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It’s Personal.

In 2013 Esquire magazine began a series of articles about Stephanie Lee, a 36-year old woman in Mississippi with stage 4 colon cancer.  It’s an incredible story, well-told by Tom Junod and Mark Warren.  You can find the first part here:

The original point of the story was to discuss the path taken by Stephanie through the new world of Personalized Medicine.  The authors, having met Eric Schadt,a leading biomathematician, at Mt Sinai Hospital on a previous assignment, introduced Stephanie to Schadt.  Schadt offered to sequence Stephanie’s tumor and attempt to find a specific treatment targeted at her tumor. (Subsequent events bring up a whole separate set of questions about end-of-life care, medical ethics, hope, futility, and suffering that make the story thought-provoking reading.)

Personalized Medicine is all the rage right now.  The government is throwing money at it, to the tune of $215 million dollars.  The President of the United States himself is on board: “Personalized medicine represents a revolutionary and exciting change in the fundamental approach and practice of medicine.”

Dr. Ralph Snyderman, one of the very first advocates of personalized medicine, says the following, according to the New York Times (

“Personalized medicine has the potential to transform our health care system, which consumes almost $3 trillion a year, 80 percent of it for preventable diseases.  It focuses therapy on individuals in whom it will work. You can avoid wasting money on people who won’t respond or will have an adverse reaction.”

Well, not quite.  Or at least, not yet.  Esquire is, of course, not a scientific journal and the authors therein are not scientists, but the story provides a taste of the kind of odds personalized medicine is up against.  Here is an excerpt from Junod and Warren’s story:

The first thing that needs to be understood about Stephanie’s data [her gene sequencing] is that there would be a lot of it. From the samples of Stephanie’s blood, the gene sequencers would generate the data about the genes in her “germline”—the genes (and the gene mutations) that she inherited from her parents and that existed in every cell of her body. From the samples sliced from her colon, the sequencers would generate data about her cancer and the mutations that produced it. But the data would be raw. It would contain millions of bits of genetic information, each one a sentence in the horror story that Stephanie’s cancer was telling—and all those sentences, at least initially, adding up to a bewildering Babel. The data would exist right on the edge of incoherence; then Schadt and his scientists would strive both to make sense of it and complicate it. That’s their trademark, and why they need a supercomputer. The genes that Stephanie was born with would be compared with the genes that were driving Stephanie’s cancer. The genes that were driving Stephanie’s cancer would be compared with the vast libraries of reference data-bases that already exist on all kinds of cancers. Then they would be plotted against the “network models” that the Icahn Institute is constructing, the millions of individual data points mined for their billions and even trillions of connections.

The result would not be dissimilar to the network model portrayed on the screen of Schadt’s office on the afternoon of September 10—a blue sphere of genetic entanglement that resembled nothing less than the universe itself, with each gene a blue star and with some blue stars off by themselves and some clustered into galaxies of cellular activity. The model on the screen happened to be a model of the genes involved in aging, but the model of the genes involved in colon cancer wouldn’t look very different. There would be a globe of blue stars. Somewhere on the blue globe would be plotted the mutant particularities of Stephanie’s cancer, in red; and though the red stars would cohere into a malign galaxy the relative size of Andromeda, they would be the target of the scientists gathered that afternoon in Schadt’s office.

I won’t reveal the punchline, but all of this data crunching took a year and a half, a multimillion dollar genetics laboratory, and a bunch of the top scientists in the world.  It cost hundreds of thousands of dollars (provided gratis by Mt. Sinai to their credit).  Does personalized medicine show promise?  Yes.  Is it giving people hope?  Absolutely.  Is it the Cure for Cancer?  Not yet.

A better PSA


Can we not have this discussion again?  Can we just agree to disagree?

Prostate cancer screening is back in the news, at least for those who read the New York Times and don’t mind their OpEds more Op than Ed. (or more OpEd than evidence-based.)  Deepak Kapoor, an urologist, makes a great case for the PSA test: “But, guys, it’s better now!  Honest!”

Read the comments.  Show us a real study.  Then we’ll talk.

The Problem With Internship

Every once in a while Sandeep Juhar shows up in the New York Times, and it is always a good read.  Today he talked about The Problem With Internship (  Since like Dr. Juhar my medical internship made a deep and lasting impression on me, akin to post traumatic stress, this topic is near and dear to my heart.  Juhar talks about the duty hour restrictions, limits on number of hours worked consecutively mandated by the Accreditation Counsel for Graduate Medical Education (ACGME).  These rules were implemented after several patient deaths were attributed to resident fatigue.  They’ve also been shown to be largely ineffectual at improving patient safety (  Additionally, attending physicians, who have completed residency and are supposedly in charge, have no such restrictions.  Witness my own regular weekend 24-hour in-house call.

