CHAPTER 1
Introduction

• 1.1 How may I be thorough yet efficient when considering the possible causes of my patient’s problems?
• 1.2 How do I characterize the information I have gathered during the medical interview and physical examination?
• 1.3 How do I interpret new diagnostic information?
• 1.4 How do I select the appropriate diagnostic test?
• 1.5 How do I choose among several risky treatment alternatives?

“Proof,” I said, “is always a relative thing. It’s an overwhelming balance of probabilities. And that’s a matter of how they strike you.”

(Raymond Chandler in Farewell, My Lovely, 1940)

Thoughtful clinicians ask themselves many difficult questions during the course of taking care of patients. Some of these questions are as follows:

• How may I be thorough yet efficient when considering the possible causes of my patient's problem?
• How do I characterize the information I have gathered during the medical interview and physical examination?
• How should I interpret new diagnostic information?
• How do I select the appropriate diagnostic test?
• How do I choose among several risky treatments?

The goal of this book is to help clinicians answer these important questions.

The first question is addressed with observations from expert clinicians “thinking out loud” as they work their way through a clinical problem. The last four are addressed from the perspective of medical decision analysis, a quantitative approach to medical decision making.

The goal of this introductory chapter is to preview the contents of the book by sketching out preliminary answers to these five questions.

1.1 How may I be thorough yet efficient when considering the possible causes of my patient's problems?

Trying to be efficient in thinking about the possible causes of a patient's problem often conflicts with being thorough. This conflict has no single solution. However, much may be learned about medical problem‐solving by listening to expert diagnosticians discuss how they reasoned their way through a case. Because the single most powerful predictor of skill in diagnosis is exposure to patients, the best advice is “see lots of patients and learn from your mistakes.” How to be thorough, yet efficient, when thinking about the possible causes of a patient's problem is the topic of Chapter 2.

1.2 How do I characterize the information I have gathered during the medical interview and physical examination?

The first step toward understanding how to characterize the information one gathers from the medical interview and physical examination is to realize that information provided by the patient and by diagnostic tests usually does not reveal the patient's true state. A patient's signs, symptoms, and diagnostic test results are usually representative of more than one disease. Therefore, distinguishing among the possibilities with absolute certainty is not possible. A 60‐year‐old man's history of chest pain illustrates this point.

Mr. Costin, a 60‐year‐old bank executive, walks into the emergency room complaining of intermittent substernal chest pain that is “squeezing” in character. The chest pain is occasionally brought on by exertion but usually occurs without provocation. When it occurs, the patient lies down for a few minutes, and the pain usually subsides in about 5 minutes. It never lasts more than 10 minutes. Until these episodes of chest pain began 3 weeks ago, the patient had been in good health, except for intermittent problems with heartburn after a heavy meal.

Although there are at least 60 causes of chest pain, Mr. Costin's medical history narrows down the diagnostic possibilities considerably. Based on his history, the two most likely causes of Mr. Costin's chest pain are coronary artery disease or esophageal disease.

However, the cause of Mr. Costin's illness is uncertain. This uncertainty is not a shortcoming of the clinician who gathered the information; rather, it reflects the uncertainty inherent in the information provided by Mr. Costin. Like most patients, his true disease state is hidden within his body and must be inferred from imperfect external clues.

How do clinicians usually characterize the uncertainty inherent in medical information? Most clinicians use words such as “probably” or “possibly” to characterize this uncertainty. However, most of these words are imprecise, as seen as we hear more about Mr. Costin's story:

The physician who sees Mr. Costin in the emergency room tells Mr. Costin, “I cannot rule out coronary artery disease. The next step in the diagnostic process is to examine the results of a stress ECG.” She also says, “I cannot rule esophageal disease either. If the stress ECG is negative, we will work you up for esophageal disease.”

Mr. Costin is very concerned about his condition and seeks a second opinion. The second physician who sees Mr. Costin agrees that coronary artery disease and esophageal disease are the most likely diagnoses. He tells Mr. Costin, “Coronary artery disease is a likely diagnosis, but to know for certain we'll have to see the results of a stress ECG.” Concerning esophageal disease, he says, “We cannot rule out esophageal disease at this point. If the stress ECG is normal, and you don't begin to feel better, we'll work you up for esophageal disease.”

Mr. Costin feels reassured that both clinicians seem to agree on the possibility of esophageal disease, since both have said that they cannot rule out esophageal disease. However, Mr. Costin cannot reconcile the different statements concerning the likelihood that he has coronary artery disease. Recall that the first clinician said “coronary artery disease can't be ruled out,” whereas the second clinician stated, “coronary artery disease is a likely diagnosis.” Mr. Costin wants to know the difference between these two different opinions. Mr. Costin explains his confusion to the second clinician and asks him to speak to the first clinician.

The two clinicians confer by telephone. Although they expressed the likelihood of coronary artery disease differently when they talked with Mr. Costin, it turns out that they had similar ideas about the likelihood that he has coronary artery disease. Both believe that about one patient out of three with Mr. Costin's history has coronary artery disease.

From this episode, Mr. Costin learns that clinicians may choose different words to express the same judgment about the likelihood of an uncertain event.

To Mr. Costin's surprise, the clinicians have different opinions about the likelihood of esophageal disease, despite the fact that both described its likelihood with the same phrase, “esophageal disease can't be ruled out.” The first clinician believes that among patients with Mr. Costin's symptoms, only one patient in ten would have esophageal disease. However, the second clinician thinks that as many as one patient in two would have esophageal disease.

Mr. Costin is chagrined that both clinicians used the same phrase, “can't be ruled out,” to describe two different likelihoods. Mr. Costin learns that clinicians commonly use the same words to express different judgments about the likelihood of an event.

The solution to the confusion that can occur when using words to characterize uncertainty with words is to use a number: a probability. Probability expresses uncertainty precisely because it is the likelihood that a condition is present or will occur in the future. When one clinician believes the probability that a patient has coronary artery disease is 1 in 10, and the other clinician thinks that it is 1 in 2, the two know that they disagree and that they must talk about why their interpretations are so disparate. The precision of numbers to express uncertainty is illustrated graphically by the scale in Figure 1.1. On this scale, uncertain events are expressed with numbers between 0 and 1.

Figure 1.1 A scale for expressing uncertainty.

Figure 1.2 A clinician can visualize the level of certainty about a disease hypothesis on a probability scale. Thirty‐three is marked on this certainty scale to correspond to a clinician’s initial probability estimate that Mr. Costin had coronary artery disease.

To understand the meaning of probability in medicine, think of it as a fraction. For example, the word “one‐third” means 33 out of a group of 100. In medicine, if a clinician states that the probability that a disease is present is 33%, it means that the clinician believes that if they see 100 patients with the same findings, 33 of them will have the disease in question (Figure 1.2).

Although probability has a precise mathematical meaning, a probability estimate need not correspond to a physical reality, such as the prevalence of disease in a defined group of patients. We define probability in medicine as a number between zero and 1 that expresses a clinician’s opinion about the likelihood of a condition being present or occurring in the future. The probability of an event a clinician believes is...