noted in the Preface, on Friday, March 7, I fell short of breath walking to the meeting at the State Department. I decided that I needed to visit my family doctor as soon as the weekend was over. On Saturday, three other runners in my club and I set out from my home with twenty pounds of flour to mark a five-mile trail that the rest of the runners would follow that afternoon. We were out for over two-and-a-half hours setting the trail. I was able to guide my colleagues on how best to set the course but was having difficulty carrying flour and could only walk, not run. That afternoon, over thirty runners showed up to run the course, socialize afterwards, and celebrate my sixty-fifth birthday.
On Monday, March 10, I went to see my family doctor. She took one look at me, asked a few questions, and told me to drive directly to an emergency room. On the morning of March 12, I underwent major surgery that saved my life.
The next three chapters document the lessons I learned from trying unsuccessfully for five years to get a diagnosis of my condition. My saga involved working with a dozen different doctors representing six different specialties and trying over a dozen different medications. In the process, I learned a lot about the state of medical practice in the United States and what can be done to improve your chances of surviving. If you want to cheat, you can jump to chapter five to learn what transpired at the hospital and afterward.
Five Techniques to Spur a Correct Diagnosis
During my five-year odyssey, I noticed a constant tension between the temptation for doctors to start treating the illness versus taking the necessary time to diagnose it. Usually, the default was to treat. In general, this strategy usually turns out to be successful because of the following:
1.In a high percentage of cases, the human body will eventually cure itself. If you visit the doctor, a treatment is usually prescribed, but, at best, it may only be expediting the recovery process.
2.Most illnesses can be treated successfully with just one or two treatments.
But what if the problem is more complicated? Given such strong incentives to treat and not diagnose, many of us who have unusual and hard-to-diagnose conditions become frustrated. Our lives become littered with unending visits to doctors’ offices, myriads of tests, and a series of unsuccessful treatments. If we die, no one usually will notice that our illnesses were undiagnosed. Our families are grieving; they already knew there was a problem and usually feel impelled to just move on.
What tools or techniques are available to this minority of undiagnosed patients, whom I call the forgotten “5 percent?” How can they get the attention they deserve? This chapter presents six Structured Analytic Techniques (SATs) they can employ to focus more attention on the need for a diagnosis.2 It describes when the techniques are most useful, what cognitive biases they help to correct, and how they were—or could have been—used in my case. The book also contains examples of how these SATs were used correctly with good results, as well as examples when they were not applied—with serious negative consequences for the patient.
SATs were developed in the late 1990s to provide more rigorous, transparent, and collaborative methods for analyzing a problem, resolving differences, innovating solutions, and anticipating the future. The techniques have proven highly effective in supporting the analytic process in the intelligence community as well as in the corporate world.3 They are a subset of a variety of practices in the intelligence community that can—and have been—adapted to the medical profession to reduce errors and improve the quality of health care (see Figure 6).
SATs came into prominence following the terrorist attacks on September 11, 2001, and the flawed 2002 National Intelligence Estimate on weapons of mass destruction in Iraq as a way to improve the overall quality of analysis in the US Intelligence Community. Over the years, use of the techniques has spread to other parts of the US government, foreign intelligence services, major corporations, and academia.
The techniques have universal value and utility. Analysis of Competing Hypotheses (ACH), for example, is similar to differential diagnosis in the medical profession.
The following key practices or concepts in intelligence analysis have the potential to help medical professionals reduce error rates:
• Recognize how mental mindsets and past experiences can bias a diagnosis (Cognitive Bias and Intuitive Traps).
• Develop more than one explanation for an illness during the initial diagnosis (Multiple Hypothesis Generation).
• Challenge preconceived notions generated by a patient’s appearance, age, or race (Key Assumptions Check).
• Focus on disconfirming evidence to quickly eliminate incorrect diagnoses (Analysis of Competing Hypotheses).
• Seek out and value the opinions of others working the case (Coordination and Peer Review).
• Know when to expect deception (Deception Detection).
Figure 6. Intelligence Tradecraft for Medicine
In this chapter, we discuss how you can leverage five SATs to gain more knowledge about your condition while helping your doctor make a correct diagnosis. The six techniques are:
1.Multiple Hypothesis Generation
2.Analysis of Competing Hypotheses
3.Indicators Generation
4.Key Assumptions Check
5.Premortem Analysis
6.Structured Self-Critique
Step-by-step instructions on how to use these techniques can be found in Appendices A-F which contain additional information on when to use them, the value added, their relationship to other techniques, and potential pitfalls to avoid.4
Multiple Hypothesis Generation: What Is the Range of Explanations for My Condition?
Instead of telling you X is the problem, let’s explore several options.
In his book, How Doctors Think, Dr. Jerome Groopman argues that the practice of considering alternative explanations for a medical problem is one of the strongest safeguards against making cognitive errors.5 He quotes one of his colleagues as saying, “I learned to always hold back [and avoid jumping to a conclusion], to make sure that, even when I think I have the answer, to generate a short list of alternatives.”
Multiple Hypothesis Generation is a technique for generating multiple alternatives for explaining a particular issue, activity, or behavior. It is a key technique in the analyst’s toolkit and is particularly useful when many factors are involved, a high degree of uncertainty exists regarding the diagnosis, and your doctors and/or nurses hold different views.
The technique helps you, your family, and your doctors avoid—or at least mitigate the power of—several analytic traps, including:
• Coming to premature closure.
• Being overly influenced by first impressions.
• Seizing on the first diagnosis or procedure that looks “good enough.”
• Focusing
