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Although screening programs for neural tube defects (NTDs) are routine and cost-effective in Great Britain their potential use in the United States has been hotly debated. In this chapter we report the attitudes of 338 prospective patients seeking genetic counseling about the use of amniocentesis for prenatal diagnosis. We have integrated these attitudes with the expected accuracy and complications of a comprehensive screening program for NTDs and have estimated the proportion of these prospective parents who would benefit from a maternal serum alpha-fetoprotein (AFP) screening program. Thus, we have addressed perhaps the most critical problem related to the decision of whether or not to institute an AFP screening program: “What are the implications of the attitudes of prospective parents toward the desirability of a large-scale screening program for the prenatal detection of NTDs?” In a larger sense, we are addressing a prototypical problem for many policy analyses: How can the personal attitudes of individual members of society be integrated into decisions affecting the medical care of society as a whole?
METHODS
Summary of screening plan. Figure 28.1 summarizes the policies analyzed in this paper. Maternal serum AFP concentration is measured at a gestational age between 16 and 18 weeks. If the concentration of AFP is above a predetermined level (typically either 2.5 times the median or two standard deviations above the mean), the serum test is repeated.
DISCUSSION OUTLINE: DESCRIPTIVE/PRESCRIPTIVE/NORMATIVE INTERACTIONS IN MEDICAL DECISION MAKING
Issues relating to values and preferences
Valued consequences that are typically reflected in formal models of medical decision making include the following:
survival (length of life)
quality of life
symptoms
physical function
social function
Are preferences regarding these attributes fixed or labile? How do they change with age, physical status, mental status, interactions with physicians? Prescriptively or normatively, how does one deal with the existence of “multiple selves”? Is the prescriptive solution more complicated than just trying to assess the uncertainty about future preferences, and then take expectations across all possible future utility functions? If perfectly or imperfectly knowable, should future preferences substitute for present preferences in decisions with future consequences?
Examples: labor and anesthesia (Christensen–Szalanski)
smoking and addictive behaviors
myopia, ignorance, or uncertainty about old age
euthanasia (Schelling)
Are some preference functions normatively “better” than others? When is it appropriate for the physician to intervene to try to change patients' preferences?
What are the ethical implications for informed consent?
Example: a couple's desire to have a baby at home, under the care of a midwife
Issues in assessing utilities for health outcomes: Assuming that preferences are stable and measurable, what is the best way to measure them? While proper von Neumann–Morgenstern utility functions may be the prescriptive goal, are there other means to that end that are more reliable or acceptable than using lottery techniques, e.g., category scaling, magnitude estimation? […]
The analysis of medical practice as a decision-making process underscores the proposition that the choice of a therapy should reflect not only the knowledge and experience of the physician but also the values and the attitudes of the patient (McNeil, Weischselbaum, and Pauker, 1981). But if patients are to play an active role in medical decision making – beyond passive informed consent – we must find methods for presenting patients with the relevant data and devise procedures for eliciting their preferences among the available treatments. However, the elicitation of preferences, for both patients and physicians, presents a more serious problem than one might expect. Recent studies of judgment and choice have demonstrated that intuitive evaluations of probabilistic data are prone to widespread biases (Kahneman, Slovic, and Tversky, 1982), and that the preference between options is readily influenced by the formulation of the problem (Tversky and Kahneman, 1986).
In a public health problem concerning the response to an epidemic, for example, people prefer a risk-averse strategy when the outcomes are framed in terms of the number of lives saved and a risk-seeking strategy when the same outcomes are framed in terms of the number of lives lost. The tendency to make risk-averse choices in the domain of gains and risk-seeking choices in the domain of losses is a pervasive phenomenon that is attributable to an S-shaped value (or utility) function, with an inflection at one's reference point (Kahneman and Tversky, 1979, 1984).
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