Your Medical Mind_ How to Decide What Is Right for You - Jerome Groopman [117]
Despite these significant limitations, many treatment guidelines rely on preference calculations using time trade-off and standard gamble. And the severe flaws in the methods do not stop different therapies from being prioritized as superior or inferior or, in some settings, paid for or denied coverage: Paul Dolan, “Developing methods that really do value the ‘Q’ in the QALY,” Health Economics, Policy and Law 3 (2008), pp. 69–77; Paul Dolan, “In defense of subjective well-being,” Health Economics, Policy and Law 3 (2008), pp. 93–95. A defense of QALYs that we find unconvincing: Peter J. Neumann, “What next for QALYs?” JAMA (commentary) 305 (2011), pp. 1806–1807.
Some researchers are trying to develop metrics for the quality of physician decision making rather than relying on the current metrics for quality care: Karen R. Sepucha et al., “Developing instruments to measure the quality of decisions: Early results for a set of symptom-driven decisions,” Patient Education and Counseling 73 (2008), pp. 504–510.
100 To learn more about the differences in how patients and physicians assess side effects, see Arthur S. Elstein et al., “Agreement between prostate cancer patients and their clinicians about utilities and attribute importance,” Health Expectations 7 (2004), pp. 115–125; and Gretchen B. Chapman et al., “Prostate cancer patients’ utilities for health states: How it looks depends on where you stand,” Med Decis Making 18 (1998), pp. 278–286.
106 See note for page 91 above.
107 Barry Schwartz, a professor of psychology at Swarthmore College, noted in his book The Paradox of Choice (New York: Harper Perennial, 2005) that when the choice set is large, people are more likely to regret a decision that does not turn out well. They may, in his words, “stew” about the options not taken and have overinflated their expectations about the chosen option in advance. See also Schwartz, “Tyranny of choice,” Scientific American 290 (April 2004).
109 Daniel Gilbert’s experiment with Harvard undergraduates asked one very interesting question: Will people more reliably forecast their experience of some future condition by reading a hypothetical scenario or by speaking with individuals who are similar to them and have already experienced it? In a series of such experiments, Gilbert found that reaction to reading the description of the experience did not predict how the students would experience it. But when a student spoke with another student of what it was like to experience the condition, then the prediction was more accurate: Daniel T. Gilbert et al., “The surprising power of neighborly advice,” Science 323 (2009), pp. 1617–1619, and supplemental material online. This research prompts us to seek people who seem similar to ourselves and to listen to their tales of what it was like to undergo a treatment or experience an illness. This is a more refined approach to extracting knowledge than from random anecdotes and testimonials on the Internet.
111 Among healthy people, misprediction of life with a certain clinical condition may occur because of (1) a focusing illusion; for instance, when imagining a colostomy, people focus narrowly on the plastic pouches and the perils of wearing bathing suits at the beach without considering life domains unaffected by a colostomy; and (2) an underestimation of adaptation, in that people fail to consider how and why emotions are likely to change over time following the onset of an illness or disability.
111 For example, Peter Ubel and others studied 195 patients who had received a colostomy at the University of Michigan over the prior ten years. Approximately half of the patients surveyed had had their colostomy reversed. Across a wide range of quality-of-life and mood measures, they found no significant differences