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Bayesian Approaches for Synthesising Evidence in Health Technology Assessment

dc.contributor.advisorTarride, Jean-Ericen_US
dc.contributor.authorMcCarron, Catherine Elizabethen_US
dc.contributor.departmentHealth Research Methodologyen_US
dc.date.accessioned2014-06-18T16:55:31Z
dc.date.available2014-06-18T16:55:31Z
dc.date.created2011-11-24en_US
dc.date.issued2012-04en_US
dc.description.abstract<p><strong>ABSTRACT</strong></p> <p><strong>Background and Objectives</strong>:<strong> </strong>Informed health care decision making depends on the available evidence base. Where the available evidence comes from different sources methods are required that can synthesise all of the evidence. The synthesis of different types of evidence poses various methodological challenges. The objective of this thesis is to investigate the use of Bayesian methods for combining evidence on effects from randomised and non-randomised studies and additional evidence from the literature with patient level trial data. <strong> </strong></p> <p><strong>Methods</strong>: Using a Bayesian three-level hierarchical model an approach was proposed to combine evidence from randomised and non-randomised studies while adjusting for potential imbalances in patient covariates. The proposed approach was compared to four other Bayesian methods using a case study of endovascular versus open surgical repair for the treatment of abdominal aortic aneurysms. In order to assess the performance of the proposed approach beyond this single applied example a simulation study was conducted. The simulation study examined a series of Bayesian approaches under a variety of scenarios. The subsequent research focussed on the use of informative prior distributions to integrate additional evidence with patient level data in a Bayesian cost-effectiveness analysis comparing endovascular and open surgical repair in terms of incremental costs and life years gained.</p> <p><strong>Results and Conclusions</strong>: The shift in the estimated odds ratios towards those of the more balanced randomised studies, observed in the case study, suggested that the proposed Bayesian approach was capable of adjusting for imbalances. These results were reinforced in the simulation study. The impact of the informative priors in terms of increasing estimated mean life years in the control group, demonstrated the potential importance of incorporating all available evidence in the context of an economic evaluation. In addressing these issues this research contributes to comprehensive evidence based decision making in health care.</p>en_US
dc.description.degreeDoctor of Philosophy (PhD)en_US
dc.identifier.otheropendissertations/6561en_US
dc.identifier.other7561en_US
dc.identifier.other2371583en_US
dc.identifier.urihttp://hdl.handle.net/11375/11605
dc.subjecthealth care decision makingen_US
dc.subjectcost-effectivenessen_US
dc.subjectinformative priorsen_US
dc.subjectcovariate adjustmenten_US
dc.subjectrandomised controlled trialsen_US
dc.subjectnon-randomised studiesen_US
dc.subjectMedicine and Health Sciencesen_US
dc.subjectMedicine and Health Sciencesen_US
dc.titleBayesian Approaches for Synthesising Evidence in Health Technology Assessmenten_US
dc.typethesisen_US

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