This isn’t really about pediatric critical care, but it’s a topic that once again has come up for debate: how many doctors do we need? Do we already have enough? Is the problem mainly one of distribution, both in the sense of having too many specialists and a geographic maldistribution of doctors? A little over a decade ago the received opinion was that we were heading for a doctor glut, and should cut back on the number we trained. Now many predict we will not have enough doctors, especially with the progressive aging of our population. Several states have made plans for expanding the sizes of their medical school classes, and, for the first time in decades, new medical schools are opening. You can read a good discussion of this trend here.
On the other hand, some say the statement that we will be short of doctors is false. For one thing, we already have more doctors now than ever before — in 1950 we had 145 physicians for every 100,000 persons, and now we have 280 per 100,000. By 2020, even without expansion of medical schools, we are projected to have 294 doctors for every 100,000 citizens. The problem, some say, is a maldistribution of doctors and too many specialists. You can read a good summary of that argument here.
A major problem in all these discussions is that we really don’t know what the optimal number of doctors is. There is also vigorous debate over whether many things doctors do could be done, often more cheaply, by others, such as nurse practitioners and physician assistants. There is also the real probability that having more doctors will actually drive up demand for what doctors do, thereby increasing the costs of medical care even higher than they already are.
One thing most people don’t realize is that the federal government is the de facto gatekeeper for the number of new doctors we train because it controls much of the financial support for training of resident physicians, the next step after medical school. So it is residency slots, not medical school class size, that determines things. Currently we have more residency slots than we have medical school graduates — the balance is filled out by residents who went to medical schools in other countries. If we have more domestic graduates there will be less foreign residents, but the total won’t change unless the cap on residency slots is lifted.
What do I think? I think health care is not like other parts of our economy, and trying to use simple market-based reasoning will not work. In many ways, doctors drive the demand for our services. We do things, order things. This means, at least in our present system, having more doctors will stimulate more demand, demand which is in some ways insatiable.
There are many debates around the blogosphere about this complicated issue. You can follow a good discussion of it here.
We have had a vaccine against varicella (chickenpox) for over 15 years now. A recent study in the journal Pediatrics assessed how well it has worked at one of its major jobs — preventing death from chickenpox. Just have a look at this graph, taken from the article. It breaks down chickenpox deaths into those in which it was the direct cause and those in which it was a contributing cause.
Many parents, and certainly virtually all grandparents, would be startled by my title. Deaths from chickenpox? Isn’t getting chickenpox just an ordinary part of childhood? Well, until recently it was. A fair number of parents still think it should be, deliberately exposing their child to active cases in the hope (expectation, really) that their child will contract a mild case and then be immune for life. I’ve also heard parents say that the “natural” chickenpox is more protective than the vaccine is. There is some truth in this if your child only gets one vaccination. However, a booster shot later gives a child the same degree of protection as the natural illness. You can get a good view of that discussion over at Dr. Wendy Swanson’s blog, SeattleMamaDoc. Here is what Dr. Paul Offit, noted vaccine expert at Children’s Hospital of Philadelphia, has to say about this.
Chickenpox deaths were rare even before the vaccine. But they happened. Before I went into critical care I practiced the subspecialty pediatric infectious diseases, and I saw several. Children who had abnormal immune systems, especially from cancer treatment, were particularly susceptible. Eradicating chickenpox from the population protects these vulnerable children because chickenpox is one of the most highly infectious diseases known, with an attack rate of well over 90%. The majority of severe cases, however, were still in otherwise normal children.
The graph is dramatic, but if you look at the numbers you will see that even before the vaccine we only had about 1 death per million children or so — that’s a lower risk than driving on the interstate. But deaths were only the tip of the iceberg. Chickenpox also led to a large number of hospitalizations (and severe disease) from secondary infection of the pox sores. You can well imagine how skin bacteria could take advantage of so many breaks in the skin to crawl in and cause trouble. The most notorious for doing this was Staphylcoccus aureus (aka staph), but others could do it as well.
Here are the current recommendations from the Centers for Disease Control, and here’s what the American Academy of Pediatrics says about it.
