Choice certainty and deliberative thinking in discrete choice experiments : A theoretical and empirical investigation

The Canadian Centre for Applied Research in Cancer Control (ARCC) is funded by the Canadian Cancer Society Research Institute (2015-703549). This paper developed from discussions between Verity Watson and Dean Regier that were funded by the Peter Wall Institute of Advanced Studies, University of British Columbia. Jonathan Sicsic acknowledges funding from the People Programme (Marie Curie Actions) of the European Union’s Seventh Framework Programme (FP7/2007-2013) under REA grant agreement PCOFUND-GA-2013-609102, through the PRESTIGE programme coordinated by Campus France. He also benefited for this research from grants provided by the French National Institute for Cancer (Coordinator: Dr Nora Moumjid). The Health Economics Research Unit is funded by the Chief Scientist Office of the Scottish Government Health and Care Directorates. The usual disclaimer applies. We thank Aki Tsuchiya, Nicolas Krucien, Thijs Dekker, and all participants to the 5th workshop on non-market valuation for useful comments on previous drafts of the paper.Peer reviewedPostprin

The EORTC QLU-C10D: The Canadian Valuation Study and Algorithm to Derive Cancer-Specific Utilities From the EORTC QLQ-C30

Objective. The EORTC QLQ-C30 is widely used for assessing quality of life in cancer. However, QLQ-C30 responses cannot be incorporated in cost-utility analysis because they are not based on general population’s preferences, or utilities. To overcome this limitation, the QLU-C10D, a cancer-specific utility algorithm, was derived from the QLQ-C30. The aim of this study was to obtain Canadian population utility weights for the QLU-C10D. Methods. Respondents from a Canadian research panel expressed their preferences for 16 choice sets in an online discrete choice experiment. Each choice set consisted of two health states described by the 10 QLU-C10D domains plus an attribute representing duration of survival. Using a conditional logit model, responses were converted into utility decrements by evaluating the marginal rate of substitution between each QLU-C10D domain level with respect to duration. Results. A total of 3,363 individuals were recruited. A total of 2,345 completed at least one choice set and 2,271 completed all choice sets. The largest utility decrements were associated with the worse levels of Physical Functioning (−0.24), Pain (−0.18), Role Functioning (−0.15), Emotional Functioning (−0.12), and Nausea (−0.12). The remaining domains and levels had decrements of −0.05 to −0.09. The utility of the worst possible health state was −0.15. Conclusion. Respondents from the general population were most concerned with generic health domains, but Nausea and Bowel Problems also had an impact on the individual’s utility. It is unclear as to whether cancer-specific domains will affect cost-utility analysis when evaluating cancer treatments; this will be tested in the next phase of the study

Discrete choice experiments informing cost benefit analysis: a Bayesian approach with an application to genetic testing

Whilst discrete choice experiments (DCEs) are now widely used in health economics, their application within cost benefit framework has been limited. Studies that have conducted cost benefit analysis (CBA) using DCEs have not taken into account the joint uncertainty surrounding the outcomes using decision analytic methods and a Bayesian approach to statistical inference and estimation.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Impact of oncologist payment method on health care outcomes, costs, quality: a rapid review

Background: The incidence of cancer and the cost of its treatment continue to rise. The effect of these dual forces is a major burden on the system of health care financing. One cost containment approach involves changing the way physicians are paid. Payers are testing reimbursement methods such as capitation and prospective payment while also evaluating how the changes impact health outcomes, resource utilization, and quality of care. The purpose of this study is to identify evidence related to physician payment methods’ impacts, with a focus on cancer control. Methods: We conducted a rapid review. This involved defining eligibility criteria, identifying a search strategy, performing study selection according to the eligibility criteria, and abstracting data from included studies. This process was accompanied by a gray literature search for special topics. Results: The incentives in fee-for-service payment systems generally lead to health care services being applied inconsistently because providers practice independently with few systems in place for developing treatment protocols and practice reviews. This inconsistency is pronounced in cancer care because much of the total per patient spending occurs in the last month of life. Some insurers are predicting that this variation can be reduced through the use of prospective or bundled payments combined with decision support systems. Workload, recruitment, and retention are all affected by changes to physician payment models; effects seem to be magnified in the specialist context as their several extra years of training lower their overall supply. Conclusions: Experimentation with physician payment methods has tended to neglect cancer care providers. Policymakers designing cancer-focused physician reimbursement pilot programs should incorporate quality measurement since very ill patients may receive too little treatment when payment models do not cover oncologists’ total costs, e.g., fee-for-service systems whose prices do not account for the possible presence of other diseases.Medicine, Faculty ofOther UBCPopulation and Public Health (SPPH), School ofReviewedFacult

FDA Accelerated Approval for Malignant Hematology and Oncology Indications in the Canadian Environment

Accelerated approval (AA) by the FDA enables earlier access to promising new therapies. Health Canada has a similar process. Canada implemented a national health technology assessment (HTA) for reimbursement decisions in 2011. This study evaluated regulatory and funding timelines and decisions for FDA AA cancer therapies in Canada. The FDA’s AA of malignant hematology and oncology from January 2000–December 2019 was reviewed. Dates from Health Canada, HTA decisions and provincial listings were collected. There were 94 FDA AAs, two of which were subsequently withdrawn. Of the 92 AAs, 70 received full (46)/conditional (24) Health Canada approval, and 22 were not filed. Since the introduction of HTA, 31 out of 45 of Health Canada’s approved indications underwent HTA review: 18 received a positive recommendation conditional on cost-effectiveness, 8 were not recommended and 5 were withdrawn/suspended. The median time from the AA to any Health Canada approval is 9.4 months, from any Health Canada approval to HTA decision is 5.8 months and from HTA decision to the first formulary listing is 12.0 months. The access and timeline for the first formulary listing differences were observed between the USA and Canada due to the decision of pharmaceutical companies to submit (or not) to regulatory/HTA bodies, national procedural delays with different healthcare delivery models and submission timelines. This study demonstrates that there is delayed access to promising new therapies in Canada