Health State Utility Values: The Implications of Patient versus Community Ratings in Assessing the Value of Care.

IF 3.1 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES
Medical Decision Making Pub Date : 2025-05-01 Epub Date: 2025-03-22 DOI:10.1177/0272989X251326600
Risha Gidwani, Katherine W Saylor, Louise B Russell
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引用次数: 0

Abstract

BackgroundHealth-state utility values (HSUVs) are key inputs into cost-utility analyses. There is debate over whether they are best derived from the community or patients, with concerns raised that community-derived preferences may devalue benefits to ill, elderly, or disabled individuals. This tutorial compares the effects of using patient-derived HSUVs versus community-derived HSUVs on incremental cost-effectiveness ratios (ICERs) and shows their implications for policy.DesignWe review published studies that compared HSUVs derived from patients and the community. We then present equations for the gains in quality-adjusted life-years (QALYs) that would be estimated for an intervention using patient versus community HSUVs and discuss the implications of those QALY gains. We present a numerical example as another way of showing how ICERs change when using patient versus community HSUVs.ResultsPatient HSUVs are generally higher than community HSUVs for severe health states. When an intervention reduces mortality, patient ratings yield more favorable ICERs than do community ratings. However, when the intervention reduces morbidity, patient ratings yield less favorable ICERs. For interventions that reduce both morbidity and mortality, the effect on ICERs of patient versus community HSUVs depends on the relative contribution of each to the resulting QALYs.ConclusionsThe use of patient HSUVs does not consistently favor treatments directed at those patients. Rather, the effect depends on whether the intervention reduces mortality, morbidity, or both. Since most interventions do both, using patient HSUVs has mixed implications for promoting investments for people with illness and disabilities. A nuanced discussion of these issues is necessary to ensure that policy matches the intent of the decision makers.HighlightsThe debate about whether health state utility values (HSUVs) are best derived from patients or the community rests in part on the presumption that using community values devalues interventions for disabled persons or those with chronic diseases.However, we show why the effect of using patient HSUVs depends on whether the intervention in question primarily reduces mortality or morbidity or has substantial effects on both.If the intervention reduces mortality, using patient HSUVs will make the intervention appear more cost-effective than using community HSUVs, but if it reduces morbidity, using patient HSUVs will make the intervention appear less cost-effective.If the intervention reduces both morbidity and mortality, a common situation, the effect of patient versus community HSUVs depends on the relative magnitudes of the gains in quality and length of life.

健康状态效用值:评估护理价值时患者与社区评分的含义。
健康状态效用值(hsuv)是成本效用分析的关键输入。关于他们是来自社区还是来自患者的最佳选择存在争议,人们担心来自社区的偏好可能会降低对病人、老年人或残疾人的好处。本教程比较了使用患者衍生的hsuv和使用社区衍生的hsuv对增量成本效益比(ICERs)的影响,并展示了它们对政策的影响。我们回顾了已发表的比较患者和社区hsuv的研究。然后,我们提出了质量调整生命年(QALYs)收益的公式,该公式将用于使用患者与社区hsuv进行干预的估计,并讨论了这些质量调整生命年收益的含义。我们提供了一个数值示例,作为另一种方式来显示使用患者和社区hsuv时ICERs如何变化。结果严重健康状态患者hsuv总体高于社区hsuv。当干预措施降低死亡率时,患者评分比社区评分产生更有利的ICERs。然而,当干预降低发病率时,患者评分产生的icer较差。对于降低发病率和死亡率的干预措施,患者与社区hsuv对ICERs的影响取决于两者对最终质量年的相对贡献。结论患者hsuv的使用并不总是有利于针对这些患者的治疗。相反,效果取决于干预是否降低死亡率,发病率,或两者兼而有之。由于大多数干预措施兼而有之,使用病人专用suv对于促进对疾病和残疾人的投资具有复杂的影响。有必要对这些问题进行细致入微的讨论,以确保政策符合决策者的意图。关于健康状态效用值(hsuv)是最好从患者还是从社区获得的争论部分基于这样一种假设,即使用社区价值降低了对残疾人或慢性病患者的干预措施的价值。然而,我们展示了为什么使用患者hsuv的效果取决于所讨论的干预是否主要降低死亡率或发病率,或者对两者都有实质性影响。如果干预降低了死亡率,使用患者专用suv将使干预看起来比使用社区专用suv更具成本效益,但如果降低了发病率,使用患者专用suv将使干预看起来成本效益较低。如果干预降低了发病率和死亡率,这是一种常见的情况,那么患者与社区hsuv的效果取决于在质量和生命长度方面获得的相对程度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Medical Decision Making
Medical Decision Making 医学-卫生保健
CiteScore
6.50
自引率
5.60%
发文量
146
审稿时长
6-12 weeks
期刊介绍: Medical Decision Making offers rigorous and systematic approaches to decision making that are designed to improve the health and clinical care of individuals and to assist with health care policy development. Using the fundamentals of decision analysis and theory, economic evaluation, and evidence based quality assessment, Medical Decision Making presents both theoretical and practical statistical and modeling techniques and methods from a variety of disciplines.
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