Doctors use a lot of tests — blood tests, urine tests, x-rays, MRI scans, and quite a few others. Some of these tests carry well-known risks in doing them. For example, a few people have serious allergic reactions to the contrast dye used in certain x-ray tests. For most of the other tests, though, the immediate risk is so low to essentially non-existent. A needle stick hurts for a few minutes, but that soon passes. Getting a simple urine sample doesn’t hurt at all. So what is the harm in getting these kinds of tests because we’re curious what they will show? For example, the “as long as you’re drawing the blood anyway” question comes up frequently; after all, once the needle is in the vein, it’s easy to take a little extra blood for extra tests.
It seems innocent, but what most parents don’t understand is another, more insidious risk, one that using a shotgun approach to testing will bring — the risk the test will give misleading information. A blood or urine test, something of little immediate risk to the child, becomes potentially quite risky if the result will confuse the situation. What can happen is that the test, if just a little (and insignificantly) “abnormal” can lead to further tests and procedures, things that you never would have ordered in the first place. These further tests, in turn, carry further risks. To complicate matters even more, every medical test has a built-in, inherent error rate; the test result may just be flat-out wrong — it’s a statistical possibility. The rule of thumb I’ve often heard is that if you do 20 blood tests, statistically one of them will be falsely abnormal, a fake.
The scenario of an abnormal result in a test done for dubious reasons, leading in turn to more tests, and ultimately to some bad medical decision making, is a well known phenomenon.
My point is that it is never a good idea to ask your doctor to do tests on your child just because you (or your doctor) are simply curious about the result. Any test needs to be clearly justified by a child’s specific situation.
Nearly everyone has heard about the medical malpractice controversy. Most doctors call it a crisis, saying, among other things, that physicians are retiring early because of it or altering their practice — not taking on what they might see as patients more likely to sue. Nonphysicians aren’t so sure about that.
What is clear is that malpractice insurance premiums, what a doctor pays every year to an insurance company and which is required by all states I know to practice, are also climbing inexorably. This seems to be happening even some states that have enacted various kinds of limits on malpractice awards, even though these measures were intended, among other things, to halt these rises in premiums. In other states, notably Mississippi, this may not be the case.
It’s also clear that the entire system we have of malpractice also does a terrible job with the two things it’s supposed to do: sanction doctors who practice bad medicine, and thereby protect the public, and compensate patients who have been injured by bad medical practice. In fact, neither of these things happen.
Meanwhile doctors fear malpractice lawsuits. This has both psychological and practical effects on physicians. There is the general perception that doctors practice a lot of what is called “defensive medicine,” doing things we otherwise would not do if we did not fear getting sued if we didn’t do them. So emergency departments get a whole lot of head CT scans, even when the probability of finding anything significant is remote. It only takes one scan you didn’t do, even though best practice guidelines say you shouldn’t, to land you in court. It’s unknown how much defensive medicine affects healthcare, but it certainly is a real thing — I’ve seen it in action, and I’m sure I’ve done it myself now and then. You can read a good article about it’s magnitude here, but it clearly costs billions. It’s also inherently unsafe: unnecessary testing can lead to unnecessary procedures, and thus unnecessary risk to patients.
But how justified are doctors’ fears of getting sued? How likely in a lifetime of practice is a doctor to face a malpractice claim? That’s really the bottom line. If I’m lecturing to a medical school class, I’d like to be able to tell them what their chances are over a lifetime of practice. I’m nearly 60 years old and have not (yet) been sued — is that a fluke, or am I the norm? A recent study in the prestigious New England Journal of Medicine finally gives us some answers to these questions.
Not surprisingly, the risk of getting sued varies with the specialty. Neurosurgeons and anesthesiologists are high risk. So are obstetricians, since complications of childbirth leading to injury are frequent causes for lawsuits. Pediatricians get sued for those cases, too, because there often is a pediatrician involved in the care of the infant. Neurosurgeons, on average (it does vary from place to place), have a nearly 20% chance each year of getting sued. For pediatricians, it’s about 3%, although the rate for my own subspecialty of pediatric critical care is much higher than it is for general pediatricians.
There is an important caveat in these data, one that you can’t tease out of the article: not every doctor in a given specialty is equally likely to get sued. That is, some doctors, one would think the worst ones, are more likely to get sued. The problem is that this is not the case. Research has shown that overall competency is not correlated with getting sued. To doctors, it seems almost random, driven by luck. This is what can drive them crazy, as well as lead to more defensive medicine.
