PubMed's core clinical journals filter: redesigned for contemporary clinical impact and utility

PubMed核心临床期刊筛选器:重新设计,更具当代临床影响力和实用性

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Abstract

OBJECTIVE: The Core Clinical Journals (CCJ) list, produced by the U.S. National Library of Medicine (NLM), has been used by clinicians and librarians for half a century for two main purposes: narrowing a literature search to clinically useful journals and identifying high priority titles for library collections. After documentation of low usage of the existing CCJ, a review was undertaken to assess current validity, followed by an update to current clinical needs. METHODS: As the subject coverage of the 50-year-old list had never been evaluated, the CCJ committee began its innovative step-wise approach by analyzing the existing subject scope. To determine whether clinical subjects had changed over the last half-century, the committee collected data on journal usage in hospitals and medical facilities, adding journal usage from Morning Report blogs recording the journal article citations used by physicians and residents in response to clinical questions. Patient-driven high-frequency diagnoses and subjects added contextual data by depicting the clinical environment. RESULTS: The analysis identified a total of 80 subjects and selected 241 journals for the updated Clinical Journals filter, based on actual clinical utility of each journal. DISCUSSION: These data-driven methods created a different framework for evaluating the structure and content of this filter. It is the real-world evidence needed to highlight CCJ clinical impact and push clinically useful journals to first page results. Since the new process resulted in a new product, the name warrants a change from Core Clinical Journals (CCJ) to Clinically Useful Journals (CUJ). Therefore, the redesigned NLM Core Clinical Journals/AIM set from this point forward will be referred to as Clinically Useful Journals (CUJ). The evidence-based process used to reframe evaluation of the clinical impact and utility of biomedical journals is documented in this article.

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