Chen Gang, McKie John, Khan Munir A, Richardson Jeff R
Flinders University, Australia.
Monash University, Australia.
Eur J Cardiovasc Nurs. 2015 Oct;14(5):405-15. doi: 10.1177/1474515114536096. Epub 2014 May 14.
Quality of life is included in the economic evaluation of health services by measuring the preference for health states, i.e. health state utilities. However, most intervention studies include a disease-specific, not a utility, instrument. Consequently, there has been increasing use of statistical mapping algorithms which permit utilities to be estimated from a disease-specific instrument. The present paper provides such algorithms between the MacNew Heart Disease Quality of Life Questionnaire (MacNew) instrument and six multi-attribute utility (MAU) instruments, the Euroqol (EQ-5D), the Short Form 6D (SF-6D), the Health Utilities Index (HUI) 3, the Quality of Wellbeing (QWB), the 15D (15 Dimension) and the Assessment of Quality of Life (AQoL-8D).
Heart disease patients and members of the healthy public were recruited from six countries. Non-parametric rank tests were used to compare subgroup utilities and MacNew scores. Mapping algorithms were estimated using three separate statistical techniques.
Mapping algorithms achieved a high degree of precision. Based on the mean absolute error and the intra class correlation the preferred mapping is MacNew into SF-6D or 15D. Using the R squared statistic the preferred mapping is MacNew into AQoL-8D.
The algorithms reported in this paper enable MacNew data to be mapped into utilities predicted from any of six instruments. This permits studies which have included the MacNew to be used in cost utility analyses which, in turn, allows the comparison of services with interventions across the health system.
通过测量对健康状态的偏好,即健康状态效用,生活质量被纳入卫生服务的经济评估中。然而,大多数干预研究使用的是针对特定疾病的工具,而非效用工具。因此,越来越多地使用统计映射算法,这些算法允许从针对特定疾病的工具中估计效用。本文提供了麦克纽心脏病生活质量问卷(MacNew)工具与六种多属性效用(MAU)工具之间的此类算法,这六种工具分别是欧洲五维度健康量表(EQ-5D)、简式6D健康量表(SF-6D)、健康效用指数(HUI)3、健康福祉量表(QWB)、15维度健康量表(15D)和生活质量评估量表(AQoL-8D)。
从六个国家招募了心脏病患者和健康公众成员。使用非参数秩检验来比较亚组效用和MacNew分数。使用三种不同的统计技术估计映射算法。
映射算法实现了高度的精确性。基于平均绝对误差和组内相关系数,首选的映射是从MacNew到SF-6D或15D。使用决定系数统计量,首选的映射是从MacNew到AQoL-8D。
本文报告的算法使MacNew数据能够映射到由六种工具中的任何一种预测的效用中。这使得包含MacNew的研究能够用于成本效用分析,进而允许在整个卫生系统中比较不同服务与干预措施。