Choices, Chances, Values Stephen K. Plume, MD Section of Cardiothoracic Surgery, Dartmouth Medical School, Hanover, New Hampshire
e surgeons can improve our clinical decisions. To do so, we will need to understand that we are overconfident about the quality of our intuitive judgments, and we will have to become comfortable with a vocabulary that is unfamiliar to most of us. Surgeons are subject to the same limitations in the way the human mind works that affect everyone else. Regardless of effort, exhortation, or training, none of us can keep more than a handful of variables in conscious attention at once; none of us can resist being disproportionately influenced by our most recent, most salient, most familiar experiences; none of us can intuitively estimate probabilities accurately. We make substantively complex judgments as if they were simple, because we attend to only a few variables when we decide. The clues we attend to are not always the most important factors. The language in which we discuss likelihood is imprecise: "rare" means to one physician what "frequent" means to another, if our estimates are calibrated on a numerical scale [l].We do not reliably come to an intuitive decision that is internally See also page 493.
consistent with our own estimates of the probabilities of important outcomes. Few of us understand that an explicit decision rule, even a simple one, outperforms clinical judgment. Expert opinion, even of august consensus panels, is no substitute. These assertions may be unwelcome, but the research on which they are based is solid. The compendia edited by Kahneman, Slovic, and Tversky [2] and by Arkes and Hammond [3] are excellent guides to the primary data. What is new to surgeons is our slowly growing recognition that the implications of such research apply to real people, real problems, and real costs, whether measured as human suffering or as resource consumption. In this issue of The Annals, Olak and Detsky [4]propose a decision analysis model for addressing an interesting, controversial, clinically important issue. Whether the elements of their model, or the data on which they depend for estimates of probability, or their method for assigning utilities are correct are discussions well worth having in their own right. The point of this editorial is to emphasize that because each decision is a synthesis of choices (options we choose among), chances (likelihoods of particular outcomes associated with each choice), and values (cost or quality or desirability of the possible outcomes), and because none of us can simultaneously integrate all this information, we can, as Olak and Detsky demonAddress reprint requests to Dr Plume, Section of Cardiothoracic Surgery, Dartmouth-HitchcockMedical Center, Lebanon, NH 03756.
0 1992 by The Society of Thoracic Surgeons
strate, exploit a technique that allows us to bring our best efforts to bear on manageable segments of the problem, one at a time. A computer (or we, if we have the patience to do the arithmetic) can carry out the computationally trivial task which, despite its triviality, is beyond the capacity of unaided human intuition: reliably to identify the best option that is logically consistent with our own beliefs. Adding sensitivity analysis to the decision model lets us test how robust the choice is if we make different assumptions about chances or values. Some have worried that use of quantitative analytical methods diminishes the "art" of medicine. I cannot reconcile (a) rejection of techniques that demonstrably improve our ability to make good decisions with (b) our commitment to reducing the impact of human illness. The need to make decisions in the face of uncertainty is a fact of life that is especially poignant for surgeons. Our judgment and skill are brought into question by realities like obstructions, leaks, infections, prolonged lengths of stay, hospital mortalities, and hosts of other measures. We are tempted to look back from adverse outcomes with a presumption that something should have been done differently [5, 61. Quantitative, probabilistic analysis can identify the best decision available to us, given what we believe at the time. Whatever the consequence (because no one can guarantee a particular outcome), we can defend the rationality of our choice. Breaking decision problems into components helps us to think more clearly about them, and helps identify areas for research, so that we can set out to make the chances of obtaining a good outcome different from what they are today. Choices, chances, values. We can do better.
References 1. Bryant GD, Norman GR. Expressions of probability: words and numbers [Letter]. N Engl J Med 1980;302:411. 2. Kahneman D, Slovic P, Tversky A, eds. Judgment under uncertainty: heuristics and biases. Cambridge: Cambridge University Press, 1983. 3. Arkes HR, Hammond KR, eds. Judgment and decision making: an interdisciplinary reader. Cambridge: Cambridge University Press, 1986. 4. Olak J, Detsky A. Surgical decision analysis: esophagectomy/ esophagogastrectomy with or without drainage? Ann Thorac Surg 1992;53:493-7. 5. Fischoff B. For those condemned to study the past: reflections on historical judgment. In: Shweder RA, Fiske DW, eds. New directions for methodology of behavioral science: fallible judgment in behavioral research. San Francisco:Jossey-Bass, 1980. 6. Caplan RA, Posner KL, Cheney FW. Effect of outcome on physician judgments of appropriateness of care. JAMA 1991; 265:1957-60.
