This paper presents an updated systematic review of studies reporting mapping algorithms from clinical or patient reported outcome measures to EQ-5D-3L or EQ-5D-5L, as well as an assessment of how far mapping studies conform to the MAPS reporting statement.

The review identified 144 mapping studies reporting 190 algorithms mapping from 110 different instruments onto EQ-5D. The 15/17 studies published in 2016 had low adherence to the MAPS checklist.

The mapping studies can be accessed in the Health Economics Research Centre (HERC) Database of Mapping Studies, available at https://www.herc.ox.ac.uk/downloads/herc-database-of-mapping-studies. This database was created in 2013 and is focused on studies mapping to EQ-5D.

NHS EED and HEED, two key databases for retrieving health economics information, have closed. Based on this changed landscape, this abstract assesses which database are now the best sources of information for retrieving economic evaluations for models and systematic reviews. The authors built a quasi-gold standard database of 351 records compiled from 46 systematic reviews of economic evaluations. Nine databases were searched for each record. Embase had the highest yield (0.89), followed by Scopus (0.84) and MEDLINE and PubMed (both 0.81). The HTA database identified the highest number of unique citations (13/351). All nine database combined retrieved 337/351 (0.96) records. The authors conclude that for most systematic reviews, Embase, the HTA database and either PubMed or MEDLINE are likely sufficient to identify economic evaluations found in bibliographic databases. Searching a multi-disciplinary database may also be useful, especially in non-clinical topics. Supplementary search techniques may be more efficient than searching a larger number of databases.

MEDLINE search strategies reported in source systematic reviews were also assessed. 10/29 (34.5%) of re-run search strategies missed at least one of the included records found in MEDLINE (with 25 citations missed in total). Weaknesses in the population or intervention concepts, rather than the economics concept, were identified as negatively impacting search retrieval.

The retrieval of studies that report health state utility values (HSUVs) is an important aspect of information retrieval for HTA and economic model production.  This study first assessed three MEDLINE search filters designed by the York Health Economic Consortium (YHEC) to identify studies reporting HSUVs. The relative recall method was used to test the sensitivity of each filter. Three quasi gold standard (QSG) sets of relevant studies were compiled from reviews of studies reporting HSUVs. The first QSG (consisting of 294 records) was used to assess the performance of the three initial filters. The best performing of the three filters was further developed using the second QSG (139 records). Ultimately, three final search filters were validated using the third QSG (139 records). The first final search filter is sensitivity maximizing, with 95% sensitivity and a number needed to read (NNR) of 842. The second filter balances sensitivity and precision, and has a 92% sensitivity with an NNR of 502. The third filter is precision maximizing, with 88% sensitivity and an NNR of 383. Real world volume of retrieved records was also tested to illustrate the impact of using the three filters for three example health conditions. Having a range of sensitivity and precision options allows researchers to choose filters based on their search requirements. The authors believe that these are the first validated filters for retrieving HSURs. Search strategies for all three final filters are presented in the article.

This paper is a guidance document providing an overview of how health state utility values can be identified, reviewed and synthesised when conducting systematic reviews. The paper includes a case study of a review in osteoporosis-related conditions.

In terms of study identification, the authors note that a range of study designs could be relevant and that a number of instruments could be required including condition-specific preference based measures or generic preference based measures. They recommend that a variety of resources and methods should be used to identify studies. As well as electronic databases, searchers should also look at reference lists, conduct key author and citation searches and contact experts.

The authors recommend caution in using filters too early in the search process, to avoid missing potentially relevant studies. The authors also note the absence of dedicated subject headings within MeSH and EMTREE, and that although general subject headings such as ‘Quality of life’ will yield relevant studies, they are likely to demonstrate poor precision. Free text terms should be included in searches and are categorised as general terms (such as QALY), instrument specific terms (such as EQ-5D) and terms describing methods of utility elicitation such as standard gamble.

This is a scoping review of the volume, economic analytic techniques and therapeutic areas encompassed by the pediatric economic evaluation studies published between 1980 and 2014.  The review uses records from the Paediatric Economic Database Evaluation (PEDE) database of pediatric economic evaluations to explore trends in analytical techniques, target age groups, interventions, outcomes and disease classifications. The paper describes the eligibility criteria for PEDE. PEDE is populated through searches of  MEDLINE, CINAHL, EMBASE, International Pharmaceutical Abstracts (IPA), EconLit, the Cochrane Library, NHS EED and ERIC, as well as searches of over 73 websites of HTA agencies and research groups. PEDE is updated annually.

This article is the second in a three-part series on how to prepare a systematic review of economic evaluations. It provides a good overview of the literature on how to select relevant databases and develop a search strategy for retrieving economic evaluations. While the main target audience of the article is developers of clinical practice guidelines, the process described is helpful for systematic review researchers as well as those undertaking health technology assessments. The authors identify four steps in the search process: (1) selecting relevant databases (basic, specific and optional); (2) developing a comprehensive search strategy; (3) performing the searches (including documentation), and (4) selecting the relevant studies. The authors note the recent discontinuation of two health economics databases (HEED and NHS EED), which has resulted in an increased reliance on the use of search filters designed to capture economic evaluations. Also noted are unsettled issues, such as the lack of consensus on how many and which databases should be searched, as well a lack of uniform guidance on the methodology of developing a sound search strategy. Validated search filters and automated processes may help to overcome problems created by the lack of health economics-specific databases.

This study evaluated the search methodology of recent systematic reviews of economic evaluations. A sample of 42 reviews identified through a MEDLINE search was analyzed. The analysis included: databases searched (general & specialist), health technology assessment sources searched, and supplementary search techniques used. The search approaches used in the systematic reviews were compared to two current recommendations: 1) the minimum search resources from the National Institute for Health and Care Excellence (NICE) economic search requirements for single technology appraisals; 2) the resources recommended in the costs and economic evaluation chapter of SuRe Info. A majority (55%) of the reviews did not meet either the NICE or SuRe Info recommendations. The data collection was hindered by lack of clarity and errors in search methodology reporting within the systematic reviews. It is likely that current recommendations on searching for economic evaluations will change due to the recent closure of two specialized databases (NHS EED & HEED). 

This paper provides recommendations for the minimum level of searching which should be conducted to populate the various parameters  (e.g. treatment effects, costs, resource use) for a health economic decision model. The minimum searching level varies by parameter and the author suggests that the level should be adjusted depending on the importance of the parameter to the model. The paper describes the range of different resources which might need to be searched for each parameter and also indicates where country or region-specific resources might need to be identified. Specific guidance is given for each parameter and where more detailed guidance is available for search approaches for specific parameters, this guidance is signposted. This paper also makes brief recommendations on how to report searches.

A bibliometric analysis of full economic evaluations of health interventions was conducted. A search of 14 databases identified 2844 economic evaluations published between 1 January 2012 and 3 May 2014. Analyses included: the sensitivity and specificity of searches in all databases, the distribution of the publications between countries, regions and health areas studied, as well as authors' country and institutional affiliations, journal type, language, and type of economic evaluation. The Scopus search identified the largest number of economic evaluations (85%), followed by NHS EED (80%), and MEDLINE (79%). EconLit captured only 1% of the publications identified. The majority of economic evaluations were published in biomedical journals (74%), addressed high-income countries (83%), and had at least one author based in a high-income country (91%). The health areas studied correlated more closely with the burden of diseases in high income countries compared to low-and middle-income countries.