Your Medical Mind_ How to Decide What Is Right for You - Jerome Groopman [41]
A second method is termed the “time trade-off.” In this approach, you imagine how much you’d be willing to shorten your life in return for perfect health. In this case, Matt would be asked how many years of life he would give up to avoid impotence or incontinence. Using the years of life traded, a utility number is calculated.
A third approach is called the “standard gamble.” This method gauges how much risk you’re willing to take to avoid a side effect. For example, the doctor would ask Matt to imagine that a “magic pill” is newly arrived from a drug company. The magic medication will prevent a side effect (in this case impotence or incontinence) but is immediately fatal in some people. In Matt’s case, what odds would he need to take the gamble? If the pill prevents impotence in 99 percent of patients and is fatal in 1 percent, will he take it? What about 90/10 or 80/20? Once the last acceptable gamble is determined, the odds are used to calculate the utility number in Bernoulli’s formula.1 However, a wealth of recent research shows that putting a number on the utility or impact of living with a side effect is unreliable. First, current methods for assessing utility are not interchangeable. Numerous studies show that a single patient using the three different methods—the 0 to 100 scale, the time trade-off, the standard gamble—will often come up with different numbers for the same side effect. If all the methods accurately determined the impact of the side effect for that patient, each method should give the same number. Moreover, even the simple scale from 0 to 100 can vary—what is “perfect health”? For whom? For a sixty-year-old or a twenty-year-old? Does it mean you never have a headache or indigestion?
Second, the patient is asked to assess his or her life in the future under unfamiliar conditions. Imagining different scenarios based on written descriptions or listening to a doctor describe a condition cannot be grasped in the same way as actually living it. Dr. Peter Ubel, a professor at Duke University, who has extensively studied patients’ utility assessments, notes the “central problem with these methods . . . is that they require respondents [patients] to think about a health state they are not actually experiencing.” Even we, as physicians, who have cared for many people who developed side effects from treatments, can’t imagine what our lives would be like with those side effects.
For that reason, researchers have tried to get a more accurate assessment of utility by surveying patients who are currently living with a given side effect. In theory, the utility number provided by these patients could be used to guide decision making for those considering treatment options. But the experience of living with that side effect is not static or fixed. It can depend on the person’s emotions at the time he is asked. If you ask a patient when he is anxious or in pain to assign a utility number, and later ask him again when he is calm or comfortable, you can get very different answers. People also adapt to their changed life after treatment for a disorder. That adaptation can be highly individual and further fluctuate over time so that a person might score his or her life better, then worse, then better again. Over a period of weeks to months, studies show that patients with conditions as varied as coronary disease and breast cancer assigned values that fluctuated by as much as 50 percent.
We believe these findings argue that the effort to reduce medical decision making to numbers is misconceived and reductionist, overly simplifying a complex and vexing process that is fraught with conflict and emotion.
We live in a culture that looks increasingly to numbers for answers. Numbers communicate a sense of precision in the face of uncertainty. Matt Conlin relied on them in his decisions at work. He was determined to find the numbers that