Literature DB >> 21954237

Evidence for the credibility of health economic models for health policy decision-making: a systematic literature review of screening for abdominal aortic aneurysms.

Rikke Søgaard1, Jes Lindholt.   

Abstract

OBJECTIVE: To investigate whether the credibility of health economic models of screening for abdominal aortic aneurysms for health policy decision-making has improved since 2005 when a systematic review by Campbell et al. concluded that reporting standards were poor and there was divergence between the findings of studies that was hard to explain.
METHODS: A systematic literature review was carried out following PRISMA reporting principles. Health economic models of the cost-effectiveness of screening for abdominal aortic aneurysms published between 2005-2010 were included. Key characteristics were extracted and the models were assessed for quality against guidelines for best practice by a multidisciplinary team.
RESULTS: Seven models were identified and found to provide divergent guidance. Only three reports met 10 of the 15 quality criteria.
CONCLUSIONS: Researchers in the field seem to have benefited from general advances in health economic modelling and some improvements in reporting were noted. However, the low level of agreement between studies in model structures and assumptions, and difficulty in justifying these (convergent validity), remain a threat to the credibility of health economic models. Decision-makers should not accept the results of a modelling study if the methods are not fully transparent and justified. Modellers should, whenever relevant, supplement a primary report of results with a technical report detailing and discussing the methodological choices made.

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Year:  2011        PMID: 21954237     DOI: 10.1258/jhsrp.2011.010133

Source DB:  PubMed          Journal:  J Health Serv Res Policy        ISSN: 1355-8196


  1 in total

1.  Cost effectiveness of abdominal aortic aneurysm screening and rescreening in men in a modern context: evaluation of a hypothetical cohort using a decision analytical model.

Authors:  Rikke Søgaard; Jesper Laustsen; Jes S Lindholt
Journal:  BMJ       Date:  2012-07-05
  1 in total

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