Ann Thorac Surg 1992;53:373
0003-4975/92/$5.00
e surgeons can improve our clinical decisions. To do so, we will need to understand that we are overconfident about the quality of our intuitive judgments, and we will have to become comfortable with a vocabulary that is unfamiliar to most of us. Surgeons are subject to the same limitations in the way the human mind works that affect everyone else. Regardless of effort, exhortation, or training, none of us can keep more than a handful of variables in conscious attention at once; none of us can resist being disproportionately influenced by our most recent, most salient, most familiar experiences; none of us can intuitively estimate probabilities accurately. We make substantively complex judgments as if they were simple, because we attend to only a few variables when we decide. The clues we attend to are not always the most important factors. The language in which we discuss likelihood is imprecise: "rare" means to one physician what "frequent" means to another, if our estimates are calibrated on a numerical scale [l].We do not reliably come to an intuitive decision that is internally See also page 493.
consistent with our own estimates of the probabilities of important outcomes. Few of us understand that an explicit decision rule, even a simple one, outperforms clinical judgment. Expert opinion, even of august consensus panels, is no substitute. These assertions may be unwelcome, but the research on which they are based is solid. The compendia edited by Kahneman, Slovic, and Tversky [2] and by Arkes and Hammond [3] are excellent guides to the primary data. What is new to surgeons is our slowly growing recognition that the implications of such research apply to real people, real problems, and real costs, whether measured as human suffering or as resource consumption. In this issue of The Annals, Olak and Detsky [4]propose a decision analysis model for addressing an interesting, controversial, clinically important issue. Whether the elements of their model, or the data on which they depend for estimates of probability, or their method for assigning utilities are correct are discussions well worth having in their own right. The point of this editorial is to emphasize that because each decision is a synthesis of choices (options we choose among), chances (likelihoods of particular outcomes associated with each choice), and values (cost or quality or desirability of the possible outcomes), and because none of us can simultaneously integrate all this information, we can, as Olak and Detsky demonAddress reprint requests to Dr Plume, Section of Cardiothoracic Surgery, Dartmouth-HitchcockMedical Center, Lebanon, NH 03756.
0 1992 by The Society of Thoracic Surgeons
strate, exploit a technique that allows us to bring our best efforts to bear on manageable segments of the problem, one at a time. A computer (or we, if we have the patience to do the arithmetic) can carry out the computationally trivial task which, despite its triviality, is beyond the capacity of unaided human intuition: reliably to identify the best option that is logically consistent with our own beliefs. Adding sensitivity analysis to the decision model lets us test how robust the choice is if we make different assumptions about chances or values. Some have worried that use of quantitative analytical methods diminishes the "art" of medicine. I cannot reconcile (a) rejection of techniques that demonstrably improve our ability to make good decisions with (b) our commitment to reducing the impact of human illness. The need to make decisions in the face of uncertainty is a fact of life that is especially poignant for surgeons. Our judgment and skill are brought into question by realities like obstructions, leaks, infections, prolonged lengths of stay, hospital mortalities, and hosts of other measures. We are tempted to look back from adverse outcomes with a presumption that something should have been done differently [5, 61. Quantitative, probabilistic analysis can identify the best decision available to us, given what we believe at the time. Whatever the consequence (because no one can guarantee a particular outcome), we can defend the rationality of our choice. Breaking decision problems into components helps us to think more clearly about them, and helps identify areas for research, so that we can set out to make the chances of obtaining a good outcome different from what they are today. Choices, chances, values. We can do better.
References 1. Bryant GD, Norman GR. Expressions of probability: words and numbers [Letter]. N Engl J Med 1980;302:411. 2. Kahneman D, Slovic P, Tversky A, eds. Judgment under uncertainty: heuristics and biases. Cambridge: Cambridge University Press, 1983. 3. Arkes HR, Hammond KR, eds. Judgment and decision making: an interdisciplinary reader. Cambridge: Cambridge University Press, 1986. 4. Olak J, Detsky A. Surgical decision analysis: esophagectomy/ esophagogastrectomy with or without drainage? Ann Thorac Surg 1992;53:493-7. 5. Fischoff B. For those condemned to study the past: reflections on historical judgment. In: Shweder RA, Fiske DW, eds. New directions for methodology of behavioral science: fallible judgment in behavioral research. San Francisco:Jossey-Bass, 1980. 6. Caplan RA, Posner KL, Cheney FW. Effect of outcome on physician judgments of appropriateness of care. JAMA 1991; 265:1957-60.
Ann Thorac Surg 1992;53:373
0003-4975/92/$5.00