The Problem With Internship is not that it sucks.  It is supposed to suck, interns know going in that it is going to suck, and they know what they signed up for.  They signed up because they expected to learn and learn and learn.  An intern is sleepless, has no social life, and eats cafeteria food three times a day, all for about fifty cents an hour, because he expects to learn and learn and learn.

The Problem With Internship is that interns don’t learn.  Or rather, they do but in the most inefficient way imaginable.  This is because the work that they do is not conducive to learning.  Interns are so busy writing notes and keeping up patient databases and signing off to each other that they see relatively little of actual patients.  As another of my favorite health writers Pauline Chen reported in 2013 that a study in the Journal of General Internal Medicine found that “interns were devoting about eight minutes each day to each patient, only about 12 percent of their time”. (

In order to learn medicine, or surgery, or whatever, you have to see a lot of patients.  Really see them, talk to them, examine them.  You need to see lots of the common disorders but you also have to see the really complicated patients, the really sick ones, the ones that take two hours to admit in a truly thoughtful way.  When the senior resident is operating on the appendectomy while the intern is updating the computerized patient list, that intern is not learning.  When the third-year anesthesia resident is doing podiatry cases all day while an attending solos on a trauma, that resident isn’t learning.  When the ICU resident knows that he has to start gathering all the data for morning rounds at 3 AM in order to enter it all into the computer, that resident is not learning.  Interns are being used by hospitals as cheap labor, a warm body in a seat or holding a retractor.  The goal of internship should be to learn.  The ACGME should be mandating the hiring of PAs, NPs, and other ancillary staff for paperwork, data gathering, and note-taking.  The ACGME should be requiring large amounts of real patient contact and truly valuable educational opportunities.  Interns won’t mind how many hours they work.  They will learn.

Taking Sides

Let me first say that I am not, nor have I ever been, in favor of independent practice for CRNAs.  I know a lot of my detractors think I am.  Thus I come to the MD vs CRNA argument with the general understanding that physician anesthesiologists should, in general, oversee the work of their “midlevels”.  The problem is that I suspect that even if the independent practice issue, which is mostly coming from the CRNA governing societies, not individual CRNAs, were off the table, the battle would still rage.  And now I think I know why. In the world of anesthesia politics something odd is going on.  While opposition to CRNAs among physicians is vocal and strident in the upper echelons of the high mucky-mucks in the American Society of Anesthesiologists (ASA), state societies of anesthesia are being encouraged to welcome another group of “midlevels”: Anesthesia Assistants.

What is an AA, exactly?

Here is what the AAAA (American Academy of Anesthesiologist Assistants, of course) says in their career flyer:

Anesthesiologist Assistants are highly educated allied health professionals who work under the direction of licensed anesthesiologists to develop and implement anesthesia care plans.  AAs work exclusively within the Anesthesia Care Team environment as described by the ASA.  AAs are trained extensively in the delivery and maintenance of quality anesthesia care as well as advanced patient monitoring techniques.

Ah.  So, they’re like CRNAs.  What’s the difference?  AA programs are based on a masters degree model.  So are CRNA programs.  AA programs require two full academic years and accepts students who have prior education in the sciences.  So do CRNA programs.  Let’s see, what else… physiology, pharmacology, anatomy, biochemistry, patient monitoring, life support, patient assessment… Yup.  All the same.  However, there is a significant difference: AA programs typically require a bachelor’s degree with all the premed requirements, and the MCAT (or GRE, for the faint of heart).  CRNA programs require a background in critical care nursing and a bachelor’s degree in nursing or related field.

Anesthesia Assistants are trained under the prevailing medical model, while CRNAs are trained from the nursing side.  AAs, therefore, are under the umbrella of medical certification, and indeed the certifying exam for AAs is administered and scored by the National Board of Medical Examiners.  CRNAs are certified by their own organization, and as such are separate from the dictates of medical societies.

AAs and CRNAs do the same work.  Yet no one is yelling about AAs taking over physician anesthesiologist jobs.  You see, AA societies are much more controllable by state medical societies, and AAAA would never, ever, suggest independent practice. AAs are firmly on the doctors’ side, since sides are being taken.  According to the most recent issue of the ASA newsletter, the Ohio Society of Anesthesiologists voted in September of 2012 to include AAs as members.  Here’s what Dr. Basem Abdelmalak, OSA president, said:

“When we met with the Ohio AAs, we found that we share the same passion for excellent care.”

(OK, but CRNAs have the same passion for excellent care.)  He continues:

“We have the same understanding and expectations of the anesthesia care team model and the roles of different members of the team under the direction of the physician anesthesiologist.”

