医疗保健政策背景:科学研究的结果形成了基于证据的卫生政策决定的基础。
背景:用于评估研究结果可信度的质量评估是卫生技术评估报告和系统综述的重要组成部分。用于评估研究质量的质量评估工具(QAT)检查研究结果在多大程度上被混淆或偏差(内部有效性)系统地扭曲。这些工具可以分为清单,规模和组件评级。
目的:哪些QAT可用于评估干预研究或卫生经济学领域研究的质量,它们之间有什么不同?从这些结果中可以得出什么结论用于质量评估?
方法:从1988年开始对相关数据库进行系统搜索,通过筛选参考文献,德国卫生技术评估署(DAHTA)的HTA报告和互联网搜索。相关文献的选择,数据提取和质量评估由两名独立的审查员进行。QAT的实质性要素是使用修改后的标准列表提取的,该标准列表由随机试验特有的项目和领域组成。观察性研究,诊断研究,系统评价和卫生经济研究。根据涵盖的项目和域的数量,越来越不全面的QAT被区分。为了交流有关工具实际应用中的问题的经验,举办了一个研讨会。
结果:总共确定了8项系统方法学综述以及147项QAT:15用于系统综述,80用于随机试验,30用于观察性研究,17用于诊断研究,22用于卫生经济研究。工具的内容差异很大,运营的性能和质量。一些工具不仅包括内部有效性项目,还包括报告质量和外部有效性项目。没有工具涵盖所有元素或域。介绍了特定于设计的通用工具,涵盖了大部分内容标准。
结论:使用含量标准对QAT进行评估是困难的,因为对内部有效性的必要要素没有科学共识,并不是所有公认的要素都是基于经验证据的。将QAT与内容进行比较忽略了各个参数的可操作性,质量和精度对透明度很重要,可复制性,正确的评估和评估者间的可靠性。QAT,混合了报告质量和内部有效性的项目,应该避免。
结论:有不同的,可用于质量评估的特定设计工具,因为它涵盖了内部有效性的实质性要素。为了最大限度地减少评估的主观性,应应用对各个元素进行详细和精确操作的工具。对于健康经济研究,工具应该开发和补充说明,它定义了标准的适当性。需要进一步的研究来确定影响研究内部有效性的研究特征。
HEALTH CARE POLICY BACKGROUND: Findings from scientific studies form the basis for evidence-based health policy decisions.
BACKGROUND: Quality assessments to evaluate the credibility of study results are an essential part of health technology assessment
reports and systematic reviews. Quality assessment tools (QAT) for assessing the study quality examine to what extent study results are systematically distorted by confounding or bias (internal validity). The tools can be divided into
checklists, scales and component ratings.
OBJECTIVE: What QAT are available to assess the quality of interventional studies or studies in the field of health economics, how do they differ from each other and what conclusions can be drawn from these results for quality assessments?
METHODS: A systematic search of relevant databases from 1988 onwards is done, supplemented by screening of the references, of the HTA
reports of the German Agency for Health Technology Assessment (DAHTA) and an internet search. The selection of relevant literature, the data extraction and the quality assessment are carried out by two independent reviewers. The substantive elements of the QAT are extracted using a modified criteria list consisting of items and domains specific to randomized trials, observational studies, diagnostic studies, systematic reviews and health economic studies. Based on the number of covered items and domains, more and less comprehensive QAT are distinguished. In order to exchange experiences regarding problems in the practical application of tools, a workshop is hosted.
RESULTS: A total of eight systematic methodological reviews is identified as well as 147 QAT: 15 for systematic reviews, 80 for randomized trials, 30 for observational studies, 17 for diagnostic studies and 22 for health economic studies. The tools vary considerably with regard to the content, the performance and quality of operationalisation. Some tools do not only include the items of internal validity but also the items of quality of reporting and external validity. No tool covers all elements or domains. Design-specific generic tools are presented, which cover most of the content criteria.
CONCLUSIONS: The evaluation of QAT by using content criteria is difficult, because there is no scientific consensus on the necessary elements of internal validity, and not all of the generally accepted elements are based on empirical evidence. Comparing QAT with regard to contents neglects the operationalisation of the respective parameters, for which the quality and precision are important for transparency, replicability, the correct assessment and interrater reliability. QAT, which mix items on the quality of reporting and internal validity, should be avoided.
CONCLUSIONS: There are different, design-specific tools available which can be preferred for quality assessment, because of its wider coverage of substantive elements of internal validity. To minimise the subjectivity of the assessment, tools with a detailed and precise operationalisation of the individual elements should be applied. For health economic studies, tools should be developed and complemented with instructions, which define the appropriateness of the criteria. Further research is needed to identify study characteristics that influence the internal validity of studies.