Dataset Information

Optimal search strategies for detecting health services research studies in MEDLINE.

ABSTRACT:

Background

Evidence from health services research (HSR) is currently thinly spread through many journals, making it difficult for health services researchers, managers and policy-makers to find research on clinical practice guidelines and the appropriateness, process, outcomes, cost and economics of health care services. We undertook to develop and test search terms to retrieve from the MEDLINE database HSR articles meeting minimum quality standards.

Methods

The retrieval performance of 7445 methodologic search terms and phrases in MEDLINE (the test) were compared with a hand search of the literature (the gold standard) for each issue of 68 journal titles for the year 2000 (a total of 25,936 articles). We determined sensitivity, specificity and precision (the positive predictive value) of the MEDLINE search strategies.

Results

A majority of the articles that were classified as outcome assessment, but fewer than half of those in the other categories, were considered methodologically acceptable (no methodologic criteria were applied for cost studies). Combining individual search terms to maximize sensitivity, while keeping specificity at 50% or more, led to sensitivities in the range of 88.1% to 100% for several categories (specificities ranged from 52.9% to 97.4%). When terms were combined to maximize specificity while keeping sensitivity at 50% or more, specificities of 88.8% to 99.8% were achieved. When terms were combined to maximize sensitivity and specificity while minimizing the differences between the 2 measurements, most strategies for HSR categories achieved sensitivity and specificity of at least 80%.

Interpretation

Sensitive and specific search strategies were validated for retrieval of HSR literature from MEDLINE. These strategies have been made available for public use by the US National Library of Medicine at www.nlm.nih.gov/nichsr/hedges/search.html.

SUBMITTER: Wilczynski NL

PROVIDER: S-EPMC524948 | biostudies-literature |

REPOSITORIES: biostudies-literature

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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.