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What does the Concorde Tell Us About Healthcare Technology in the 21st Century?

• 8

By JOE FLOWER

I am spending this month in the English Midlands in Stratford-on-Avon hard by the canal, the Bard’s town of quaint half-timbered Tudor pubs with “established 1482” on the plaques, and I am thinking about medical technology. I am here with Jenni to support her older brother as he goes through open-heart surgery and recovery. We have spent hours watching the ICU monitors.

The other night I watched a BBC documentary about the development of the Concorde, the supersonic aircraft. Beautiful plane, impressive technology for the time. Ridiculously expensive. Ultimately abandoned as not easily profitable and of limited use for a limited market.

The designers of the plane were quite proud of it, even as old men talking to the documentary cameras. They well should be, as it was a formidable technological achievement. One of the pilots talked about how many passengers would leave London at 10:30 am, arrive in New York at 9:30 am, conduct a day’s business, then ride the Concorde back to London in the evening, at $8,000 for round trip.

Here is the shocking take-away from the documentary. When they had finished the plane and were shopping it around, a number of countries complained about the noise, the sonic booms it would generate over every inch of its flight path. Eventually they sold zero planes, and the only airlines that put the Concorde into regular service were Air France and British Airways, the national carriers of the two countries that built it. That is not what is shocking. This is what is shocking: This was a surprise to them. The promoters and designers had apparently never considered that people might object to the noise. Never even thought about it.

Nor, it turns out, had they ever fully considered the cost/benefit ratio: Even at very high ticket prices, even at relatively full utilization, even when British Airways was given the planes for £1 each by the British government without having to shoulder any of the vast and deep more-than-decade-long development costs, the Concorde was hard to make a profit from. The crash of a Concorde in Paris in 2000, then 9/11 with its prolonged drop in air travel, spelled the beginning of the end. By 2003 both airlines had withdrawn the entire fleet from service and given up on the beautiful but flawed Concorde.

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Secure your seat for live demos on precision medicine delivery at next week’s Tech Summit

Imagine if you will, a future in which a cancer diagnosis will be treated with a lifestyle change, like a chronic condition. Survivable. Manageable. Like Diabetes. Sure, to receive a cancer diagnosis today does not mean what it meant twenty years ago, but we are also unlikely to reach a point of ever acting casual about the term or the treatment plan.

In the meantime though, the increasing prevalence of personal data collection is driving new approaches in care plans that have a real shot at improving quality of life. The narrative of one’s life can be seen in the data – everything from where you live, what you eat, how you workout, even what you search for on the internet. The sources of such personal data come from places like clinical trials, biosensors, and wearables and is being stored in your Electronic Medical Record.

The sticking point though is the advancement of technological tools to view, aggregate, extract, and analyze relevant data to derive a meaningful plan of attack (er, treatment plan). One interoperable tool that plugs right into the EMR is Cota Healthcare. Pair this with omics data and genome sequencing technology, like 2bPrecise, and physicians are gaining insight into what makes you, you. And thus are better able to customize a bespoke cancer treatment plan, designed for you and only you.

Learn more about how omics data is driving new care plans, and see a live demo from Cota Healthcare andothers at the Technology for Precision Health Summit next week in San Francisco.

Five Radiology Artificial Intelligence Companies That Somebody Should Build and Invest In

• 3

By HUGH HARVEY

I’ve previously written comprehensively on where to invest in Radiology AI, and how to beat the hype curve precipice the field is entering. For those that haven’t read my previous blog, my one line summary is essentially this:

“Choose companies with a narrow focus on clinically valid use cases with large data sets, who are engaged with regulations and haven’t over-hyped themselves …”

The problem is… hardly any investment opportunities in Radiology AI like this actually exist, especially in the UK. I thought it’s about time I wrote down my ideas for what I’d actually build (if I had the funding), or what companies I would advise VC’s to invest in (if they existed).

Surprisingly, none of the companies actually interpret medical images – I’ll explain why at the end!

