Systematic narrative review of decision frameworks to select the appropriate modelling approaches for health economic evaluations

Background In constructing or appraising a health economic model, an early consideration is whether the modelling approach selected is appropriate for the given decision problem. Frameworks and taxonomies that distinguish between modelling approaches can help make this decision more systematic and this study aims to identify and compare the decision frameworks proposed to date on this topic area. Methods A systematic review was conducted to identify frameworks from peer-reviewed and grey literature sources. The following databases were searched: OVID Medline and EMBASE; Wiley’s Cochrane Library and Health Economic Evaluation Database; PubMed; and ProQuest. Results Eight decision frameworks were identified, each focused on a different set of modelling approaches and employing a different collection of selection criterion. The selection criteria can be categorized as either: (i) structural features (i.e. technical elements that are factual in nature) or (ii) practical considerations (i.e. context-dependent attributes). The most commonly mentioned structural features were population resolution (i.e. aggregate vs. individual) and interactivity (i.e. static vs. dynamic). Furthermore, understanding the needs of the end-users and stakeholders was frequently incorporated as a criterion within these frameworks. Conclusions There is presently no universally-accepted framework for selecting an economic modelling approach. Rather, each highlights different criteria that may be of importance when determining whether a modelling approach is appropriate. Further discussion is thus necessary as the modelling approach selected will impact the validity of the underlying economic model and have downstream implications on its efficiency, transparency and relevance to decision-makers. Electronic supplementary material The online version of this article (doi:10.1186/s13104-015-1202-0) contains supplementary material, which is available to authorized users.

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PID https://www.doi.org/10.1186/s13104-015-1202-0
PID pmid:26081877
PID pmc:PMC4470071
URL https://core.ac.uk/display/81730548
URL https://www.ncbi.nlm.nih.gov/pubmed/26081877
URL https://bmcresnotes.biomedcentral.com/articles/10.1186/s13104-015-1202-0
URL https://dx.doi.org/10.1186/s13104-015-1202-0
URL https://academic.microsoft.com/#/detail/1817620624
URL http://link.springer.com/content/pdf/10.1186/s13104-015-1202-0
URL https://bmcresnotes.biomedcentral.com/track/pdf/10.1186/s13104-015-1202-0
URL http://dx.doi.org/10.1186/s13104-015-1202-0
URL https://link.springer.com/article/10.1186%2Fs13104-015-1202-0
URL http://europepmc.org/articles/PMC4470071
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Access Right Open Access
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Author Tsoi, B
Author O’Reilly, D
Author Jegathisawaran, J
Author Tarride, J-E
Author Blackhouse, G
Author Goeree, R
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Collected From Europe PubMed Central; PubMed Central; Datacite; UnpayWall; Crossref; Microsoft Academic Graph; CORE (RIOXX-UK Aggregator)
Hosted By Europe PubMed Central; SpringerOpen; BMC Research Notes
Journal BMC Research Notes, 8, 1
Publication Date 2015-06-17
Publisher Springer Nature
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Language English
Resource Type Other literature type; Article; UNKNOWN
keyword Biochemistry, Genetics and Molecular Biology_all_
system:type publication
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Source https://science-innovation-policy.openaire.eu/search/publication?articleId=dedup_wf_001::459cb4d89899c2c1bcce0807a95a9349
Author jsonws_user
Last Updated 24 December 2020, 15:13 (CET)
Created 24 December 2020, 15:13 (CET)