The nub of the article, though, is lifetime risk: how likely is a doctor to get sued in a lifetime of practice? The answer is — very, very likely. For those in high risk specialties, the chances are virtually 100%. So, if you become an obstetrician, you will be sued at least once. Even if you practice a low-risk specialty, like pediatrics, you have a 70-80% lifetime risk of getting sued.
More than anything else, those numbers emphasize that our current malpractice system is unsatisfactory. Think about it — it’s saying that every single neurosurgeon in America, and three-quarters of all pediatricians, are accused of malpractice at least once in their career. Malpractice is not the same thing as making a mistake; we all make mistakes, large or small. Malpractice is clear negligence leading to patient injury.
As it turns out, physicians accused of malpractice, if the case goes to trial, are far more likely to win than are the plaintiffs — the doctors win about 85% of the time. Clear-cut cases, in which the doctor very likely was negligent, tend to be settled without trial. But not always, and this is another aspect that upsets doctors; it is typically the insurance company, not the doctor, who decides to settle the case, even though the doctor may want to fight it out in court. So a financial decision by an insurance company creates a blot on a doctor’s record that lasts for the rest of his or her career. And it is a blot. Every time I renew my medical license or hospital privileges I have to answer, not only if there are any malpractice judgements against me, but also if there are any pending claims that haven’t even gotten to court yet. To be accused is to have the stain already.
Again, the system we’ve got is both a bad way to discipline and even remove from practice bad doctors, and an unfair and inefficient way to compensate patients who really have been injured by malpractice. We’ve got to do better. My own opinion is that some sort of medical injury board, sort of like a workman’s compensation board, should handle most of these. Both experts and members of the public would be represented. But if people can bypass such an arrangement, or sue anyway if they don’t get what they want, such boards would simply add another layer to the already slow and complicated process.
A hundred years ago virtually all decisions about how to care for sick children came from the child’s family. It was the norm. By mid-century, though, things had changed significantly. Medical professionals—doctors and nurses—were making more and more of these decisions. In some cases families were even actively excluded from key decision-making. It was a time of paternalism, the notion that the doctors always knew the best thing to do. Parents were also physically shut out of the process. For example, when I began my pediatric training in 1978, families were excluded from the pediatric intensive care unit for long stretches of time by restricted visiting hours. If their child needed some sort of a procedure, such as an intravenous line, the parents were often told to leave while it was being done.
These days the pendulum is swinging back with the increasing acceptance of what is called family-centered care. The notion is pretty simple: parents are encouraged to stay with their child as much as they like (although we do try to make sure they are getting some breaks from the PICU), and we involve them in all significant decision-making. Many PICUs involve the parents in the ritual of bed-side rounds, the time when the entire care team goes around the unit and discusses each child’s case. This particular innovation has been greatly helped by changes in the physical layout of the PICU. Thirty years ago most units were just one open room with beds or cribs arrayed around the walls. Now most newly constructed PICUs have private rooms. This is important, because parents don’t want their child’s case discussed in detail within earshot of other parents.
These days most parents also stay to watch and comfort their child during procedures (although a few do choose to leave during them). Even though we use sedatives and pain-killers to minimize the discomfort of procedures, having a parent at the bedside is enormously helpful. This is particularly so during those rare and tension-filled times when we are performing cardiopulmonary resuscitation (CPR). When parents are present, though, it is important to detail a member of the team to sit with them and explain exactly what we are doing and why.
Nearly all parents think this is a good thing. Many have told me their imaginings of what I am doing to their child is far more stressful to them than actually watching me do it. Some physicians are uncomfortable with this notion, since it lays bare some of our ignorance and fumbling. But we need to get used to it, both because it is the wave of the future and because it is the right thing to do.
You can read much more about the family care movement in medical care here and here.
I would think by now, midway through 2011, that I wouldn’t have to write anything about the importance of child car seats. But I find I do, because as I drive around I still see adults holding babies and toddlers over their shoulder, often while sitting in the front seat. This has been illegal in most places for many years, but it is still common and it is still stupid and dangerous. I also still see the results–several children each year come through the PICU who were unrestrained passengers in a car accident, and a few of them die.
