Similarities between a crisis in the ER & healthcare architecture design theory

Hussain Varawalla

While I’m hooked into reviewing books and drawing tenuous connections between their content and healthcare architecture, let me do it one more time with an excellent book I read lately, “Blink” by Malcolm Gladwell.

Blink is a book about thinking on your feet, as the blurb at the rear says, “A book about how we think without thinking…in the blink of an eye.” The book claims to reveal that the best decision makers are not those who agonise over decisions, but those who have perfected the art of “Thin slicing” – knowing the very few things that matter.

Gladwell claims that never again will you think about thinking in the same way. Well, lets test that. I’m going to quote now at length from the book, apologies are due to Gladwell as it is heavily edited, but please buy the book if you are interested to read the entire account. It is available at all fine bookstores, displayed prominently. I give you, dear reader, Malcolm Gladwell.

A crisis in the ER

On West Harrison Street in Chicago, there is an ornate, block-long building designed and built in the early part of the last century. This was the home of Cook County Hospital. It was here that the world’s first blood bank opened, where cobalt-beam therapy was pioneered, where surgeons once reattached four severed fingers, and where the trauma center was so famous, and so busy treating the gunshot wounds and injuries of the surrounding gangs, that it inspired the television series ER. In the late 1990s, however, Cook County Hospital started a project that may one day earn the hospital as much acclaim as any of those earlier accomplishments. Cook County changed the way its physicians diagnose patients coming to the ER complaining of chest pain.

Cook County’s big experiment began in 1996, a year after a remarkable man named Brendan Reilly came to Chicago to become chairman of the hospital’s Department of Medicine. The institution that Reilly inherited was a mess. As the city’s principal public hospital, Cook County was the place of last resort for the hundreds of thousands of Chicagoans without health insurance.

The list of problems Reilly faced was endless. But the Emergency Department (the ED) seemed to cry out for special attention. Because so few Cook County patients had health insurance, most of them entered the hospital through the Emergency Department. There were long lines down the hall. The rooms were jammed. A staggering 250,000 patients came through the ED every year.

From the beginning, the question of how to deal with heart attacks was front and center. A significant number of those people filing into the ED on average, about thirty a day, were worried that they were having a heart attack. And those thirty used more than their share of beds and nurses and doctors and stayed around a lot longer than other patients. Chest-pain patients were resource-intensive. The treatment protocol was long and elaborate and worst of all maddeningly inconclusive.

A patient comes in clutching his chest. A nurse takes his blood pressure. A doctor puts a stethoscope on his chest to detect whether the patient has fluid in his lungs . She asks him a series of questions: How long have you been experiencing chest pain? Where does it hurt? Are you in particular pain when you exercise? Have you had heart trouble before? What’s your cholesterol level? Do you, use drugs? Do you have diabetes? Then a technician performs the electrocardiogram. The ECG is far from perfect. Sometimes someone with an ECG that looks perfectly normal can be in serious trouble, and sometimes someone with an ECG that looks terrifying can be perfectly healthy. There are ways to tell with absolute certainty whether someone is having a heart attack, but those involve tests of particular enzymes that can take hours for results. And the doctor confronted in the emergency room with a patient in agony and another hundred patients in a line down the corridor doesn’t have hours. So when it comes to chest pain, doctors gather as much information as they can, and then they make an estimate.

The problem with that estimate, though, is that it isn’t very accurate. One of the things Reilly did early in his campaign at Cook, for instance, was to put together twenty perfectly typical case histories of people with chest pain and give the histories to a group of doctors: cardiologists, internists, emergency room docs, and medical esidents — people, in other words, who had lots of experience making estimates about chest pain.

The point was to see how much agreement there was about who among the twenty cases was actually having a heart attack. What Reilly found was that there really wasn’t any agreement at all. The answers were all over the map. The same patient might be sent home by one doctor and checked into intensive care by another. “We asked the doctors to estimate on a scale of zero to one hundred the probability that each patient was having an acute myocardial infarction [heart attack] and the odds that each patient would have a major life-threatening complication in the next three days,” Reilly says. “In each case, the answers we got pretty much ranged from zero to one hundred. It was extraordinary.”

The doctors thought they were making reasoned judgments. But in reality they were making something that looked a lot more like a guess, and guessing, of course, leads to mistakes. Somewhere between two and eight percent of the time in American hospitals, a patient having a genuine heart attack gets sent home — because the doctor doing the examination thinks for some reason that the patient is healthy. More commonly, though, doctors correct for their uncertainty by erring heavily on the side of caution.

