Julie Glanville1, Suzy Paisley. 1. York Health Economics Consortium, University of York, Market Square, York, North Yorks YO10 5NH, United Kingdom. jmg1@york.ac.uk
Abstract
OBJECTIVES AND METHODS: Health technology assessment (HTA) often requires the identification and review of economic evaluations and models. This study surveys the available specific and general resources to search to identify economic evaluations. It also provides information on efficient searching of those resources and comments on the current evidence-base. RESULTS: Published checklists recommend searching for economic evaluations in specific information resources which collect economic evaluations such as NHS EED and HEED, followed by top-up searches of large biomedical bibliographic databases (such as MEDLINE and EMBASE). Other resources such as the HTA and DARE databases can yield reports of economic evaluations. Searches within NHS EED and HEED can be made more efficient by using database-specific search options. Searches within large biomedical databases such as MEDLINE and EMBASE require the use of economic search terms called search filters. Search filters are highly sensitive, retrieving most economic evaluations, but suffer from low precision returning many irrelevant records which need to be assessed. CONCLUSIONS: It is relatively easy to identify rapidly a high proportion of economic evaluations but more research is required to improve the efficiency of this process. There are key high yield resources to search but more evidence is required on their overlap and unique contribution to searches. The value of other resources, particularly those providing access to gray literature, should be explored. Research into efficient retrieval requires clear definitions of economic evaluations to allow comparison across studies.
OBJECTIVES AND METHODS: Health technology assessment (HTA) often requires the identification and review of economic evaluations and models. This study surveys the available specific and general resources to search to identify economic evaluations. It also provides information on efficient searching of those resources and comments on the current evidence-base. RESULTS: Published checklists recommend searching for economic evaluations in specific information resources which collect economic evaluations such as NHS EED and HEED, followed by top-up searches of large biomedical bibliographic databases (such as MEDLINE and EMBASE). Other resources such as the HTA and DARE databases can yield reports of economic evaluations. Searches within NHS EED and HEED can be made more efficient by using database-specific search options. Searches within large biomedical databases such as MEDLINE and EMBASE require the use of economic search terms called search filters. Search filters are highly sensitive, retrieving most economic evaluations, but suffer from low precision returning many irrelevant records which need to be assessed. CONCLUSIONS: It is relatively easy to identify rapidly a high proportion of economic evaluations but more research is required to improve the efficiency of this process. There are key high yield resources to search but more evidence is required on their overlap and unique contribution to searches. The value of other resources, particularly those providing access to gray literature, should be explored. Research into efficient retrieval requires clear definitions of economic evaluations to allow comparison across studies.
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