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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Shemilt, Ian Khan, Nada Park, Sophie Thomas, James |
| Abstract | Background Meta-research studies investigating methods, systems, and processes designed to improve the efficiency of systematic review workflows can contribute to building an evidence base that can help to increase value and reduce waste in research. This study demonstrates the use of an economic evaluation framework to compare the costs and effects of four variant approaches to identifying eligible studies for consideration in systematic reviews. Methods A cost-effectiveness analysis was conducted using a basic decision-analytic model, to compare the relative efficiency of ‘safety first’, ‘double screening’, ‘single screening’ and ‘single screening with text mining’ approaches in the title-abstract screening stage of a ‘case study’ systematic review about undergraduate medical education in UK general practice settings. Incremental cost-effectiveness ratios (ICERs) were calculated as the ‘incremental cost per citation ‘saved’ from inappropriate exclusion’ from the review. Resource use and effect parameters were estimated based on retrospective analysis of ‘review process’ meta-data curated alongside the ‘case study’ review, in conjunction with retrospective simulation studies to model the integrated use of text mining. Unit cost parameters were estimated based on the ‘case study’ review’s project budget. A base case analysis was conducted, with deterministic sensitivity analyses to investigate the impact of variations in values of key parameters. Results Use of ‘single screening with text mining’ would have resulted in title-abstract screening workload reductions (base case analysis) of >60 % compared with other approaches. Across modelled scenarios, the ‘safety first’ approach was, consistently, equally effective and less costly than conventional ‘double screening’. Compared with ‘single screening with text mining’, estimated ICERs for the two non-dominated approaches (base case analyses) ranged from £1975 (‘single screening’ without a ‘provisionally included’ code) to £4427 (‘safety first’ with a ‘provisionally included’ code) per citation ‘saved’. Patterns of results were consistent between base case and sensitivity analyses. Conclusions Alternatives to the conventional ‘double screening’ approach, integrating text mining, warrant further consideration as potentially more efficient approaches to identifying eligible studies for systematic reviews. Comparable economic evaluations conducted using other systematic review datasets are needed to determine the generalisability of these findings and to build an evidence base to inform guidance for review authors. |
| Related Links | https://systematicreviewsjournal.biomedcentral.com/counter/pdf/10.1186/s13643-016-0315-4.pdf |
| Ending Page | 13 |
| Page Count | 13 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| ISSN | 20464053 |
| DOI | 10.1186/s13643-016-0315-4 |
| Journal | Systematic Reviews |
| Issue Number | 1 |
| Volume Number | 5 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2016-08-17 |
| Access Restriction | Open |
| Subject Keyword | Medicine Public Health Biomedicine Statistics for Life Sciences Health Sciences Incremental Cost Text Mining Base Case Analysis Undergraduate Medical Education Code Option Medicine/Public Health |
| Content Type | Text |
| Resource Type | Article |
| Subject | Medicine |
| Journal Impact Factor | 6.3/2023 |
| 5-Year Journal Impact Factor | 4.5/2023 |
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