13 research outputs found

    Disclosure and rationality: Comparative risk information and decision-making about prevention

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    With the growing focus on prevention in medicine, studies of how to describe risk have become increasing important. Recently, some researchers have argued against giving patients "comparative risk information," such as data about whether their baseline risk of developing a particular disease is above or below average. The concern is that giving patients this information will interfere with their consideration of more relevant data, such as the specific chance of getting the disease (the "personal risk"), the risk reduction the treatment provides, and any possible side effects. I explore this view and the theories of rationality that ground it, and I argue instead that comparative risk information can play a positive role in decision-making. The criticism of disclosing this sort of information to patients, I conclude, rests on a mistakenly narrow account of the goals of prevention and the nature of rational choice in medicine

    Comparison of Historical Data on Rounds to Medicine and Pediatrics Observations.

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    <p>*Category defined by <i>Elliot et al.</i> as “discussion of diseases not directly related to patient care” and <i>Miller et al.</i> as “topic presentations”.</p

    Generalized Estimating Equation for Association of Observed Characteristics of Rounds with Adjusted Bedside Minutes per Patient<sup>a</sup>.

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    a<p>Adjusted Bedside Minutes = √(bedside minutes/patient census), intercept 0.87.</p>b<p>ß = Slope of the regression line adjusted for each variable and adjusted bedside minutes, expressed per unit of each variable.</p>c<p>when compared to internal medicine.</p>d<p>when compared to “Institution A”.</p><p><b>Bold text</b> indicates significance of .05 or less.</p

    Mean Values for Team Composition, Patient load, and Duration of Location and Activities Observed on Rounds Vary by Specialty.

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    a<p>Unadjusted p-values calculated from a two group t-test.</p>b<p>adjusted p-values represent the Holm correction for multiple comparisons. All p-values are two-sided.</p><p><b>Bold text</b> indicates significance of .05 or less.</p><p>Grey box indicates no significance test was performed.</p
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