Updated generic search filters for finding studies of adverse drug effects in Ovid medline and Embase may retrieve up to 90% of relevant studies

Background

The most current objectively derived search filters for adverse drug effects are 15 years old and other strategies have not been developed and tested empirically.

Objective

To develop and validate search filters to retrieve evidence on adverse drug effects from Ovid medline and Ovid Embase.

Methods

We identified systematic reviews of adverse drug effects in Epistemonikos. From these reviews, we collated their included studies which we then randomly divided into three tests and one validation set of records. We constructed a search strategy to maximise relative recall using word frequency analysis with test set one. This search strategy was then refined using test sets two and three and validated on the final set of records.

Results

Of 107 systematic reviews which met our inclusion criteria, 1948 unique included studies were available from medline and 1980 from Embase. Generic adverse drug effects searches in medline and Embase achieved 90% and 89% relative recall, respectively. When specific adverse effects terms were added recall was improved.

Conclusion

We have derived and validated search filters that retrieve around 90% of records with adverse drug effects data in medline and Embase. The addition of specific adverse effects terms is required to achieve higher recall.     

Sensitivity and precision of adverse effects search filters in MEDLINE and EMBASE: a case study of fractures with thiazolidinediones

Background: Search filters have been developed in MEDLINE and EMBASE to help overcome the challenges of searching electronic databases for information on adverse effects. However, little evaluation of their effectiveness has been carried out. Objectives: To measure the sensitivity and precision of available adverse effects search filters in MEDLINE and EMBASE. Methods: A case study systematic review of fracture related adverse effects associated with the use of thiazolidinediones was used. Twelve MEDLINE search strategies and three EMBASE search strategies were tested. Results: Nineteen relevant references from MEDLINE and 24 from EMBASE were included in the review. Four search filters in MEDLINE achieved high sensitivity (95 or 100%) with an improved level of precision from searches without any adverse effects filter. High precision in MEDLINE could also be achieved (up to 53%) using search filters that rely on Medical Subject Headings. No search filter in EMBASE achieved high precision (all were under 5%) and the highest sensitivity in EMBASE was 83%. Conclusions: Adverse effects search filters appear to be effective in MEDLINE for achieving either high sensitivity or high precision. Search filters in EMBASE, however, do not appear as effective, particularly in improving precision.     

Optimising the retrieval of information on adverse drug effects

Pharmaceutical interventions have brought about many benefits to health, improving the population's well‐being and life expectancy. However, these interventions are not without potential harmful side‐effects and yet searching for the evidence on adverse effects is challenging. This article summarises a PhD whose main aim was to develop a better understanding of the implications of using different sources and approaches to identifying relevant data on adverse effects. The author is Su Golder, who has recently completed her PhD at the University of York and who has already published several articles on specific aspects of her research, including this journal. This article is the first in the Dissertations into Practice series to report on a PhD study, and it summarises her research in a way which emphasises the implications for practice. AM     

Development of a validated search filter for Ovid Embase for degenerative cervical myelopathy

Background

Degenerative cervical myelopathy (DCM) is a recently proposed umbrella term for symptomatic cervical spinal cord compression secondary to degeneration of the spine. Currently literature searching for DCM is challenged by the inconsistent uptake of the term ‘DCM’ with many overlapping keywords and numerous synonyms.

Objectives

Here, we adapt our previous Ovid medline search filter for the Ovid embase database, to support comprehensive literature searching. Both embase and medline are recommended as a minimum for systematic reviews.

Methods

References contained within embase identified in our prior study formed a ‘development gold standard’ reference database (N = 220). The search filter was adapted for embase and checked against the reference database. The filter was then validated against the ‘validation gold standard’.

Results

A direct translation was not possible, as medline indexing for DCM and the keywords search field were not available in embase . We also used the ‘focus’ function to improve precision. The resulting search filter has 100% sensitivity in testing.

Discussion and Conclusion

We have developed a validated search filter capable of retrieving DCM references in embase with high sensitivity. In the absence of consistent terminology and indexing, this will support more efficient and robust evidence synthesis in the field.     

The performance of adverse effects search filters in MEDLINE and EMBASE

Background: Search filters can potentially improve the efficiency of searches involving electronic databases such as medline and embase . Although search filters have been developed for identifying records that contain adverse effects data, little is known about the sensitivity of such filters. Objectives: This study measured the sensitivity of using available adverse effects filters to retrieve papers with adverse effects data. Methods: A total of 233 included studies from 26 systematic reviews of adverse effects were used for analysis. Search filters from medline and embase were tested for their sensitivity in retrieving the records included in these reviews. In addition, the sensitivity of each individual search term used in at least one search filter was measured. Results: Subheadings proved the most useful search terms in both medline and embase . No indexing terms in medline achieved over 12% sensitivity. The sensitivity of published search filters varied in medline from 3% to 93% and in embase from 57% to 97%. Whether this level of sensitivity is acceptable will be dependent on the purpose of the search. Conclusions: Although no adverse effects search filter captured all the relevant records, high sensitivity could be achieved. Search filters may therefore be useful in retrieving adverse effects data.