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PERFORMANCE OF OVID MEDLINE SEARCH FILTERS TO IDENTIFY HEALTH STATE UTILITY STUDIES

Part of: Special Collection - Methods

Published online by Cambridge University Press:  25 October 2017

Mick Arber ,
Sonia Garcia ,
Thomas Veale ,
Mary Edwards ,
Alison Shaw  and
Julie M. Glanville Open the ORCID record for Julie M. Glanville [Opens in a new window]
Mick Arber
Affiliation:
York Health Economics Consortiummick.arber@york.ac.uk
Sonia Garcia
Affiliation:
York Health Economics Consortium
Thomas Veale
Affiliation:
York Health Economics Consortium
Mary Edwards
Affiliation:
York Health Economics Consortium
Alison Shaw
Affiliation:
York Health Economics Consortium
Julie M. Glanville
Affiliation:
York Health Economics Consortium
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Abstract

Objectives: This study was designed to assess the sensitivity of three Ovid MEDLINE search filters developed to identify studies reporting health state utility values (HSUVs), to improve the performance of the best performing filter, and to validate resulting search filters.

Methods: Three quasi-gold standard sets (QGS1, QGS2, QGS3) of relevant studies were harvested from reviews of studies reporting HSUVs. The performance of three initial filters was assessed by measuring their relative recall of studies in QGS1. The best performing filter was then developed further using QGS2. This resulted in three final search filters (FSF1, FSF2, and FSF3), which were validated using QGS3.

Results: FSF1 (sensitivity maximizing) retrieved 132/139 records (sensitivity: 95 percent) in the QGS3 validation set. FSF1 had a number needed to read (NNR) of 842. FSF2 (balancing sensitivity and precision) retrieved 128/139 records (sensitivity: 92 percent) with a NNR of 502. FSF3 (precision maximizing) retrieved 123/139 records (sensitivity: 88 percent) with a NNR of 383.

Conclusions: We have developed and validated a search filter (FSF1) to identify studies reporting HSUVs with high sensitivity (95 percent) and two other search filters (FSF2 and FSF3) with reasonably high sensitivity (92 percent and 88 percent) but greater precision, resulting in a lower NNR. These seem to be the first validated filters available for HSUVs. The availability of filters with a range of sensitivity and precision options enables researchers to choose the filter which is most appropriate to the resources available for their specific research.

Keywords

Quality of lifeQuality-adjusted life-yearsCost-Benefit AnalysisInformation storage and retrievalDatabasesBibliographic
Type
Methods
Information
International Journal of Technology Assessment in Health Care , Volume 33 , Issue 4: Mini-Theme: Stories of HTA Impact , 2017 , pp. 472 - 480
Copyright
Copyright © Cambridge University Press 2017 

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References

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