The Checklist Manifesto_ How to Get Things Right - Atul Gawande [19]
But they presumably have limits, as well. So a key step is to identify which kinds of situations checklists can help with and which ones they can’t.
Two professors who study the science of complexity—Brenda Zimmerman of York University and Sholom Glouberman of the University of Toronto—have proposed a distinction among three different kinds of problems in the world: the simple, the complicated, and the complex. Simple problems, they note, are ones like baking a cake from a mix. There is a recipe. Sometimes there are a few basic techniques to learn. But once these are mastered, following the recipe brings a high likelihood of success.
Complicated problems are ones like sending a rocket to the moon. They can sometimes be broken down into a series of simple problems. But there is no straightforward recipe. Success frequently requires multiple people, often multiple teams, and specialized expertise. Unanticipated difficulties are frequent. Timing and coordination become serious concerns.
Complex problems are ones like raising a child. Once you learn how to send a rocket to the moon, you can repeat the process with other rockets and perfect it. One rocket is like another rocket. But not so with raising a child, the professors point out. Every child is unique. Although raising one child may provide experience, it does not guarantee success with the next child. Expertise is valuable but most certainly not sufficient. Indeed, the next child may require an entirely different approach from the previous one. And this brings up another feature of complex problems: their outcomes remain highly uncertain. Yet we all know that it is possible to raise a child well. It’s complex, that’s all.
Thinking about averting plane crashes in 1935, or stopping infections of central lines in 2003, or rescuing drowning victims today, I realized that the key problem in each instance was essentially a simple one, despite the number of contributing factors. One needed only to focus attention on the rudder and elevator controls in the first case, to maintain sterility in the second, and to be prepared for cardiac bypass in the third. All were amenable, as a result, to what engineers call “forcing functions”: relatively straightforward solutions that force the necessary behavior—solutions like checklists.
We are besieged by simple problems. In medicine, these are the failures to don a mask when putting in a central line or to recall that one of the ten causes of a flat-line cardiac arrest is a potassium overdose. In legal practice, these are the failures to remember all the critical avenues of defense in a tax fraud case or simply the various court deadlines. In police work, these are the failures to conduct an eyewitness lineup properly, forgetting to tell the witness that the perpetrator of the crime may not be in the lineup, for instance, or having someone present who knows which one the suspect is. Checklists can provide protection against such elementary errors.
Much of the most critical work people do, however, is not so simple. Putting in a central line is just one of the 178 tasks an ICU team must coordinate and execute in a day—ICU work is complicated—and are we really going to be able to create and follow checklists for every possible one of them? Is this even remotely practical? There is no straightforward recipe for the care of ICU patients. It requires multiple practitioners orchestrating different combinations of tasks for different conditions—matters that cannot be controlled by simple forcing functions.
Plus, people are individual in ways that rockets are not—they are complex. No two pneumonia patients are identical. Even with the same bacteria, the same cough and shortness of breath, the same low oxygen levels, the same antibiotic, one patient might get better and the other might not. A doctor