped validate Elizabeth Warren’s fractional claim to native American ancestry. They also helped solve a few baffling cold case murders through their sieve-like personal privacy protections.
Though it is possible that genetic therapy will be transformative in two more decades, it is extremely unlikely if the price tag for gene therapies escalates into seven figures . It will be an option for tech billionaires but few of us ordinary mortals.
And while the Internet has wreaked havoc in retailing, print media and politics, it has yet to have a discernible impact on the healthcare system. Internet-based virtual care systems for patient monitoring and physician visits and digital health tools like the electronic health record and online patient portals have, thus far at least, been major disappointments. We discussed the backlash against these tools here The same fate likely awaits AI and machine learning in healthcare.
While some digital pioneers such as Kaiser and Group Health (which merged with Kaiser in 2017) have built digital access into a major complement to their subscribers’ experience, it took twenty years to do so! Other health systems have struggled with the clunky, late-1990’s user interfaces and limited functionality of Epic’s ubiquitous MyChart.
Also disappointing have been: virtual communities of patients, online clinical trials and cell phone apps with health uses, which now number a laughable 325 thousand! Health systems executives attempting to harness healthcare apps to improve the customer experience have likened it to walking into a swarm of sand flies. Search tools have certainly democratized access to health information, and enabled patients to be better prepared. But they have also contributed to the flood of misinformation. It is not clear that the consumer’s “empowerment” through search and online communities has led to better results, or better health.
The problems in digital health were different, and less “technical” than those in clinical genetics and personalized medicine. They have been rooted in the continuing frustrating search for viable business models to sustain digital health innovation (e.g. generating a return on investment). It is worth recording that the handful of dominant businesses that control the Internet are themselves struggling to move beyond ever more invasive, predictive advertising placement as their dominant revenue source. Powerful firms like Google, Microsoft, Apple and Facebook have yet to crack the healthcare code, despite billions thrown at the healthcare “vertical”.
Digital health has been stymied by the difficulty in” automating” the relationship between patients and caregivers and the complex care process. Here too, the subtlety and variability of human disease and the depth and intensity of the doctor-patient relationship have been grossly underestimated by forecasters and investors alike. Healthcare is the most complex product in the US economy. Digital health’s problems have been compounded by HIPAA and by clumsy federal efforts to mandate the content and processes surrounding the electronic health record, which reached a zenith during the early Obama years.
Futurism and the Technology Hype Cycle
Healthcare technological progress is not immune to the “Hype Cycle” popularized by technology consultants at the Gartner Group. In a media-saturated world, technologies follow a predictable trajectory, from overhyped introduction to rapid attainment of the peak of inflated expectations to the humiliating plunge into the trough of disillusionment, from which only a few technologies emerge to climb the slope of enlightenment and become essential to us.
Futurists play a crucial role in the Hype Cycle, since as presumed experts on transformative technology, they lend velocity to a technology’s upslope progress. “Upslope futurists” also play a crucial role in the fund raising process, since they provide seemingly objective validation of the commercial merits of the innovation (e.g. the more “transformative”, the higher the valuation).
Futurists working the other side of the slope, however, are greeted with chilly silence, particularly if they weigh in toward the top of the hype cycle. “Downslope futurists” may observe that the innovation does not actually deliver the claimed benefits to users, and therefore does not justify the inflated valuations paid by early and mezzanine investors. Honest futurists can also draw attention to “business model” problems that will prevent innovations from turning into real businesses.
Such honest forecasts are troublesome to investors because inflated valuations are baked into the asset side of many venture and PE firm balance sheets, like foam at the top of a mug of artisanal IPA. Futurists who issue enough “this ain’t happening” forecasts will eventually notice the haunting sound of their phones not ringing! Gartner has actually helped us with this problem by periodically publishing their own version of the Hype cycle for healthcare technology.
In reality, only a fraction of innovations actually emerge from the Gartner slough of despond, and, for those that do become actual businesses, it can take a decade. The crucial element in the progression to the ” plateau of productivity” is the presence of strong feedback loops between customers/end users and the engineers and marketers. Why some technologies succeed and others fail to emerge from Gartner’s Trough is a compelling doctoral thesis project for students of technology.
A crucial element in this progression is realism on the part of management, and the willingness of Boards/investors to change out managements that remain intoxicated by their own brilliance, and fail to grasp the extent of re-engineering required. How many Steve Jobs-type managers can make that difficult transition from the Apple’s embarrassing Newton to the iPhone? (It took Jobs himself more than a decade.) This process requires capital, patience and determination, and almost takes longer than people expect.
The Future of Futurism
There is no natural law of technological progress that states that innovation in a given field comes in a nice steady stream. History suggests that technological progress comes in unexpected surges. More often, it comes in a less dramatic but steady accretion of small adjustments and changes. As we suggested in the Disruption Distraction essay cited earlier, there has been great progress in medicine in the past thirty years, just not of the iPhone variety. Most of the progress has been incremental and substantial, especially in surgical technique and anaesthesia.
The biggest unknown in forecasting technological change in any field is timing. That is why giving a date for one’s predictions is a true measure of a futurist’s courage. Accurate forecasting involves guessing, and that is the correct word to use, which technologies have wise enough managements and the patient financial backing needed to re-engineer based on user feedback.
The art form here is assessing the founders and engineers behind a technology, and their processing of market feedback. Progress up that slope of enlightenment is all about listening to the customer (Thank you, Peter Drucker!) and understanding how to deliver value to them. Successful futurism is, thus, neither an art nor a science, but rather, ultimately, an exercise in reading talent (founders and teams including investors) and its potential.
Five for ’40 (2040, that is).
And since I’ll never learn (and won’t be around for the inevitable embarrassments), here are some bold “upslope” forecasts for technologies I am watching with great interest.
By 2040, we will have:
Vaccines for Schizophrenia and possibly Autism
An Implantable Substantia Nigra for Parkinson’s Disease
A Dialysis Like Solution for Septic Infections
Remotely Piloted Drone Air Ambulances
Thought Guided Computing