Here are some statistics on car seats and motor vehicle accidents. (The most recent I could find come from 2003.) For that year nearly 59,000 children under the age of 5 were injured, 8% of them seriously, and about 1% died. This amounted to 471 children. Significantly, over one third of the children who died were unrestrained.
Most of us have been lectured to about these things, but I have found many parents have difficulty understanding notions of statistical risk. For example, one study showed 72% of parents were seriously afraid their child would be abducted by a stranger. That is a legitimate fear, but it is not very likely to happen; in fact, it is vanishingly unlikely. It is only one-fourth as likely as you getting struck by lightning.
My point is that parents should do what they can to reduce the chances of their child suffering harm: by all means tell your child about what to do when approached by strangers, but also please buckle them into a car seat, preferably in the back seat, when you drive anywhere with them, even a short distance.
You can find an excellent overview of all manner of car seats and how to use them here at the American Academy of Pediatrics site.
Most people think medicine is a science. Mostly, that’s true. But only mostly. In fact, medicine makes frequent use of science, but it’s not entirely science — it’s more of a mishmash of science, experience, intuition, guesswork, and blind luck. Many wish this were not so, but it is.
The last decade has seen an attempt to bring more scientific rigor into medical practice. The movement is called Evidence Based Medicine. The notion seems simple, one few could argue with: take a critical look at all the research that’s been done about a particular medical treatment and see if, on balance, the treatment works. The process has several important principles, among which are to establish in advance how much credance we should place on various research studies, especially when they conflict with one another. To do this we assign a hierarchy of reliability of the evidence. The weakest evidence is expert opinion alone — after all, experts can be wrong. The reliability of evidence works its way up from there, through case reports to uncontrolled trials to the strongest evidence — the randomized, placebo-controlled trial.
These trials compare the results between two groups of patients: those who got the treatment and those who didn’t. One key to this is the placebo part: neither group knows until the trial is over who got the treatment and who got the “placebo,” the sugar pill. A second key is patients are randomly assigned to the treatment or the placebo groups. A final crucial element is that the doctors caring for the patients don’t know themselves who’s getting the treatment and who’s getting the placebo until after the trial is done. Then the investigators look at the data and see if the treatment works, if it’s better than the placebo.
Sounds simple. It isn’t, though, especially as it applies to the Holy Grail of evidence based medicine. For one thing, for some things there isn’t a good placebo — a major operation, for example. For another, physicians have only studied a tiny fraction of all medical conditions, typically those which affect a lot of people, are controversial for one reason or another, or which look financially promising to drug companies.
So how do I and my colleagues decide what to do? We use hard evidence if there is any. We do what makes sense in light of what we do know about the condition or others like it. We tend to do what we have been taught, and we respect the opinions of our medical forebearers. Sometimes we have no idea what to do, in which case it is usually better to do nothing. In short, we still rely to some extent on experience, intuition, guesswork, and blind luck. For myself, I actually like things to stay at least a little bit that way.
If you want to learn more about evidence based medicine, the guiding organization is the Cochrane Collaboration, a huge group of valiant volunteers who scour the medical literature to collect information about specific ailments and write reviews about what the data show. The Cochrane site is here.
In previous posts I described various kinds of medical evidence, ranked from less to more reliable. This time I’ll lay out how researchers collect the best evidence — something called the randomized, controlled trial. These are the gold-standard for clinical research in medicine. They are also the most difficult and expensive kind of clinical research to do.
The concept is simple. If, for example, an investigator wants to test if a particular pill is effective against a certain disease, she identifies a group of patients with the condition, gives half of them the pill and the other half a fake pill, called a placebo, and sees what happens. The key to the validity of the trial is that assignment of a patient to the group that gets the drug or the placebo is truly random (this is often done by computer code), and that neither the patient nor the investigator knows which patient is in which group until after the trial is over, at which time the code disguising the two groups is unsealed and the data analyzed. The randomized, controlled trial eliminates nearly all the problems you read about in earlier posts, although even randomized trials have occasionally been bedeviled by the discovery afterwards that the control and experimental groups did, in fact, differ in key ways.
