Carnegie Mellon University, Department of Engineering and Public Policy, Pittsburgh, PA, USA.
McMaster University Faculty of Social Sciences, Hamilton, ON, Canada.
Med Decis Making. 2018 Aug;38(6):683-698. doi: 10.1177/0272989X18776637. Epub 2018 Jun 26.
Health-related quality of life (HRQL) preference-based scores are used to assess the health of populations and patients and for cost-effectiveness analyses. The National Institutes of Health Patient-Reported Outcomes Measurement Information System (PROMIS) consists of patient-reported outcome measures developed using item response theory. PROMIS is in need of a direct preference-based scoring system for assigning values to health states.
To produce societal preference-based scores for 7 PROMIS domains: Cognitive Function-Abilities, Depression, Fatigue, Pain Interference, Physical Function, Sleep Disturbance, and Ability to Participate in Social Roles and Activities.
Online survey of a US nationally representative sample ( n = 983).
Preferences for PROMIS health states were elicited with the standard gamble to obtain both single-attribute scoring functions for each of the 7 PROMIS domains and a multiplicative multiattribute utility (scoring) function.
The 7 single-attribute scoring functions were fit using isotonic regression with linear interpolation. The multiplicative multiattribute summary function estimates utilities for PROMIS multiattribute health states on a scale where 0 is the utility of being dead and 1 the utility of "full health." The lowest possible score is -0.022 (for a state viewed as worse than dead), and the highest possible score is 1.
The online survey systematically excludes some subgroups, such as the visually impaired and illiterate.
A generic societal preference-based scoring system is now available for all studies using these 7 PROMIS health domains.
健康相关生活质量(HRQL)偏好评分用于评估人群和患者的健康状况,并进行成本效益分析。美国国立卫生研究院患者报告结局测量信息系统(PROMIS)由使用项目反应理论开发的患者报告结局测量组成。PROMIS 需要一个直接的偏好评分系统,以便为健康状况赋值。
为 7 个 PROMIS 领域(认知功能-能力、抑郁、疲劳、疼痛干扰、身体功能、睡眠障碍以及参与社会角色和活动的能力)生成基于社会的偏好评分。
在美国全国代表性样本(n=983)的在线调查。
使用标准博弈法得出 PROMIS 健康状态的偏好,以获得 7 个 PROMIS 领域中的每一个的单一属性评分函数和一个乘法多属性效用(评分)函数。
使用具有线性插值的等渗回归拟合 7 个单一属性评分函数。乘法多属性综合函数估计 PROMIS 多属性健康状态的效用,其范围为 0 是死亡的效用,1 是“完全健康”的效用。可能的最低得分为-0.022(表示比死亡状态更差的状态),可能的最高得分为 1。
在线调查系统地排除了一些亚组,例如视力障碍者和文盲。
现在,对于使用这 7 个 PROMIS 健康领域的所有研究,都有一个通用的基于社会的偏好评分系统。