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Integration of genomics into clinical care : methods for economic evaluation

University of British Columbia

Background: As genomic technologies become more affordable, the demand for having these data will increase. Decision-makers must anticipate the increasing influence of genomics on heath care systems and take into account the expectations of patients, the public, health care providers, and industry in this regard. This thesis demonstrates applications of several methods for evaluation of genomic technologies in medicine. Using four case studies, I have highlighted the advantages that each method can offer given the nature and scope of the research question in each case study. Objectives: My specific objectives in the case studies were: 1) To elicit the preferences of cancer patients as well as the public for a hypothetical, genetically-guided treatment for cancer (a discrete choice experiment ); 2) To estimate the relative importance of attributes which influence physicians’ decisions for using personalized medicine in their practice (a Best Worst Scaling choice experiment); 3) To evaluate the impact of three potential genomic/proteomic tests on the long term burden of COPD in Canada (a system dynamics model); 4) To measure the cost-effectiveness of adding a new molecular diagnostic test (DX) to the current diagnostic strategy for thyroid cancer (using a discrete event simulation). Methods: Through these case studies, I have demonstrated the particular advantages of using discrete choice experiment (DCE), best-worst scaling (BWS) experiment, system dynamics simulation, and discrete event simulation (DES) for evaluations of genomic technologies. Results: Using four case studies I exemplified the questions that emerge in the process of integrating genomics into clinical care. In addition to bridging the methodological gaps by incorporating several novel methods (BWS, dynamic systems, and DES), the selected case studies illustrated the practical issues regarding the integration of genomics into clinical care from the perspective of patients, the public, health care providers, and decisionmakers. Conclusion: Although the methods previously developed for health technology assessment can be applied to the evaluation of genomic technologies as well, methodological challenges in the evaluation of genomic applications entail utilizing more diverse and more sophisticated analytical tools.

Text

2012-03-02

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/41113

Pharmaceutical Sciences

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/