Randomized, controlled trials are the centerpiece for a recent movement in medical practice called evidence-based medicine. The term could, of course, allow doctors to use any sort of evidence, but what people mean by evidence-based medicine is that doctors should be guided by the results, whenever possible, of proper randomized, controlled trials. If there are not any such data available, then doctors should use a formal, defined process for evaluating what evidence there is. They should weigh the evidence much as we are doing now, ranking it from expert opinion, through case series, uncontrolled trials, and up to any controlled trial information there is available.
There is even a name assigned to this formal evaluative process — meta-analysis. The notion of meta-analysis is that the results of several, disparate studies, which by themselves might be inconclusive, can be pooled together to reach a conclusive, composite answer. Of course one cannot make a silk purse from a sow’s ear; the summation of several bad studies can simply be a single bad study. However, meta-analysis does have the ability to make explicit how we judge the validity of medical research.
If randomized, controlled studies are the gold standard, why are we even discussing any of those less useful methods? Why not just do that kind of research for everything? The answer is two-fold. For one thing, relatively few disorders have been the subject of randomized trials because they are extremely complicated and expensive experiments to plan and carry out. They often take years to map out and execute, followed by another year or more to analyze the data. A second issue is that it is not really possible to devise a randomized, controlled trial to examine many of the medical questions parents — and pediatricians, too — have about their children, even if we had the time and money to do it.
Randomized trials are best suited to testing some kind of therapy or intervention. But the intervention must be of the sort that neither the researcher nor the subject knows if they are using the experimental treatment or the placebo. This is feasible for a pill, although even then it can prove difficult. For example, one of the trials about the effectiveness of fish oil in reducing the risk of heart disease was complicated by the fact the fish oil smelled and tasted a certain way, alerting the subject to what group he was in.
For some things it is difficult even to devise a placebo — a surgical procedure, for example. Some questions are so important to answer that patients have undergone (with their informed consent, of course) sham surgery as a way to blind both the subject and the evaluator to which group the patient was in. Considering how difficult it is to set trials like this up it is understandable why so many things, important things for children’s health, have never been studied with a randomized, controlled trial, and very likely never will be. We will just have to decide what to do with data which, although still usable, are intrinsically less reliable. That is unfortunate, but that is the reality.
For myself, I find this notion comforting — it means there still is a place in medical practice for intuition and common sense.
Here is another post in understanding the proper use of medical evidence. (Previous ones in the series are here, here, here, and here) Medical researchers can use several techniques to try and get around some the pitfalls you read about in earlier posts. Various kinds of population studies are examples of how they do this.
These kinds of studies can be retrospective, meaning we look back in time at things that have already happened to people, or prospective, meaning we follow forward, in real time, a group of patients to observe what happens. They are most often used to determine if there is any association between something, say a drug or an environmental exposure, and a disease.
Finding such an association doesn’t prove causation. We must beware of another logical fallacy, cum hoc ergo propter hoc, or “with this, therefore because of this” in the Latin. But a very strong association between two things is reasonable evidence for a link of some sort between them, such as one thing at least partially causing the other, or else both being caused by some third thing. After all, where there’s smoke, there’s usually fire.
One common tool of this sort of research is the case-control study. In this technique the researcher tries to identify a group of people who have the thing she’s studying (the case group) and match it with another group of people who are just like the case group in such things as age, sex, and whatever else might confound the analysis, but who don’t have the disease (the control group).
The two groups can then be compared, looking for things that the case group has that the control group doesn’t; such things could then be associated with the disease, and maybe even cause it. The crucial part of this process is choosing a good control group. Sometimes each individual case has its own individual control, matched to it as closely as possible. A major problem with case-control studies is that investigators can only match the two groups for confounding variables they know or think at the time may be important for the disease they are studying; it may turn out later some completely different thing was important, something they didn’t control for when they matched the two groups because they didn’t know it mattered.
Here is a simple, hypothetical example of what I mean. Suppose an investigator has a theory a certain food is protective against cancer of the large intestine (colon). She identifies persons who developed the cancer, matches them with others who don’t have the cancer, and then does a detailed analysis of the diets of the two groups to see if there were differences between cases and controls in how much they ate of whatever the theoretically protective food item is. If she doesn’t match the case and control groups for the variable of having a family history of colon cancer, she will be seriously misled by the results because colon cancer is one of those malignancies that tend to run in families.
