Applying Clinical Search Filters

A method for improving the retrieval of high quality studies applicable to clinical practice is to include search terms that select studies at advanced stages of testing for clinical application. Including one, or a combination of these terms, in a MEDLINE search strategy will selectively retrieve evidence-based literature that is more likely to answer clinical questions.

Clinical Queries

PubMed, a National Library of Medicine platform for searching MEDLINE, has a special search feature called Clinical Queries which automatically filters searches on questions of therapy, diagnosis, etiology or prognosis by looking for the highest levels of evidence in the literature.

Clinical filters are imposed behind the scenes by the search engine based on the work of B. Haynes, et al, on the best strategies for retrieving clinically relevant information from MEDLINE. Table of Clinical Filters

PubMed has another unique feature which contributes to getting the most out of MEDLINE. The Related Articles function will retrieve additional related articles based on an algorithm of key words and Medical Subject Headings.

Expert search strategies for clinical filters have been developed by several groups of librarians. These are two of the best available on the Web.

• Nesibt Filters for Ovid MEDLINE & CINAHL -- Miner Library, University of Rochester
  http://www.urmc.rochestser.edu/hslt/miner/digital_library/evidence_based_resources.cfm
• Search strategies to Identify Reviews and Meta-analyses in MEDLINE & CINAHL
  http://www.york.ac.uk/inst/crd/search.htm

Possible Clinical Filters for MEDLINE Search Strategies

Therapy Problems

Randomized Controlled Trial [pt]	Treatment Outcome [MeSH]
Controlled Clinical Trial [pt])	Multicenter Study [pt]
Therapy [sh]	Clinical Trial [pt]
Double Blind Method [MeSH]	Random* [tw]
Placebo* [tw]	Management [ti]

The best single term strategy is Randomized Controlled Trial [PT]

Diagnosis Problems

The best single-term search is Sensitivity and Specificity [MeSH]

Prognosis Problems

Etiology Problems

Questions of Harm

Find definitions of many of these terms in the Evidence-Based Medicine Glossary at http://www.cebm.net/glossary.asp

The following definitions are adapted from the Scope Notes in the National Library of Medicine's Medical Subject Headings: Annotated Alphabetical List

Randomized Controlled Trial [pt]
Clinical trials that involve at least one test treatment and one control treatment, concurrent enrollment and follow up of the test- and control-treated groups, and in which the treatments to be administered are selected by a random process, such as the the use of a
random-numbers table.

Clinical Trial [pt]
Pre-planned studies of the safety, efficacy or optimum dosage schedule of one or more diagnostic, therapeutic or prophylactic drugs, devices or techniques, selected according to predetermined criteria of eligibility and observed for predefined evidence of favorable and unfavorable effects.

Cohort Studies [MeSH]
Studies in which subsets of a defined population are identified. These groups may or may not be exposed to factors hypothesized to influence the probability of the occurrence of a particular disease or outcome.

Controlled Clinical Trial [pt]
Clinical trials that do not employ truly randomized techniques for patient assignment, but rather base allocation on coin flips, odd-even numbers, patient social security numbers, days of the week, or other pseudo- or quasi-random processes.

Case-Control Studies [MeSH]
Studies which start with the identification of persons with a disease of interest and a control group without the disease. The relationship of an attribute to the disease is examined by comparing diseased and non-diseased persons with regard to the frequency or levels of the attribute in each group.

Follow-up Studies [MeH]
Studies in which individuals or populations are followed to assess the outcome of exposures, procedures, or effects of a characteristic.

This page is maintained at www.uic.edu/depts/lib/lhsp/resources/ebm.shtml by Jo Dorsch, UIC Library of the Health Sciences-Peoria. Please send comments to Jo Dorsch jod@uic.edu.