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在SUMSearch和谷歌学术中为临床实践指南制定检索策略并评估其检索性能。

Developing search strategies for clinical practice guidelines in SUMSearch and Google Scholar and assessing their retrieval performance.

作者信息

Haase Andrea, Follmann Markus, Skipka Guido, Kirchner Hanna

机构信息

Institute for Quality and Efficiency in Health Care (Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen [IQWiG]), Cologne, Germany.

出版信息

BMC Med Res Methodol. 2007 Jun 30;7:28. doi: 10.1186/1471-2288-7-28.

Abstract

BACKGROUND

Information overload, increasing time constraints, and inappropriate search strategies complicate the detection of clinical practice guidelines (CPGs). The aim of this study was to provide clinicians with recommendations for search strategies to efficiently identify relevant CPGs in SUMSearch and Google Scholar.

METHODS

We compared the retrieval efficiency (retrieval performance) of search strategies to identify CPGs in SUMSearch and Google Scholar. For this purpose, a two-term GLAD (GuideLine And Disease) strategy was developed, combining a defined CPG term with a specific disease term (MeSH term). We used three different CPG terms and nine MeSH terms for nine selected diseases to identify the most efficient GLAD strategy for each search engine. The retrievals for the nine diseases were pooled. To compare GLAD strategies, we used a manual review of all retrievals as a reference standard. The CPGs detected had to fulfil predefined criteria, e.g., the inclusion of therapeutic recommendations. Retrieval performance was evaluated by calculating so-called diagnostic parameters (sensitivity, specificity, and "Number Needed to Read" [NNR]) for search strategies.

RESULTS

The search yielded a total of 2830 retrievals; 987 (34.9%) in Google Scholar and 1843 (65.1%) in SUMSearch. Altogether, we found 119 unique and relevant guidelines for nine diseases (reference standard). Overall, the GLAD strategies showed a better retrieval performance in SUMSearch than in Google Scholar. The performance pattern between search engines was similar: search strategies including the term "guideline" yielded the highest sensitivity (SUMSearch: 81.5%; Google Scholar: 31.9%), and search strategies including the term "practice guideline" yielded the highest specificity (SUMSearch: 89.5%; Google Scholar: 95.7%), and the lowest NNR (SUMSearch: 7.0; Google Scholar: 9.3).

CONCLUSION

SUMSearch is a useful tool to swiftly gain an overview of available CPGs. Its retrieval performance is superior to that of Google Scholar, where a search is more time consuming, as substantially more retrievals have to be reviewed to detect one relevant CPG. In both search engines, the CPG term "guideline" should be used to obtain a comprehensive overview of CPGs, and the term "practice guideline" should be used if a less time consuming approach for the detection of CPGs is desired.

摘要

背景

信息过载、时间限制日益增加以及搜索策略不当,使得临床实践指南(CPG)的检索变得复杂。本研究的目的是为临床医生提供搜索策略建议,以便在SUMSearch和谷歌学术中高效识别相关CPG。

方法

我们比较了在SUMSearch和谷歌学术中识别CPG的搜索策略的检索效率(检索性能)。为此,开发了一种双词GLAD(指南与疾病)策略,将一个定义的CPG词与一个特定疾病词(医学主题词)相结合。我们针对9种选定疾病使用了3个不同的CPG词和9个医学主题词,以确定每个搜索引擎最有效的GLAD策略。汇总了9种疾病的检索结果。为了比较GLAD策略,我们将对所有检索结果的人工审查作为参考标准。检测到的CPG必须符合预定义标准,例如包含治疗建议。通过计算搜索策略的所谓诊断参数(敏感性、特异性和“阅读需要量”[NNR])来评估检索性能。

结果

搜索总共产生了2830条检索结果;谷歌学术中有987条(34.9%),SUMSearch中有1843条(65.1%)。我们总共为9种疾病找到了119条独特且相关的指南(参考标准)。总体而言,GLAD策略在SUMSearch中的检索性能优于谷歌学术。搜索引擎之间的性能模式相似:包含“指南”一词的搜索策略敏感性最高(SUMSearch:81.5%;谷歌学术:31.9%),包含“实践指南”一词的搜索策略特异性最高(SUMSearch:89.5%;谷歌学术:95.7%),且NNR最低(SUMSearch:7.0;谷歌学术:9.3)。

结论

SUMSearch是快速全面了解可用CPG的有用工具。其检索性能优于谷歌学术,在谷歌学术中搜索更耗时,因为要检测到一条相关CPG需要审查更多的检索结果。在这两个搜索引擎中,如果想全面了解CPG,应使用CPG词“指南”;如果希望采用耗时较少的方法检测CPG,则应使用“实践指南”一词。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9360/1925105/923c6787b51b/1471-2288-7-28-1.jpg

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