Abstract

OBJECTIVES: The key economic evaluation (EE) databases, NHS EED and HEED, have closed. Which databases do we now need to search to identify economic evaluations for models and systematic reviews (SRs)? We assess which databases are now the best sources of EEs and whether typical search strategies are effective.

METHODS: A quasi-gold standard (QGS) set of economic evaluations was formed from studies included in SRs of EEs undertaken to inform HTA. 9 databases were searched for each QGS reference. Yield for each database, and combination of databases, was calculated. MEDLINE search strategies reported in source SRs were re-run to assess their performance in finding EEs.

RESULTS: We built a QGS of 351 records from 46 reviews. 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 records (13/351), despite a low overall yield (0.1). All 9 databases combined retrieved 337/351 records. The most efficient combination of databases which could be searched to find records for all 337 references was Embase, Scopus, HTA Database and (MEDLINE or PubMed). 10/29 (34.5%) of re-run strategies missed at least 1 of the included records available in MEDLINE (25 records missed in total). Only 1 of the missed records was due to failings of search terms used for the economics concept.

CONCLUSIONS: For most SRs Embase, HTA Database and either PubMed or MEDLINE are likely to be sufficient to identify EEs included in bibliographic databases. Additionally searching a multidisciplinary database may be useful, particularly in non-clinical topics. Beyond this, supplementary search techniques may be more efficient than extensive database searching. Weaknesses in reported MEDLINE search strategies were identified which impacted retrieval; these weaknesses appear to be associated with population and intervention concepts, rather than the economics concept.

Abstract

INTRODUCTION: The estimation of utility values for the economic evaluation of therapies for wet age-related macular degeneration (AMD) is a particular challenge. Previous economic models in wet AMD have been criticized for failing to capture the bilateral nature of wet AMD by modelling visual acuity (VA) and utility values associated with the better-seeing eye only.

METHODS: Here we present a de novo regression analysis using generalized estimating equations (GEE) applied to a previous dataset of time trade-off (TTO)-derived utility values from a sample of the UK population that wore contact lenses to simulate visual deterioration in wet AMD. This analysis allows utility values to be estimated as a function of VA in both the better-seeing eye (BSE) and worse-seeing eye (WSE).

RESULTS: VAs in both the BSE and WSE were found to be statistically significant (p < 0.05) when regressed separately. When included without an interaction term, only the coefficient for VA in the BSE was significant (p = 0.04), but when an interaction term between VA in the BSE and WSE was included, only the constant term (mean TTO utility value) was significant, potentially a result of the collinearity between the VA of the two eyes. The lack of both formal model fit statistics from the GEE approach and theoretical knowledge to support the superiority of one model over another make it difficult to select the best model. CONCLUSION: Limitations of this analysis arise from the potential influence of collinearity between the VA of both eyes, and the use of contact lenses to reflect VA states to obtain the original dataset. Whilst further research is required to elicit more accurate utility values for wet AMD, this novel regression analysis provides a possible source of utility values to allow future economic models to capture the quality of life impact of changes in VA in both eyes.

Abstract

Patient experience and patient centred care have become increasingly recognised as ethical imperatives over the past few decades. Although the definition is still somewhat contested, patient centred care incorporates aspects of the patient experience, such as communication, shared decision making, and the way services are designed, accessed, and delivered, including integration of care.1 Patient experience has also become seen as integral to quality of care, leading to calls internationally for measurement and incentive structures to be realigned to place a greater focus on patient reported information. Existing pay for performance schemes such as the Quality and Outcomes Framework (QOF) in England, have been criticised for focusing on clinical management above patient experience. However, although it is easy to identify the shortcomings of current incentives, incorporating measures using patient reported information has challenges.

Abstract

OBJECTIVE: This article reviews the available evidence and guidance on methods to identify reports of quasi-experimental (QE) studies to inform systematic reviews of health care, public health, international development, education, crime and justice, and social welfare.

STUDY DESIGN AND SETTING: Research, guidance, and examples of search strategies were identified by searching a range of databases, key guidance documents, selected reviews, conference proceedings, and personal communication. Current practice and research evidence were summarized.

RESULTS: Four thousand nine hundred twenty-four records were retrieved by database searches, and additional documents were obtained by other searches. QE studies are challenging to identify efficiently because they have no standardized nomenclature and may be indexed in various ways. Reliable search filters are not available. There is a lack of specific resources devoted to collecting QE studies and little evidence on where best to search.

CONCLUSION: Searches to identify QE studies should search a range of resources and, until indexing improves, use strategies that focus on the topic rather than the study design. Better definitions, better indexing in databases, prospective registers, and reporting guidance are required to improve the retrieval of QE studies and promote systematic reviews of what works based on the evidence from such studies.

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.

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No abstract available