Division of Nephrology, University of Western Ontario, London, Ont.
CMAJ. 2012 Feb 21;184(3):E184-90. doi: 10.1503/cmaj.101661. Epub 2012 Jan 16.
Physicians face challenges when searching PubMed for research evidence, and they may miss relevant articles while retrieving too many nonrelevant articles. We investigated whether the use of search filters in PubMed improves searching by physicians.
We asked a random sample of Canadian nephrologists to answer unique clinical questions derived from 100 systematic reviews of renal therapy. Physicians provided the search terms that they would type into PubMed to locate articles to answer these questions. We entered the physician-provided search terms into PubMed and applied two types of search filters alone or in combination: a methods-based filter designed to identify high-quality studies about treatment (clinical queries "therapy") and a topic-based filter designed to identify studies with renal content. We evaluated the comprehensiveness (proportion of relevant articles found) and efficiency (ratio of relevant to nonrelevant articles) of the filtered and nonfiltered searches. Primary studies included in the systematic reviews served as the reference standard for relevant articles.
The average physician-provided search terms retrieved 46% of the relevant articles, while 6% of the retrieved articles were relevant (corrected) (the ratio of relevant to nonrelevant articles was 1:16). The use of both filters together produced a marked improvement in efficiency, resulting in a ratio of relevant to nonrelevant articles of 1:5 (16 percentage point improvement; 99% confidence interval 9% to 22%; p < 0.003) with no substantive change in comprehensiveness (44% of relevant articles found; p = 0.55).
The use of PubMed search filters improves the efficiency of physician searches. Improved search performance may enhance the transfer of research into practice and improve patient care.
医生在 PubMed 中搜索研究证据时面临挑战，他们在检索到过多不相关文章的同时，可能会错过相关文章。我们研究了在 PubMed 中使用搜索过滤器是否能改善医生的搜索效果。
我们随机抽取了加拿大的肾病医生，让他们回答从 100 篇肾脏治疗系统评价中衍生出来的 100 个独特的临床问题。医生们提供了他们将输入 PubMed 以查找文章来回答这些问题的搜索词。我们将医生提供的搜索词输入 PubMed，并单独或组合使用两种类型的搜索过滤器：一种是基于方法的过滤器，旨在识别有关治疗的高质量研究（临床查询“疗法”）；另一种是基于主题的过滤器，旨在识别具有肾脏内容的研究。我们评估了过滤和非过滤搜索的全面性（找到的相关文章比例）和效率（相关文章与不相关文章的比例）。系统评价中包含的原始研究作为相关文章的参考标准。
平均而言，医生提供的搜索词检索到了 46%的相关文章，而检索到的 6%的文章是相关的（校正后）（相关文章与不相关文章的比例为 1:16）。同时使用这两种过滤器显著提高了效率，导致相关文章与不相关文章的比例为 1:5（16 个百分点的提高；99%置信区间为 9%至 22%；p<0.003），但全面性没有实质性变化（找到的相关文章为 44%；p=0.55）。
使用 PubMed 搜索过滤器可以提高医生搜索的效率。搜索性能的提高可能会促进研究成果向实践的转化，并改善患者的护理。