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Orbiting ORBITA

• 8

By ANISH KOKA, MD

I’m sitting amidst a number of cardiologists to go over the most recent trials presented at the interventional cardiology conference in Denver.  The cardiology fellow presenting goes quickly through the hors de oeuvres until finally getting to the main course – ORBITA.

ORBITA sought to test the very foundations interventional cardiology was built on – the simple idea that opening a stenosed coronary artery was good for patients.  The trial was a double blind randomized control trial of patients with tightly stenosed arteries who either had a stent placed or had a sham procedure.  Before the results are presented, the lay media headlines from cardiobrief, the New York Times, and the Atlantic are presented to guffaws from the audience.  The indignant smirks are audible as the accompanying editorial remarks from Rita Redberg and David Brown are displayed :

”The results of ORBITA show unequivocally that there are no benefits for PCI compared with medical therapy for stable angina, even when angina is refractory to medical therapy.”

The trial results follow – no statistically significant difference in the primary outcome of exercise time increment between sham and stent, and no difference in angina between the two groups.  The meat of the presentation involves the limitations of the trial that make the trial inapplicable – 200 patients total, 6 week follow up, the underlying heterogeneity of the patient angiograms that were randomized, and the wide confidence intervals of the primary outcome that swallowed the actual effect size.  Two different angiograms were shown to the audience from the ORBITA appendix.

The images demonstrate two ‘blockages’.  To the eye, at least, one appears tighter than the other.  The audience was polled on each image – everyone voted to stent the tighter blockage and medically manage the lesser of the blockages.  It could be all perception but I could feel the relief in the room as ORBITA was being made irrelevant.  The implication clearly was that some angiograms used to show the lack of benefit from stents would not have needed stenting in the first place.

There was no real challenge to the presenter save for one:

“One of the authors – Rita Redberg – is very sharp – why do you think she wrote that editorial?”

There was no good answer – the presenter shrugged and muttered something about an anti-interventional cardiology bias.

It was at that moment that I realized why cardiologists were having such trouble with  ORBITA – we were arguing like puritans.   Everyone in the room already ‘knew’ stents worked.  This was an exercise in bias confirmation when what was needed was an examination of the source of bias.  Faced with the ultimate epistemological challenge we were resorting to authority to dismiss findings we didn’t like.  Now I think cardiologists have authority with good reason, and certainly ORBITA may have limitations inherent in any small randomized control trial that’s performed, but we can do a better job answering the fundamental question raised here that relates to the primary evidence opening a narrowed artery actually can relieve angina.

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Could Artificial Intelligence Destroy Radiology by Litigation Claims?

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By HUGH HARVEY, MD

We’ve all heard the big philosophical arguments and debate between rockstar entrepreneurs and genius academics – but have we stopped to think exactly how the AI revolution will play out on our own turf?

At RSNA this year I posed the same question to everyone I spoke to: What if radiology AI gets into the wrong hands? Judging by the way the crowds voted with their feet by packing out every lecture on AI, radiologists would certainly seem to be very aware of the looming seismic shift in the profession – but I wanted to know if anyone was considering the potential side effects, the unintended consequences of unleashing such a disruptive technology into the clinical realm?

While I’m very excited about the prospect and potential of algorithmic augmentation in radiological practice, I’m also a little nervous about more malevolent parties using it for predatory financial gains.

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The Evolution of Precision Health

HEALTH 2.o WIDGET

Health 2.0 sat down with Linda Molnar to discuss the evolution of Precision Health, the imperatives at stake in a fast-paced field, and empowerment through big data. Linda has over 20 years in the field of Life Sciences and is responsible for a number of initiatives that further the field with start-ups, the feds, and for investors.

Her current endeavor is leading the upcoming Technology for Precision Health Summit in San Francisco alongside Health 2.0. “We’re never going to pull together all of this disparate data from disparate sources in a meaningful (i.e. clinically actionable) way, unless we talk about it” she says. “The Summit is an attempt to bring together the worlds of Precision Medicine and Digital Healthcare to realize the full potential of a predictive and proactive approach to maintaining health”.

