Is your niche too narrow? Too wide? It doesn’t matter.

Academics care about being in a niche.  A person only has 24 hours a day and 7 days a week.  It’s practically impossible to be the world expert in everything.

Some days I worry that my interest in informatics is too narrow.  So tell me again, why wouldn’t anyone just hire either a dedicated radiologist or a dedicated informaticist?  What’s the point of you?

Some days I worry my niche is too broad. Because that’s basically all of radiology, you dimwit!  That inner voice in my head would scream.   How can you expect to understand all of what makes my profession tick, all the intricacies behind every segmentation algorithm, every big-data challenge, every line of code?  Give it up.

And then there are days when I spend 8 hours doing something I want to do, and the day feels 20 minutes long.  Days when I feel tired but satisfied, proud to have made those career choices.

These are the days when that voice doesn’t speak.

 

Measure Differently to Think Differently

Credit: Innovation by Boegh, licensed by Creative Commons

There are many forms of innovations.  Sometimes medical innovation is nanotechnology, molecular imaging, high-precision targeted therapy, or 3D-printed prosthetic, which are advancements whose adaptation rate are limited by the rate of research.  This is a good thing.

And then, there exists technology that has become commonplace in every other industry but is still considered “innovation” in medicine due to their glacial adaptation rates in hospitals and clinics.  Case in point: When was the last time you saw a pager that doesn’t belong to a healthcare provider?

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Before the End of the Day

Radiology Education

Credit: arztsamui from freedigitalphotos.net

 

“Before the end of the day,” a staff radiologist placed a gentle but firm hand placed on my shoulder a few months into my first year in residency, “we should talk about your report.”  I felt a dull tugging in my stomach, worried that something had gone seriously wrong – an incorrect diagnosis, a poorly phrased finding, an embarrassing lapse in voice recognition leaving out the “no” in front of “evidence of cancer.”  Maybe I was completely off-base, having seen a finding that did not exist and perhaps called it “highly suspicious.”  Maybe the ordering physician called my attending on her personal cell phone to complain.

Maybe it was the patient who called.

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Stop Using Tablets/Phones/Computers before You Go to Bed!

According to some smart Harvard people, anyway.

Because evolution never expected humans to develop ways to produce light, our bodies are wired to assume that nightfall is all dark.  A December 2014 study from PNAS states that the light from a back-lit computer screen degrades sleep hygiene from a hormonal level. 
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The Gorilla Detection Exercises at Dawn – A Theory of Radiology Nightfloat

As a rite of passage as well as part of the regular work schedules of a radiologist, a resident trainee must take on the role of independent interpretation for exams that come into the hospital at night.  I happen to work at a place where attending backup is readily available by phone, but an attending radiologist is not in-house at night.  This provides an abundance of learning opportunities.

After finishing one week of radiology night duties as one of two trainees, I’ve begun to think how the progression of the night always seem to follow some pattern, and what that means for a radiologist trainee on call.

Pareto-Efficient

First, it’s probably useful to introduce the concept of a pareto-efficient curve. The curve explains the relationship between two desirable but partially mutually exclusive qualities.  For example, a radiologist wants to be very fast at interpreting studies.  A radiologist also wants to provide very high quality interpretations.  Alas, we cannot do both at the maximal capacity.  One might imagine the relationship between the two to look like this:

pec1

Standard pareto-efficiency curve

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Do More or Better – But Usually Can’t Do Both

Today’s world provides us with tools that make humans more capable than ever. Writers who used to make elaborate trips to exotic locations to gleam material for the next espionage thriller while talking to their book agent on the landline with expensive long distance fees can now do the research at their computers while setting up an Amazon self-publishing account.  Radiologists who used to be at the mercy of transcriptionists to translate their verbal stutters into fluent medical poetry days later now generate reports within minutes using voice recognition technology.

These are empowering tools, putting the ability to affect outcome directly in the hand of those holding the highest stakes.  In general terms, it makes sense that with advancements in technology, professionals can now (1) do the same amount of work with better quality, or (2) do more work at the same quality.

Unfortunately,  inadvertently what happens is we tend to be expected to accomplish more and do better (occasionally one also expects to feel less tired at the end of it!) Business school professors would teach that technology advances push the entire pareto-efficient frontier forward.  That is, assuming that you are already working at your absolutely most efficient way such that any improvement in speed will automatically have a quality tradeoff, then adapting a new technology may change the nature of the curve such that you can now move both “up” and “to the right.”  The truth is, I am so rarely pareto-efficient in the first place that if a new technology can somehow land me onto my existing frontier, it was well worth the cost.  And while technology like this, this, and this don’t literally breaking any frontiers, they do have the added benefit of putting productivity in my conscious thought and – at least temporarily – make me healthier and more productive.