Bingo.  Those Anesthesia Assistants are speaking Dr. Abdelmalak’s language.  CRNAs are not.  That’s the problem.  That’s why the fight continues.  That’s why sides are being taken and barricades built.

I call on the ASA and the AANA (American Association of Nurse Anesthetists) to sit down with each other and create a common language. Medicine and Nursing should not be on opposite sides of anything.  We should all be working together.




Rise of the Machines

Here’s an astonishing assertion:

“We are convinced the machine can do better than human anesthesiologists.”

This statement was made by a doctor.  Not only a doctor but an anesthesiologist.  Not just an anesthesiologist but a pediatric anesthesiologist.  Not just any old pediatric anesthesiologist but one in charge of pediatric anesthesia research at the University of British Columbia medical school in Vancouver.  One can only assume that this guy has a pretty low estimation of what his colleagues can do.  Must make for great break room conversation.

The doctor making this statement, one JM Ansermino, is co-creator of a new automated anesthesia system called, cutely, iControl-RP.  This machine uses vital sign readings along with oxygen saturation levels and EEG monitoring to give anesthesia to patients undergoing surgery, without any human input.  Thanks to my fellow blogger Karen Siebert for pointing this one out. and

iControl-RP is what the creators call “A scheme-based closed-loop anesthesia system”.  Here’s what their paper says about it: (

The system software in its entirety consists of approximately 22K lines of Scheme code and features a client-server implementation interfacing medical devices with portable graphical user interface.  The strengths of the Scheme functional language have been leveraged to build a robust maintainable modular system with extensive testing facilities to mitigate the inherent safety hazards associated with the application.

Blah, blah, blah… wait.  “Inherent safety hazards?”  You think?

Look.  Here is the “problem” that the folks in Vancouver are hoping to “solve”.  Intravenous anesthetics like Propofol have dosage and administration guidelines that are, in practice, mere suggestions.  People have a very wide range of responses to sedatives and the effects can not always be predicted.  Which is why you have a human, an anesthesiologist or CRNA, up at the head of the bed controlling the dosing.  This type of sedation, using intravenous agents only, is not usually called “General Anesthesia (GA)”. You can do a GA with just IV drugs but is not very common.  Usually Propofol infusions are used in what we call a MAC or “Monitored Anesthetic Care” which is a really stupid name that basically implies that someone is giving sedation and monitoring how it works, but in reality means that the patient is sedated but retains the ability to maintain independent respiration, and someone is adjusting things so that both sedation and spontaneous breathing occur.  In other words, you’re in la la land but don’t need to be put on a ventilator.  We use it for procedures in which local anesthetic effectively numbs the surgical area so that all that is needed is to make the patient comfortable.

There are a number of cases in which doing a procedure under MAC becomes difficult to impossible.  For example, if the local anesthetic is not adequate to block the pain at the surgical site MAC is tricky because the level of sedation needed to eliminate the experience of pain usually also causes people to stop breathing.  Obese patients are at risk of airway obstruction at even fairly low levels of sedation.  A young teenager might still be reactive at very high levels of sedation.  People with involuntary movements, tics, restless legs, etc. often do not lose these movements when sedated.  Some people get more agitated the less aware they are of their surroundings. People who take drugs or chronic pain medications respond very differently and may prove impossible to sedate adequately under MAC conditions.

In some cases the anesthesiologist might decide “switch from a MAC to a GA”, at which time the anesthesiologist takes over breathing for the patient and thus is able to provide an higher level of sedation.  This decision is not made easily or lightly.  It requires considerations about patient size and state of health, how effective the surgeon is at numbing the surgical area, how fast the surgeon is, what the anesthesiologists threshold is for switching, what operation is being performed, what the duration of action of the local anesthetic is, unexpected surgical findings or complications, and ultimately, the safety of the patient.  If the decision is made an actual person, i.e, the anesthesiologist, has to secure the airway and then set the ventilator and gas parameters appropriately.  Consider this from the iControl-RP paper:

A closed-loop automated drug delivery system that administers drug based on feedback from measurement of a physiological end point can potentially improve the outcomes for patients by addressing the inter-patient variability, providing greater hemodynamic and respiratory stability, more stable depth of anesthesia, and reducing the total dose of drug delivered.

Where in that sentence is there mention of any of the variables I just listed?  Is there an algorithm for deciding a different approach is needed?  Are there different settings for different surgeons?  Do you dial in a different number for the super-anxious patient or the one with the Methadone habit?  Inter-patient variability is what makes anesthesia part art, part science.  Inter-patient variability is the very reason we need actual humans at the head of the bed.  Patients are not Scheme code.  Which is why…

The “operating room scenario” depicted in figure 1 of the creators’ Researchgate article features an attending anesthesiologist.  To monitor the iControl.


