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Use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews

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 e...

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Autores principales: Shemilt, Ian, Khan, Nada, Park, Sophie, Thomas, James
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4989498/
https://www.ncbi.nlm.nih.gov/pubmed/27535658
http://dx.doi.org/10.1186/s13643-016-0315-4
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author Shemilt, Ian
Khan, Nada
Park, Sophie
Thomas, James
author_facet Shemilt, Ian
Khan, Nada
Park, Sophie
Thomas, James
author_sort Shemilt, Ian
collection PubMed
description 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.
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spelling pubmed-49894982016-08-19 Use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews Shemilt, Ian Khan, Nada Park, Sophie Thomas, James Syst Rev Research 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. BioMed Central 2016-08-17 /pmc/articles/PMC4989498/ /pubmed/27535658 http://dx.doi.org/10.1186/s13643-016-0315-4 Text en © Khan et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Shemilt, Ian
Khan, Nada
Park, Sophie
Thomas, James
Use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews
title Use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews
title_full Use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews
title_fullStr Use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews
title_full_unstemmed Use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews
title_short Use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews
title_sort use of cost-effectiveness analysis to compare the efficiency of study identification methods in systematic reviews
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4989498/
https://www.ncbi.nlm.nih.gov/pubmed/27535658
http://dx.doi.org/10.1186/s13643-016-0315-4
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