Case-control studies, if they use interview techniques, can be quite susceptible to recall bias. For example, imagine you are trying to determine if exposure to a particular food is associated with a medical problem. You assemble a group of patients who have a disease and ask them about exposure to whatever food you are investigating. Then you ask the same questions of those in the control group. The trouble is, usually researchers are investigating a potential connection like this because it’s already believed at least by some people, perhaps many people, that there is one. If it’s already widely believed there is such an association, unless you design your survey very carefully, the patients in the case group are more likely to recall an exposure to whatever the food is than are your controls.
Another way to examine, say, the theory a particular environmental agent or activity is associated with developing a disease is to do a prospective cohort study, selecting two groups of people who differ only in their exposure to the thing being studied, and then follow them over time to see what happens. This kind of study is much less likely to be plagued with recall bias because you are not asking people to remember what already happened to them. (It is also more time-consuming, often taking years.) If the hypothesis is correct, then those exposed to whatever the agent or activity you’re studying should be more likely to get the disease than are those who aren’t exposed. Like case-control studies, however, the key is in the selection of the control group — it must not differ from the case group in any way that could affect susceptibility to getting the disease.
Properly done, these kinds of population studies give much more reliable data than do the techniques I discussed in previous posts — expert opinion, case reports, and uncontrolled trials. However, they don’t lend themselves well to treatment trials, assessing what works, because the population researcher is generally just passively observing things. The best way to determine if a treatment works is to use the gold standard, known as the randomized, controlled trial. You will read about how those work in a later post.
Here is another post about how to read news reports about a medical claim and evaluate for yourself if it’s valid or not. My last post dealt with case reports — doctors’ descriptions of patients they have seen — as medical evidence. Although useful, that sort of information has serious pitfalls. This post is about the next rung on the ladder of reliability of medical evidence — what we call the uncontrolled clinical trial.
Researchers can do other things with a series of patient cases besides simply describing what the patients are like; they can manipulate the situation in various ways. For example, if a doctor looks at her series of patients and becomes convinced that a particular therapy will work for the disease, she can give the therapy to the next patient, or series of patients, that come her way with the problem, and see what happens. This would constitute one version of an uncontrolled trial, and is probably the oldest kind of medical treatment research doctors have used. Venerable as the technique is, it is easy to see how an experiment like this could yield misleading results.
First, the patient group is subject to the same selection bias as that of the case series — the assortment of people with the problem who come to see the doctor are unlikely to represent a random sample of all people with the disease. Next, the only way the doctor could decide the treatment might be helping would be to compare what happens in the patients who get the new therapy with the patients she saw in the past who did not. Such so-called historical controls are the weakest sort of control group. This is because they are subject to the same kind of selection bias as the experimental group, those who get the treatment. More than that, since they were seeing the doctor at an earlier time, they may not even be representative of the patients with the disease who are seeing her now. Finally, a doctor who believes that a particular treatment will work (which is, after all, why she is doing the experimental trial in the first place) is hardly the best person to decide impartially if that is so. All of us want our theories to be correct, so her evaluation is bound to be slanted — it is only human nature at work.
Uncontrolled trials like this are particularly susceptible to what logicians call the fallacy of post hoc, ergo propter hoc, translated from the Latin as “after this, therefore because of this.” Anyone who has watched late-night cable television has seen countless examples of this logical trap, in the form of personal testimonials from people who had this or that problem, took the pill or bought the product, and the problem went away. The fallacy, of course, is that the two events may be entirely unrelated, just as the fact I may drink coffee every morning before the sun comes up does not cause the heavens to move in that way.
Trials like this are also highly prone to suffer from the placebo effect, the trick the human mind plays on us to believe so much that a particular treatment is working we actually will it to happen. The power of wishful thinking in the human mind is astonishing. Even more astonishing is that, in some situations, the “useless” placebo, a sugar pill or its equivalent, actually does improve the situation, if only slightly (15-30% by most estimates). So oftentimes people get a little better no matter what the therapy. The only way we can be sure the improvement is from the therapy (as a therapy, and not a placebo) is to blind both the patient and the observer to knowing which patients got the treatment and which ones got the placebo. Those clinical trials are called randomized controlled trials, and I’ll write about them in a later post.
