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One Thousand Health-Related Quality-of-Life Estimates

可比性 比例(比率) 一致性(知识库) 数据提取 生活质量(医疗保健) 医学 梅德林 质量调整寿命年 精算学 质量(理念) 成本效益 计算机科学 业务 风险分析(工程) 数学 政治学 护理部 法学 人工智能 哲学 物理 组合数学 认识论 量子力学
作者
Tammy O. Tengs,Amy E. Wallace
出处
期刊:Medical Care [Lippincott Williams & Wilkins]
卷期号:38 (6): 583-637 被引量:671
标识
DOI:10.1097/00005650-200006000-00004
摘要

Objective. Analysts performing cost-effectiveness analyses often do not have the resources to gather original quality-of-life (QOL) weights. Furthermore, variability in QOL for the same health state hampers the comparability of cost-effectiveness analyses. For these reasons, opinion leaders such as the Panel on Cost-Effectiveness in Health and Medicine have called for a national repository of QOL weights. Some authors have responded to the call by performing large primary studies of QOL. We take a different approach, amassing existing data with the hope that it will be combined responsibly in meta-analytic fashion. Toward the goal of developing a national repository of QOL weights to aid cost-effectiveness analysts, 1,000 health-related QOL estimates were gathered from publicly available source documents. Methods. To identify documents, we searched databases and reviewed the bibliographies of articles, books, and government reports. From each document, we extracted information on the health state, QOL weight, assessment method, respondents, and upper and lower bounds of the QOL scale. Detailed guidelines were followed to ensure consistency in data extraction. Results. We identified 154 documents yielding 1,000 original QOL weights. There was considerable variation in the weights assessed by different authors for the same health state. Methods also varied: 51% of authors used direct elicitation (standard gamble, time tradeoff, or rating scale), 32% estimated QOL based on their own expertise or that of others, and 17% used health status instruments. Conclusions. This comprehensive review of QOL data should lead to more consistent use of QOL weights and thus more comparable cost-effectiveness analyses.
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