Background

Health utilities express the perceptions patients have on the impact potential adverse events of medical treatments may have on their quality of life. Being able to accurately assess health utilities is crucial when deciding what is the best treatment when multiple and diverse treatment options exist, or when performing a cost / utility analysis. Due to the emotional and other complexities that may exist when such data are elicited, the values of the health utilities may be inaccurate and cause inconsistencies. Existing literature indicates that such inconsistencies may be very frequent. However, no method has been developed for dealing with such inconsistencies in an effective manner.

Methods

Given a set of health utilities, this paper first explores ways for determining if there are any inconsistencies in their values. It also proposes a number of quadratic optimization approaches to best estimate the actual (and hence unknown) values when a set of initial health utility values are provided by the patient and certain inconsistencies have been detected. This is achieved by readjusting the initial values in a way that is minimal and also satisfies certain consistency requirements.

Results

The proposed methods are applied on an illustrative example related to localized prostate cancer. Data from some published studies were used to illustrate how a set of initial values can be analyzed. This analysis aims at readjusting them in a minimal manner that would also satisfy some key numerical constraints pertinent to health utility values.

Conclusions

The numerical results and the computational complexities of the proposed models indicate that the proposed approaches are practical as they involve quadratic optimization modeling. These approaches are novel as the problem of addressing numerical inconsistencies in the elicitation process of health utilities has not been addressed adequately. The approaches are also critical in shared decision making and also when performing cost / utility analyses because health utilities play a central role in determining the quality-adjusted life years when making decisions in these healthcare domains.

中文翻译：

---

在为以患者为中心的决策制定健康状态效用值时，如何识别和处理数据不一致。

背景

卫生公用事业表达了患者对医疗潜在不良事件可能对其生活质量产生的影响的看法。当存在多种不同的治疗方案时，或在进行成本/效用分析时，在决定最佳治疗方法时，能够准确评估卫生效用至关重要。由于引出此类数据时可能存在的情绪和其他复杂性，健康公用事业的价值可能不准确并导致不一致。现有文献表明，这种不一致可能非常频繁。然而，尚未开发出以有效方式处理此类不一致的方法。

方法

给定一组健康实用程序，本文首先探讨了确定它们的值是否存在任何不一致的方法。它还提出了许多二次优化方法，以在患者提供一组初始健康效用值并且检测到某些不一致时最好地估计实际（因此未知）值。这是通过以最小的方式重新调整初始值并满足某些一致性要求来实现的。

结果

所提出的方法应用于与局部前列腺癌相关的说明性示例。一些已发表研究的数据用于说明如何分析一组初始值。该分析旨在以最小的方式重新调整它们，同时满足与健康效用值相关的一些关键数值约束。

结论

所提出模型的数值结果和计算复杂性表明所提出的方法是实用的，因为它们涉及二次优化建模。这些方法是新颖的，因为在卫生公用事业的启发过程中解决数值不一致的问题尚未得到充分解决。这些方法在共享决策以及执行成本/效用分析时也很重要，因为在这些医疗保健领域做出决策时，卫生公用事业在确定质量调整寿命年方面发挥着核心作用。