We’re all special!

Hey readers.  Check out my latest pharmaceutical diatribe at The Medical Bag:

Winning the Popularity Contest

I have to take issue with an article published several days ago by the New York Times about communication and the prevention of malpractice litigation ( Aaron E. Carroll, the article’s author and himself a doctor and healthcare policy writer (like me, only way more famous), has oversimplified the discussion quite a bit.  You see, communication is a two-way street.  There are characteristics on both sides of the table that hinder true understanding.  Let’s take one of Carroll’s examples :

A short while ago, the Annals of Emergency Medicine published a study that examined patient-physician communication in the emergency room on the management of acute coronary syndrome, which is chest pain caused by decreased blood flow to the heart, as with a heart attack or angina. About two-thirds of patients left conversations thinking they were having a heart attack, while physicians believed this to be the case less than half the time. The median estimate of whether a patient might die at home of a heart attack was 80 percent in patients and 10 percent in physicians. Doctors and patients were reasonably close in their estimates of danger only 36 percent of the time. They clearly weren’t hearing each other.

Here we have a classic case of misunderstanding that arises from the fact that the two communicators don’t speak the same language.  An old friend of mine says that medical school is all about learning about 100,000 new words.  So the patient thinks “heart attack” and the doctor thinks “myocardial infarction”.  That would be fine except there are ST elevation myocardial infarctions (big heart attack) and NON-ST elevation myocardial infarctions (little heart attack).  Myocardial infarctions can look very different depending on which vessel is blocked, how many are blocked, how long they’ve been blocked, and if they’ve been blocked before.  ALSO, “angina” does not mean “myocardial infarction”.  Angina is only a word for the symptoms that arise from the blockage of a vessel.  “Chest pain” is not the same thing as “angina” unless the pain is related to the heart.  Angina and heart attack are not the same thing.  Acute Coronary Syndrome is actually a fairly new term that encapsulates all of the above. ALSO, there are other problems that LOOK like a heart attack which are not heart-related at all, there being more inside your chest than just your heart.  FINALLY, it isn’t always immediately clear what, of a myriad of possibilities, a person with “chest pain” has.

How could there possibly be any confusion?

Communication is hindered not only by language, but by differences in underlying knowledge base specific to the subject at hand and to differences in receptivity. I might have a patient who is a car mechanic and he can talk ’til he’s blue in the face about cars and I won’t understand him, and I could talk about medicine ’til I’m blue in the face and he might understand me.  Neither of us is stupid or uneducated.  Our underlying knowledge of our respective areas of expertise provide unspoken background that, in essence, translates what we are saying to ourselves, without us realizing that the other person doesn’t have the same background.  Additionally, even solid background information doesn’t help when extreme emotional turmoil is occurring for one of the parties involved.  For example, Dr. Carroll cites the following:

To understand why patients file claims, we have to talk to them. Many researchers have. A study in 1992 found that about a quarter of mothers who had sued physicians because of deaths or permanent injuries in their newborn infants “needed money.” But there were answers given more frequently that had nothing to do with remuneration. A third of respondents said that their doctor would not talk openly to them, half said their doctor had tried to mislead them, and 70 percent said that they were not warned about long-term neurodevelopmental problems in their children.

Maybe the mothers who sued were all lawyers, or librarians, or rocket scientists.  No matter how educated they were, they didn’t necessarily have the knowledge base to understand that the obstetrician might have been talking to them because they were trying to save the babies’ lives at the time.  They might not understand that obstetricians are not pediatricians and don’t actually know anything about neurodevelopmental problems.  It is also possible that the obstetrician did in fact explain what was going on but the mothers were, understandably, freaking out and didn’t hear or retain the information.

The third way communication breaks down is in the areas of emotion and perspective. Human-ness, if you will. Dr. Carroll:

Decades-old studies have shown that primary care physicians sued less often are those more likely to spend time educating patients about their care, more likely to use humor and laugh with their patients and more likely to try to get their patients to talk and express their opinions. It seems that more likable physicians are less likely to have claims filed against them.

Ah.  The popularity card.  But didn’t your mother tell you that not everyone in the world is going to like you?  “Liking” someone or something is a matter of taste.  One patient could really like a doctor one day and another patient could think that same doctor is a jerk the next day.  Maybe one patient likes the doctor because the doctor gives them whatever they want.  Maybe the patient who thinks the doctor is a jerk was really just mad because he had to sit in the waiting room for an hour with nothing but a 3 year old copy of Musclemania.

I’m not saying all doctors are great communicators.  But suggesting that the whole problem with the doctor/patient relationship is that doctors aren’t communicating is akin to what the guy in the lookout perch on the HMS Titanic saw (Smell ice can ya?  Blimey!):  not the whole story.



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