Dataset Information

Dialysis search filters for PubMed, Ovid MEDLINE, and Embase databases.

ABSTRACT:

Background and objectives

Physicians frequently search bibliographic databases, such as MEDLINE via PubMed, for best evidence for patient care. The objective of this study was to develop and test search filters to help physicians efficiently retrieve literature related to dialysis (hemodialysis or peritoneal dialysis) from all other articles indexed in PubMed, Ovid MEDLINE, and Embase.

Design, setting, participants, & measurements

A diagnostic test assessment framework was used to develop and test robust dialysis filters. The reference standard was a manual review of the full texts of 22,992 articles from 39 journals to determine whether each article contained dialysis information. Next, 1,623,728 unique search filters were developed, and their ability to retrieve relevant articles was evaluated.

Results

The high-performance dialysis filters consisted of up to 65 search terms in combination. These terms included the words "dialy" (truncated), "uremic," "catheters," and "renal transplant wait list." These filters reached peak sensitivities of 98.6% and specificities of 98.5%. The filters' performance remained robust in an independent validation subset of articles.

Conclusions

These empirically derived and validated high-performance search filters should enable physicians to effectively retrieve dialysis information from PubMed, Ovid MEDLINE, and Embase.

SUBMITTER: Iansavichus AV

PROVIDER: S-EPMC3463205 | biostudies-literature | 2012 Oct

REPOSITORIES: biostudies-literature

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Publications

Dialysis search filters for PubMed, Ovid MEDLINE, and Embase databases.

Iansavichus Arthur V AV Haynes R Brian RB Lee Christopher W C CW Wilczynski Nancy L NL McKibbon Ann A Shariff Salimah Z SZ Blake Peter G PG Lindsay Robert M RM Garg Amit X AX

Clinical journal of the American Society of Nephrology : CJASN 20120823 10

<h4>Background and objectives</h4>Physicians frequently search bibliographic databases, such as MEDLINE via PubMed, for best evidence for patient care. The objective of this study was to develop and test search filters to help physicians efficiently retrieve literature related to dialysis (hemodialysis or peritoneal dialysis) from all other articles indexed in PubMed, Ovid MEDLINE, and Embase.<h4>Design, setting, participants, & measurements</h4>A diagnostic test assessment framework was used to ...[more]

PMID: 22917701

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Project description:BACKGROUND: The identification of health services research in databases such as PubMed/Medline is a cumbersome task. This task becomes even more difficult if the field of interest involves the use of diverse methods and data sources, as is the case with nurse staffing research. This type of research investigates the association between nurse staffing parameters and nursing and patient outcomes. A comprehensively developed search strategy may help identify nurse staffing research in PubMed/Medline. METHODS: A set of relevant references in PubMed/Medline was identified by means of three systematic reviews. This development set was used to detect candidate free-text and MeSH terms. The frequency of these terms was compared to a random sample from PubMed/Medline in order to identify terms specific to nurse staffing research, which were then used to develop a sensitive, precise and balanced search strategy. To determine their precision, the newly developed search strategies were tested against a) the pool of relevant references extracted from the systematic reviews, b) a reference set identified from an electronic journal screening, and c) a sample from PubMed/Medline. Finally, all newly developed strategies were compared to PubMed's Health Services Research Queries (PubMed's HSR Queries). RESULTS: The sensitivities of the newly developed search strategies were almost 100% in all of the three test sets applied; precision ranged from 6.1% to 32.0%. PubMed's HSR queries were less sensitive (83.3% to 88.2%) than the new search strategies. Only minor differences in precision were found (5.0% to 32.0%). CONCLUSIONS: As with other literature on health services research, nurse staffing studies are difficult to identify in PubMed/Medline. Depending on the purpose of the search, researchers can choose between high sensitivity and retrieval of a large number of references or high precision, i.e. and an increased risk of missing relevant references, respectively. More standardized terminology (e.g. by consistent use of the term "nurse staffing") could improve the precision of future searches in this field. Empirically selected search terms can help to develop effective search strategies. The high consistency between all test sets confirmed the validity of our approach.

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Dataset Information

Dialysis search filters for PubMed, Ovid MEDLINE, and Embase databases.

Background and objectives

Design, setting, participants, & measurements

Results

Conclusions

Publications

Dialysis search filters for PubMed, Ovid MEDLINE, and Embase databases.

Similar Datasets

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