Development of a Decision-Analytic Methodology for Definition of Standards of Disclosure

法律和医学交叉的最关键领域之一是医疗知情同意。从科学的角度来看，对于应该向患者披露哪些信息以增强他们做出知情决定的能力，人们知之甚少。无论是在理论上还是在方法上，都需要一种基于分析的方法来实现这种决策。Fischhoff博士和他的同事们正在寻求开发一种适用于医生确保患者知情同意的法律义务的披露方法。他们的工作旨在对患者可能的健康结果评估中的变化进行量化建模。这项研究借鉴了一种新的技术，即在模型的蒙特卡罗模拟中，使用Logistic回归来解释输入信息对决策变化的变量贡献。这种方法将产生客观的、“合理的”主观差异范围。这些目标值随后将被应用于几个医疗程序的决策分析建模。这项研究有望取得重大进展。它将显示分析的优势和局限性，并允许在医疗法律环境中进一步开发、推广和实施这一方法。此外，它也是审查法律如何适应专业披露做法背后的量化分析的重要先导。

One of the most critical areas where law and medicine intersect is on medical informed consent. From a scientific standpoint little is known about the range of information that should be disclosed to patients to enhance their ability to make an informed decision. Both theoretically and methodologically, there is need for an analytically based approach to enable such decisionmaking. Dr. Fischhoff and his colleagues are seeking to develop such an approach to disclosure that is applicable to physicians' legal obligations to insure informed consent from patients. Their work aims to model quantitatively the variation in evaluations of possible health outcomes of patients. The research draws on a new technique whereby logistic regression is used to explain the variable contribution of input information to decision variation in a Monte Carlo simulation of a model. This method will produce an objective, "reasonable" range of subjective differences. These objective values will then be applied in a decision analysis modeling of several medical procedures. This study promises important advances. It will show the strengths and limitations of the analysis and permit the further development, generalization, and implementation of this approach within the medical-legal setting. Also, it is an essential precursor to examining the ways in which the law can accommodate quantitative analyses underlying professional disclosure practices.