Back when Xerox invented the mouse

Xerox PARC, founded in the 1960s, was among the most cutting edge research group of its time.  On December 9, 1968, Douglas Englebart famously showcased a set of inventions that set the vision for the future of computing.  In a world when everything ran on a black and white screen with punch cards and command lines, he showcased live video conferencing, real-time document editing, and something called a graphical user interface.

In the center of all of this technology was a simple box-with-a-ball device that came to be known as the mouse, which then promptly spent the next 11 years in obscurity, discussed only by the geekiest pioneers in technology.  Continue reading

Sometimes it’s okay to turn the car around

Let’s say you decided to start a new project, one that requires significant investment of effort on your part and has an element of uncertainty.  This can be an academic project, a new start-up, or maybe you’ve decided to start a new year resolution.

A fair assumption may be that we wish to succeed in that project we’ve started.

If this project happens to be related to scientific research or entrepreneurship, then odds are not to our favor.  I’ve been told on several occasions that the failure rate of projects in either category is more than 90%.   This statistics forms the pillar of several success-related famous quotes, my personal favorite being one from Warren Buffett:

The difference between successful people and really successful people is that really successful people say no to almost everything.

What Mr. Buffett neglected to advise is how to pick out what is part of almost everything and what would be the occasional something where ‘yes’ is the right answer.

So sometimes, we end up committing to projects before we have enough information (or the guts to overcome the academic fear of missing out) to say ‘no.’  When I first began training, one of the most salient advice was that a trainee should “stick with your project and see it through.”  The most helpful mentors sometimes nudge their trainees along the path by asking “what’s the best next step?”

But what if the “best next step” is to stop “seeing it through?”

If starting a new research project is like driving down a long road with many forks but only one correct path, then the endpoint may be like getting to White Castle at the end of that road trip.  And that each of the forks leads to a cliff.

The problem is: when you’re at a fork in the road, all you see is the fork.  You don’t see White Castle, and you certainly don’t see the cliff.

While everyone wants to find a White Castle at the end of their sober, not otherwise herbaceously enhanced academic road trip, knowing the statistics that 9 out of 10 roads lead to a cliff naturally leads to a different approach:

If the best thing that can happen to a project is to succeed, then the second best thing that can happen is to know exactly when it was going nowhere.  Unfortunately, sometimes you just keep driving after making a turn, not knowing where the end of this fork leads.

The worst part is that the more you drive along a forked branch, the more committed you become to it, and the harder it is to stop and turn around.

I have been advised numerous times to define endpoints, visualize the White Castle at the end of the trip, smell its hamburgers, and at every step find the next best action to get there.   Although sound, maybe it is an incomplete advice.  What if the best thing to do is to turn around and start over?  How will I know when it’s time to move forward and when to stop?

Harvard Business School gives this approach a fancy name called Discover-Based Planning, one element of which involves an inverted income statement where entrepreneurs are encouraged to start by writing down a Net Income forecast  necessary for the nascent start-up to survive.  Then, assumptions are added one by one – if these are the bottom lines, then when must the next rounds of funding happen? What must our operating profit be?  How many widgets must we sell to achieve these numbers?

The first generation Amazon Kindle was designed with the instructions that the engineers can do whatever they want as long as the device has 3G connectivity, long battery life, easy to hold, and use ink-like screen, a stringent set of criteria set by the CEO Bezos as necessary for success, without which the project becomes no longer worth pursuing.

Mr. Buffett knows how to be very successful by saying no to almost everything.  But for those of us who don’t have the same acumen, we may fare better by creating internal checklists and establishing hard-stops that makes the next “no” easier to say to our hardest customers – ourselves.

Have we begun to think like our media?

Once upon a time, there was no social media.  There was no traditional media.  There wasn’t even writing (yes, we are going way back).

Information relied on stories, particularly stories with well-defined heroes and villains whose actions are followed through elaborate stories of their deeds, as events were far more memorable than simple lists of facts.  Anthropologists believed that information was passed down by song, a natural mnemonic that helped countless village elders remember these elaborate stories. Continue reading

3 Ways To Build Better To-Do Lists (3 of 3)

This is a continuation of a thread of posts (part 1, part 2).

3.  Put the whole project on a list and off your mind, or don’t use one at all.

Computers are simple creations.  Despite dramatic advances in artificial intelligence – and the ensuing debate on what constitutes “intelligence” – our multi-core, multi-gigahertz processing machines touting terabytes of storage can’t make a decision that it wasn’t programmed to do.  Continue reading