Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành y học dành cho các bạn tham khảo đề tài: Evaluating the impact of MEDLINE filters on evidence retrieval: study protocol | Shariff et al. Implementation Science 2010 5 58 http content 5 1 58 Implementation Science IMPLEMENTATION SCIENCE STUDY PROTOCOL Open Access Evaluating the impact of MEDLINE filters on evidence retrieval study protocol Salimah Z Shariff 1 Meaghan S Cuerden1 R Brian Haynes2 3 K Ann McKibbon3 Nancy L Wilczynski3 Arthur V Iansavichus1 Mark R Speechley4 Amardeep Thind4 Amit X Garg1 3 4 Abstract Background Rather than searching the entire MEDLINE database clinicians can perform searches on a filtered set of articles where relevant information is more likely to be found. Members of our team previously developed two types of MEDLINE filters. The methods filters help identify clinical research of high methodological merit. The content filters help identify articles in the discipline of renal medicine. We will now test the utility of these filters for physician MEDLINE searching. Hypothesis When a physician searches MEDLINE we hypothesize the use of filters will increase the number of relevant articles retrieved increase recall also called sensitivity and decrease the number of non-relevant articles retrieved increase precision also called positive predictive value compared to the performance of a physician s search unaided by filters. Methods We will survey a random sample of 100 nephrologists in Canada to obtain the MEDLINE search that they would first perform themselves for a focused clinical question. Each question we provide to a nephrologist will be based on the topic of a recently published well-conducted systematic review. We will examine the performance of a physician s unaided MEDLINE search. We will then apply a total of eight filter combinations to the search filters used in isolation or in combination . We will calculate the recall and precision of each search. The filter combinations that most improve on unaided physician searches will be identified and characterized. Discussion If these filters improve search performance .
