Objective: To contribute to making searching for Technology Assessment Reports (TARs) more cost-effective by suggesting an optimum literature retrieval strategy.
Data sources: A sample of 20 recent TARs.
Review methods: All sources used to search for clinical and cost-effectiveness studies were recorded. In addition, all studies that were included in the clinical and cost-effectiveness sections of the TARs were identified, and their characteristics recorded, including author, journal, year, study design, study size and quality score. Each was also classified by publication type, and then checked to see whether it was indexed in the following databases: MEDLINE, EMBASE, and then either the Cochrane Controlled Trials Register (CCTR) for clinical effectiveness studies or the NHS Economic Evaluation Database (NHS EED) for the cost-effectiveness studies. Any study not found in at least one of these databases was checked to see whether it was indexed in the Science Citation Index (SCI) and BIOSIS, and the American Society of Clinical Oncology (ASCO) Online if a cancer review. Any studies still not found were checked to see whether they were in a number of additional databases.
Results: The median number of sources searched per TAR was 20, and the range was from 13 to 33 sources. Six sources (CCTR, DARE, EMBASE, MEDLINE, NHS EED and sponsor/industry submissions to National Institute for Clinical Excellence) were used in all reviews. After searching the MEDLINE, EMBASE and NHS EED databases, 87.3% of the clinical effectiveness studies and 94.8% of the cost-effectiveness studies were found, rising to 98.2% when SCI, BIOSIS and ASCO Online and 97.9% when SCI and ASCO Online, respectively, were added. The median number of sources searched for the 14 TARs that included an economic model was 9.0 per TAR. A sensitive search filter for identifying non-randomised controlled trials (RCT), constructed for MEDLINE and using the search terms from the bibliographic records in the included studies, retrieved only 85% of the known sample. Therefore, it is recommended that when searching for non-RCT studies a search is done for the intervention alone, and records are then scanned manually for those that look relevant.
Conclusions: Searching additional databases beyond the Cochrane Library (which includes CCTR, NHS EED and the HTA database), MEDLINE, EMBASE and SCI, plus BIOSIS limited to meeting abstracts only, was seldom found to be effective in retrieving additional studies for inclusion in the clinical and cost-effectiveness sections of TARs (apart from reviews of cancer therapies, where a search of the ASCO database is recommended). A more selective approach to database searching would suffice in most cases and would save resources, thereby making the TAR process more efficient. However, searching non-database sources (including submissions from manufacturers, recent meeting abstracts, contact with experts and checking reference lists) does appear to be a productive way of identifying further studies.