In recent years, the problem has gotten worse because the medical community has done such a good job of educating people about heart attacks that patients come running to the hospital at the first sign of chest pain. At the same time, the threat of malpractice has made doctors less and less willing to take a chance on a patient, with the result that these days only about 10 percent of those admitted to a hospital on suspicion of having a heart attack actually have a heart attack.

This, then, was Reilly’s problem. He was at Cook County. He was running the Department of Medicine on a shoestring. Yet every year, the hospital found itself spending more and more time and money on people who were not actually having a heart attack. A single bed in Cook County’s coronary care unit, for instance, cost roughly USD 2,000 a night — and a typical chest pain patient might stay for three days, yet the typical chest pain patient might have nothing, at that moment, wrong with him. Is this, the doctors at Cook County asked themselves, any way to run a hospital?

Reilly’s first act was to turn to the work of a cardiologist named Lee Goldman. In the 1970s, Goldman got involved with a group of mathematicians who were very interested in developing statistical rules for telling apart things like subatomic particles. Goldman wasn’t much interested in physics, but it struck him that some of the same mathematical principles the group was using might be helpful in deciding whether someone was suffering a heart attack. So he fed hundreds of cases into a computer, looking at what kinds of things actually predicted a heart attack, and came up with an algorithm, an equation, that he believed would take much of the guesswork out of treating chest pain. Doctors, he concluded, ought to combine the evidence of the ECG with three of what he called urgent risk factors: (i) Is the pain felt by the patient, unstable angina? (2) Is there fluid in the patient’s lungs? and (3) Is the patient’s systolic blood pressure below 100?

For each combination of risk factors, Goldman drew up a decision tree that recommended a treatment option. For example, a patient with a normal ECG who was positive on all three urgent risk factors would go to the intermediate unit; a patient whose ECG showed acute ischemia (that is, the heart muscle wasn’t getting enough blood) but who had either one or no risk factors would be considered low-risk and go to the short-stay unit; someone with an ECG positive for ischemia and two or three risk factors would be sent directly to the cardiac care unit, and so on.

Goldman worked on his decision tree for years, steadily refining and perfecting it. But at the end of his scientific articles, there was always a plaintive sentence about how much more hands-on, real-world research needed to be done before the decision tree could be used in clinical practice. As the years passed, however, no one volunteered to do that research, not even at Harvard Medical School, where Goldman began his work, or at the equally prestigious University of California at San Francisco, where he completed it. For all the rigor of his calculations, it seemed that no one wanted to believe what he was saying, that an equation could perform better than a trained physician.

But Reilly shared none of the medical community’s qualms about Goldman’s findings. He was in a crisis. He took Goldman’s algorithm, presented it to the doctors in the Cook County ED and the doctors in the Department of Medicine, and announced that he was holding a bake-off. For the first few months, the staff would use their own judgment in evaluating chest pain, the way they always had. Then they would use Goldman’s algorithm, and the diagnosis and outcome of every patient treated under the two systems would be compared. For two years, data were collected, and in the end, the result wasn’t even close. Goldman’s rule won hands down in two directions: it was a whopping 70 per cent better than the old method at recognising the patients who weren’t actually having a heart attack.

At the same time, it was safer. The whole point of chest pain prediction is to make sure that patients who end up having major complications are assigned right away to the coronary and intermediate units. Left to their own devices, the doctors guessed right on the most serious patients somewhere between 75 and 89 per cent of the time. The algorithm guessed right more than 95 per cent of the time. For Reilly, that was all the evidence he needed. He went to the ED and changed the rules. In 2001, Cook County Hospital became the first medical institution in the country to devote itself full-time to the Goldman algorithm for chest pain, and if you walk into the Cook County ER, you’ll see a copy of the heart attack decision tree posted on the wall.

Why is the Cook County experiment so important? Because we take it, as a given, that the more information decision makers have, the better off they are. If the specialist we are seeing says she needs to do more tests or examine us in more detail, few of us think that’s a bad idea. But what does the Goldman algorithm say? Quite the opposite: that all that extra information isn’t actually an advantage at all; that, in fact, you need to know very little to find the underlying signature of a complex phenomenon. All you need is the evidence of the EGG, blood pressure, fluid in the lungs, and unstable angina.

