ICD-10: The epidemiologist, the observer and the vanishingly rare

I first heard about the ICD-10 when I was working at a small start-up, trying to develop an EMR for a string of dialysis clinics. It was always spoken of with a certain gravity, like the ominous visit from an aunt that nobody in the family likes, but feels obligated to see.  Practical (read: business) people hate ICD-10. It’s giant and unwieldy. Doctors think it’ll be an excuse to bilk them out of payments.  They dread the day that they get a “false coding” note for a visit for a broken arm because they didn’t specify the patient fell off their bicycle or down a flight of stairs.  So who’s driving this?

I can only assume that it’s research.  ICD-10 must be an epidemiologist’s dream. Want to prove something inane, like the fact that waterskiing accidents are more common in the summer?  ICD-10 is your tool.  If you can collate all the insurance billing from the entire country, you can begin to pull out these vanishingly rare instances and analyze them.  Admittedly, as this article points out, some of the events the ICD-10 tries to capture are so vanishingly rare that they actually, well, vanish.  They’re literally unheard of or actually impossible. But what about some of the other widely panned codes, like falling off a chicken coop?  Theoretically, we could begin to perform real time monitoring of safety conditions in all kind of industries.  These events are rare, which means that if we see a cluster of them occurring in a particular geographic area, an investigation might be warranted. Maybe building inspectors aren’t performing their inspections. Maybe a certain company isn’t enforcing proper safety standards. Again, theoretically, the giant index of ICD-10 codes could drive meaningful data collect and interventions.

The problem is the observer. Inter-observer variability is a problem in all sorts of medical fields, from reading chest x-rays to interpreting physical exam findings. For the ICD-10 to be useful for research, you need to code these rare events correctly.  And, with the endless array of options, the chances of this happening seem, to me, to be vanishingly small.  Maybe there’s a good technical solution to this, where an EMR scans the HPI and offers a variety of appropriate billing codes (writing “chicken coop” should be a dead give-away).  The validation and implementation of this for all 155,000 codes is, however, a monumental task at best.  Such an undertaking can (and should) be done by those who created the codes in the first place. Unfortunately, something tells me they can be less than thorough.

Should your hospital be your ride?

I recently had the opportunity to attend an event by my institution’s human-centered design group.  With escalating penalties for 30-day re-admissions on the horizon, they’d been charged with finding a way to bring our rates down. Like any set of Lean-trained professionals, they began delving into the chain of causes leading to patients bouncing back into the ER (i.e. the “5 Whys”).  Their thought process was: We’re having too many 30 day re-admissions (why?). Because patients are missing their follow-up appointments (why?). Because they can’t arrange transportation (why?).  At this point, two different threads emerged. On the one hand, public transport wasn’t sufficiently robust to deliver the patients to their appointments and take them home in a timely manner; on the other hand, patients had trouble arranging rides home because clinic appointments tended to run late and they never knew when they needed to be picked up.  The latter is a process-centered, Lean-friendly kind of problem (and can be addressed as such). But what about the former? The logic was that “Either through re-admission penalties or taxi vouchers or some other way, we’re paying for these patients inability to find adequate transportation. So why not do it directly?” So the presenters began a pilot program providing transportation to patients who couldn’t find a ride.

Note that we only got “3 Whys” deep before we lost the distinction between the responsibilities of the healthcare system and the responsibilities of society at large. Since many hospitals are public institutions, I don’t believe this is necessarily wrong.  However, we need to acknowledge the uncomfortable position this puts us in.  The medical-industrial complex already plays a large role in our lives. By expanding the explicit responsibilities of healthcare organizations, we also expand their responsibility for the (generally unspoken) social determinants of health.  Doing so creates redundancies and conflicts between different healthcare organizations and between healthcare organizations and the social support systems they try to supplement. Competition drives innovation, but economics of scale drives efficiency.  The question is: how de we find a balance between the two?

Are doctors obligated to seek knowledge that has no medical benefit?

The New York Times published an article titled “A Life-Death Predictor Adds to a Cancer’s Strain” or, alternatively, “Genetic Test Changes Game in Cancer Prognosis.”  The piece is interesting on several levels, but, to me, serves to highlight an increasingly common ethical conundrum: are physicians obligated to seek knowledge that is available but has no possible medical benefit?

Most of us are familiar with the Schrödinger’s cat thought experiment (the basic setup: a cat is placed in a box, along with a device that has a 50/50 chance of killing it within the hour).  Suppose Schrödinger decided to actually carry out this experiment and you happen to be the veterinarian for the poor soul whose cat he borrowed.  Having been rushed to the scene by a distraught owner, you are faced with a choice: open the box and reveal the cat’s present state of health or wait and let the cat reveal itself by its eventual demands to be let free (or lack thereof).

Where my story runs parallel to real life: at the point of decision, Schrödinger’s veterinarian and the physician have no power over the patient’s outcome.  Their professional capacity as healer has been exhausted. The cat is either dead or alive.  The patient has Class 1 or Class 2 ocular melanoma (and its attendant mortality).  Until the proverbial box has been opened, however, neither state of affairs has quite come to pass.  The patient is neither doomed nor saved.  The physician stands as the portal of knowledge, holding the key that could dispel fear but also kill hope.

Typically, patients just want the good news.  In a perfect world, only patients with the treatable Class 1 melanoma would have the test performed.  Their Class 2 counterparts, on the other hand, would avoid it and preserve their hope until the end.  Unfortunately, this perfect world requires physicians with prescience (or an ethics “flexible” enough to perform the test without the patient’s knowledge).

What, then, of our imperfect world?  Is the possibility of relief worth the risk of a death sentence?  Further, what is the physician’s role in answering this question?  It is my belief that the option must be presented. The decision to know or not know is deeply personal.  Once he has stepped outside of his role as healer, the physician has no expert knowledge to justify any form of paternalism.  While he can serve as counselor, interpreter and friend, the physician has no right to decide if the possibility of finding a dead cat is worse than waiting next to a terrifyingly silent box.