Greg Freiherr has reported on developments in radiology since 1983. He runs the consulting service, The Freiherr Group.
The Changing Future of Innovation
Innovation is all around, especially at trade shows. It’s been that way for as long as I can remember. What’s different today is that the type of innovation has changed. This change is especially evident in information technology, where artificial intelligence (AI) and cloud computing are driving markets.
The use of AI to interpret radiological images was emphasized at the annual meeting of the Healthcare Information and Management Systems Society (HIMSS) in Orlando. The presence of AI was obvious in the Innovation Live Pavillion, just as its presence was palpable on the exhibit floor. Ditto for cloud computing, which like AI, rated its own forum at the HIMSS meeting.
Innovation Teems At HIMSS
Trade shows are rife with innovation. That was the case at HIMSS 2019, as it was at RSNA 2018, where vendors showed products and works-in-progress for every marketable form of imaging modality and information technology. I am certain we’ll see other such offerings as the year progresses, each tailored to specific medical disciplines and applications, at annual meetings for the American College of Cardiology (ACC) in March; Society of Breast Imaging (SBI) in April; Society for Imaging Informatics in Medicine (SIIM) in May; and American Society for Radiation Oncology (ASTRO) in September.
Driving the need to innovate is the newfound patient centrism of value-based medicine, which is creating demands that medicine is finding hard to fulfill. Underlying it all — masquerading, if you will, as technological insight — is fear … fear of not meeting patient expectations.
In this rapidly evolving world of innovation, radical thinking is turning moment-by-moment into conventional thought. It is fertile ground for the seeds of AI and cloud computing to take root; where both promise economic and clinical advances. But AI and cloud computing are just examples of the new kind of innovation.
Vendors are focusing on the ends that their products provide rather than the means by which they are obtained. CT vendors, for example, years ago stopped focusing on the number of slices their scanners produce in a single rotation; how fast the “gantries” — actually the electronic guts within — scan a patient; or even how fast a scan is performed (unless, of course, the CT is targeting the emergency department). Now vendors are focusing on clinical or operational benefits for patients or users. In short, the means are blending into the background.
This is why the adoption and use of AI and cloud computing are happening out of sight and out of mind from patients — and providers — who care mostly about results. It is why AI and cloud computing are being adopted and will continue to be adopted in the foreseeable future — and not because they are the latest or most advanced technologies.
This is a decidedly good thing. It is how it must be if the price of healthcare is to be checked (or go down) at the same time quality goes up. These two are different sides of the patient centrism coin. And both — clinical and operational improvements — must be achieved if value-based medicine is to really catch on.
Technological transparency is the “go-to” characteristic as the world becomes more and more dependent on the results of technology. In this world, AI and cloud computing are the “doers” that will allow providers to reach what were previously unattainable goals.
Why Profits Matter
Choices determine not only what we do but who we are. And equipment vendors have made choices on the basis of what providers want. Typically those choices have reflected what could be measured with absolute certainty. More CT slices, for example, might be obtained per rotation from successive generations of systems. This metric was handy only until it was obvious that the number of slices made no radiological sense. Similarly vendors pointed to scan speed, often measured in tenths of a second, a speed that weirdly had little or no significance in terms of reduced patient wait time or backlog.
Departments that purchased these systems based their decisions on metrics that have since become either obsolete or are rapidly doing so. This has or is happening thanks to a fundamental change among healthcare providers. Simply put, the profit motive is taking hold.
Profits have long been important to equipment vendors. And for good reason. Generating more revenue than expenses has been essential for companies to grow or — even more basically — stay in business. But this reality of the business world had largely eluded healthcare providers if they purchased new equipment releases that achieved only iterative improvement, particularly when the improvement had no calculable impact on either their bottom lines or patients.
The slice wars in CT — where quad-slice scanners gave way to 16-, then 64- and 128-slice models (with stepping-stone releases of systems capable of generating, for example, 8 and 32 slices) — exemplify this. The war stopped only after it was obvious that the majority of patients would not benefit — when 64-slice scanners delivered as many slices per rotation as radiologists could reasonably use.
In that vein, profits, it seemed, were once widely viewed as antithetical to healthcare. They were the oil; patient care was the water. Totally incompatible. But the realization has begun to set in that volunteers who wheel patients out of hospitals and fund-raisers that help pay for equipment can go only so far. Neither is sustainable. Smart management is.
Economics — the common denominator of business success — is becoming a part of healthcare. And it is being made so by value-based medicine — and value-based imaging.
How Value-based Imaging Is Powering AI, Cloud Computing
The innovation that is part of this value equation is radically different from what was defined as being innovative in the past. Technology is no longer king but rather king maker. It goes unseen both in what it does clinically to benefit the patient’s health and operationally to shore up the provider’s bottom line. Whereas technology was once held up by providers as one — and sometimes the key — differentiator, AI and cloud computing, for example, tend to be transparent. They in themselves are not the point. Their results are.
AI and cloud computing are the catalysts. They make value-based change possible. And it is why AI and cloud computing are — and will continue — taking hold.
Rather than being iterative, innovation now has a loftier purpose. It is focused on making healthcare higher quality and less expensive — and they promise in some circumstances to do both at the same time. Value-based imaging requires that diagnosis be not only precise but that patient wait times are shorter; care must be rendered efficiently to multiple interested parties, as well as the patient. And the most successful applications are ones that not only do these but also make a difference in the clinical management of the patient.
This is heady stuff. But not so much that they are beyond the reach of today’s innovation. And that is the beauty of what we have now. It’s a lot different than how it used to be.