That’s a radical statement. Take, for instance, the hypothetical case of a man who conies into the ER complaining of intermittent left-side chest pain that occasionally comes when he walks up the stairs and that lasts from five minutes to three hours. His chest exam, heart exam, and EGG are normal, and his systolic blood pressure is 165, meaning it doesn’t qualify as an urgent factor. But he’s in his sixties. He’s a hard-charging executive. He’s under constant pressure. He smokes. He doesn’t exercise. He’s had high blood pressure for years. He’s overweight. He had heart surgery two years ago. He’s sweating. It certainly seems like he ought to be admitted to the coronary care unit right away. But the algorithm says he shouldn’t be. All those extra factors certainly matter in the long term. The patient’s condition and diet and lifestyle put him at serious risk of developing heart disease over the next few years. It may even be that those factors play a very subtle and complex role in increasing the odds of something happening to him in the next seventy-two hours.

What Goldman’s algorithm indicates, though, is that the role of those other factors is so small in determining what is happening to the man right now that an accurate diagnosis can be made without them. In fact that extra information is more than useless. It’s harmful. It confuses the issues. What screws up doctors when they are trying to predict heart attacks is that they take too much information into account. The problem of too much information also conies up in studies of why doctors sometimes make the mistake of missing a heart attack entirely, of failing to recognise when someone is on the brink of or in the midst of a major cardiac complication. Physicians, it turns out, are more likely to make this kind of mistake with women and minorities. Why is that? Gender and race are not irrelevant considerations when it comes to heart problems; blacks have a different overall risk profile than whites, and women tend to have heart attacks much later in life than men. The problem arises when the additional information of gender and race is factored into a decision about an individual patient. It serves only to overwhelm the physician still further. Doctors would do better in these cases if they knew less about their patients, if, that is, they had no idea whether the people they were diagnosing were white or black, male or female.

It is no surprise that it has been so hard for Goldman to get his ideas accepted. It doesn’t seem to make sense that we can do better by ignoring what seems like perfectly valid information. “This is what opens the decision rule to criticism,” Reilly says. “This is precisely what docs don’t trust. They say, “This process must be more complicated than just looking at an EGG and asking these few questions. Why doesn’t this include whether the patient has diabetes? How old he is? Whether he’s had a heart attack before?’ These are obvious questions. They look at it and say, “This is nonsense, this is not how you make decisions.’” There is a kind of automatic tendency among physicians to believe that a life-or-death decision has to be a difficult decision. “Doctors think it’s mundane to follow guidelines,” he says. “It’s much more gratifying to come up with a decision on your own. Anyone can follow an algorithm. There is a tendency to say, ‘Well, certainly I can do better. It can’t be this simple and efficient; otherwise, why are they paying me so much money?’” The algorithm doesn’t feel right.

Healthcare Architecture Design Theory

I have also wondered through many years of doing healthcare architecture why people pay me so much money to do something I would do for nothing (if I couldn’t find a payer to pay me to do it!). Healthcare architecture (or any kind of design) is best done fast…in a “creative rush” so to speak. The design brief should be read late in the working day, towards evening and then left alone, home to dinner and music (avoid the TV for just one evening), early meal, get to bed before midnight. Brisk early morning walk, cold shower (don’t make the mistake of going to the office – nothing destroys incipient brilliant design like rush-hour traffic…) brush the breadcrumbs on the breakfast table aside, A2 paper and soft pencil and BLINK!

When your eyes are open again, you should see your hospital on that paper. OK, I’ll accept that’s exaggerated for dramatic effect, but you get the message. Sleep culls from the design brief only the information you need, refers all these important design imperatives to your stomach (…gut feel…), and all that remains is for you to get in touch with your stomach, it will show you the Way.

If I were to take a page out of Goldman’s book and try to compile Hussain’s “urgent design factors” (admittedly without the mathematics, computers or masses of data), but with the benefit of years of healthcare experience design, I would come up with: (1) secondary or tertiary level care (2) charitable or for-profit (3) total area/beds envisaged – to limit it to three, like him.

Listen to me: it’s not about the relationships between or within medical departments, it’s not about how many OT’s or whether we have to cater for an MRI or not. The first you’ll find in textbooks, the second hidden in the pages of your brief. Such information should not even be in your conscious mind at the instant of the above-mentioned blink! That kind of information I think of as clutter. Even better than storing it in the attic is to just throw it away.

There is a tendency among architects to think that it is very difficult to design a healthcare facility (as opposed to most other building types), because all they are seeing is the amount of “clutter” you need to accumulate to design one. But you’ll find the necessary clutter in the (attic…Neuferts Architect’s Data). OK, I’ll grant you it needs a certain amount of knowledge, but more importantly you need to (as Gladwell says) harness “the power of thinking without thinking.”

You need to know how to blink!

The author is Director-Design Services at Hosmac India Private Limited and can be contacted at hussain.varawalla@hosmac.com