Check out the full interview here.
As a bonus, save 25% off the standard admission to the Technology for Precision Health Summit by using discount code TPH25. Register here!

How the Republican Tax Cuts Will Impact the Health Care System

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By STEVEN FINDLAY

The U.S. tax system and health care are deeply intertwined. The Republican tax bills hurtling through Congress would make significant changes in this relationship.

The proposed changes, primarily a large cut in the corporate tax rate from 35 to 20 percent, would benefit health care (and most other) companies.

But none of the changes would, in the long run, benefit consumers, the public good, or public health. The major components of the proposed legislation are dangerously ill-conceived and ill-timed in the context of the overall economy and in particular health care policy and spending, which is projected to comprise 20 percent of the nation’s economy in 2025, up from 18.3 percent today.

That’s a difference and increase that reflects several trillion dollars of “additional” health care spending over the next decade. Amid this projected rise, the Trump administration and congressional Republicans propose to reduce the rate of growth of overall federal government spending and shift a sizable portion of health spending to other government entities and programs. These include the Pentagon, national security, homeland security, infrastructure projects, and—most notable in the context of the tax bills—a tax cut for corporations and upper income Americans.

It doesn’t and won’t add up—unless two (unlikely) things happen: (1) the economy grows at twice to three times the rate most economists predict and (2) the rate of growth in health spending is dramatically constrained.

Absent both, the Republican tax bills will cause the annual federal budget deficit and the nation’s long-term debt to balloon even more than already forecast.

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On THCB

By THE EDITORS

Valuing Value-Based Payment
By ANISH KOKA, MD

Why “Precision Health” May Not Be the Precise Word

• 1

By DAVID SHAYWITZ, MD

The appeal of precision medicine is the promise that we can understand disease with greater specificity and fashion treatments that are more individualized and more effective.

A core tenet (or “central dogma,” as I wrote in 2015) of precision medicine is the idea that large disease categories – like type 2 diabetes – actually consist of multiple discernable subtypes, each with its own distinct characteristics and genetic drivers. As genetic and phenotypic research advances, the argument goes, diseases like “type 2 diabetes” will go the way of quaint descriptive diagnoses like “dropsy” (edema) and be replaced by more precisely defined subgroups, each ideally associated with a distinct therapy developed for that population.

In 2015, this represented an intuitively appealing idea in search of robust supporting data (at least outside oncology).

In 2017, this represents an intuitively appealing idea in search of robust supporting data (at least outside oncology).

The gap between theory and data has troubled many researchers, and earlier this year, a pair of cardiologists from the Massachusetts General Hospital (MGH) and the Broad Institute, Sek Kathiresan and Amit V. Khera, wrote an important – and I’d suggest underappreciated – commentary in the journal Circulation that examined this very disconnect, through the lens of coronary artery disease (CAD).

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Practicing Medicine While Black
(Part II)

• 3

By KIP SULLIVAN

Managed care advocates see quality problems everywhere and resource shortages nowhere. If the Leapfrog Group, the Medicare Payment Advisory Commission, or some other managed care advocate were in charge of explaining why a high school football team lost to the New England Patriots, their explanation would be “poor quality.”

If a man armed with a knife lost a fight to a man with a gun, ditto: “Poor quality.” And their solution would be more measurement of the “quality,” followed by punishment of the losers for getting low grades on the “quality” report card and rewards for the winners. The obvious problem – a mismatch in resources – and the damage done to the losers by punishing them would be studiously ignored.

This widespread, willful blindness to the role that resource disparities play in creating ethnic and income disparities and other problems, and the concomitant widespread belief that all defects in the US health care system are due to insufficient “quality,” is difficult to explain. I will attempt to lay out the rudiments of an explanation in this essay.

In my first article in this two-part series, I presented evidence demonstrating that “pay-for-performance” (P4P) and “value-base purchasing” (VBP) (rewarding and punishing providers based on crude measures of cost and quality) punish providers who treat a disproportionate share of the poor and the sick.

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