The link between objective facts and politically relevant beliefs is an essential mechanism for democratic accountability. Yet the bulk of empirical work on this topic measures objective facts at whatever geographic units are readily available. We investigate the implications of these largely arbitrary choices for predicting individual-level opinions. We show that varying the geographic resolution—namely aggregating economic data to different geographic units—influences the strength of the relationship between economic evaluations and local economic conditions. Finding that unemployment claims are the best predictor of economic evaluations, especially when aggregated at the commuting zone or media market level, we underscore the importance of the modifiable areal unit problem. Our methods provide an example of how applied scholars might investigate the importance of geography in their own research going forward.

Research on partisan motivated reasoning shows that citizens perceive the world differently based upon their partisan allegiances. Here we marshal evidence from several national surveys to investigate whether partisan motivated reasoning is attenuated among partisans situated within disagreeable political discussion networks. While our analyses suggest that exposure to interpersonal disagreement is associated with weaker partisan identities, we find limited evidence that disagreement attenuates partisan differences in knowledge or retrospective evaluations of the economy. This suggests that interpersonal disagreement is unlikely to help reduce partisan motivated reasoning. Our results thus speak to important debates concerning the influence of social discussion on political attitudes, the nature of partisan motivated reasoning and the ability of citizens to hold elites accountable.

Objectives: The aim of this study was to present the updated methodological guidelines for economic evaluations of healthcare interventions (drugs, medical devices, and other interventions) in Belgium.

Methods: The update of the guidelines was performed by three Belgian health economists following feedback from users of the former guidelines and personal experience. The updated guidelines were discussed with a multidisciplinary team consisting of other health economists, assessors of reimbursement request files, representatives of Belgian databases and representatives of the drugs and medical devices industry. The final document was validated by three external validators that were not involved in the previous discussions.

Results: The guidelines give methodological guidance for the following components of an economic evaluation: literature review, perspective of the evaluation, definition of the target population, choice of the comparator, analytic technique and study design, calculation of costs, valuation of outcomes, definition of the time horizon, modeling, handling uncertainty and discounting. We present a reference case that can be considered as the minimal requirement for Belgian economic evaluations of health interventions.

Conclusions: These guidelines will improve the methodological quality, transparency and uniformity of the economic evaluations performed in Belgium. The guidelines will also provide support to the researchers and assessors performing or evaluating economic evaluations.

Objectives: The aim of this study was to present a review of economic evaluations conducted from a Canadian perspective and to characterize sources of evidence and statistical methods to analyze effectiveness measures, resource utilization, and uncertainty.

Methods: A search strategy was developed to identify Canadian economic evaluations published between January 2001 and June 2006. A standardized abstraction form was used to extract key data (e.g., study design, data sources, statistical methods).

Results: A total of 153 unique studies were included for review, of which 75 were evaluations of drug therapies and less than half were funded by industry. Cost-effectiveness analysis was the most common type of economic evaluation and 80 percent of the studies used modeling techniques. A single source of evidence for effectiveness measures was used in half of the studies. Statistical methods were commonly reported to compare effectiveness measures when the economic evaluation was conducted alongside a clinical trial but less commonly when determining effectiveness input parameters in model-based economic evaluations, or to analyze resource utilization data. Authors relied mostly on univariate sensitivity analyses to explore uncertainty.

Conclusions: This review identifies the need to improve the conduct and reporting of statistical methods for economic evaluations to improve confidence in the results.

Objectives: To examine the production of Health Technology Assessments (HTAs) with economic evaluations (EEs) conducted by Canadian HTA agencies.

Methods: This research used a three-step approach: (i) the Web sites of five Canadian organizations promoting HTA were searched to identify HTA reports with EEs; (ii) HTA agencies were surveyed to verify that our information was complete with respect to HTA activities and to describe the factors that influence the HTA process in Canada (i.e., selection of HTA topics, execution, dissemination of results and future trends); (iii) HTAs with EEs were appraised in terms of study design, retrieval of clinical and economic evidence, resource utilization and costing, effectiveness measures, treatment of uncertainty as well as presence of a budget impact analysis (BIA), and policy recommendations.

Results: Two hundred forty-nine HTA reports were identified of which 19 percent included EEs (n = 48). Decision analytic techniques were used in approximately 75 percent of the forty-eight EEs and probabilistic sensitivity analyses were commonly used by all agencies to deal with parameter uncertainty. BIAs or policy recommendations were given in 50 percent of the evaluations. Differences between agencies were observed in terms of selection of topics, focus of assessment and production of HTA (e.g., in-house activities). Major barriers to the conduct of HTAs with EEs were capacity, a lack of interest by decision makers and a lack of robust clinical information.

Conclusions: The results of this research point to the need for increased HTA training, collaboration, evidence synthesis, and use of pragmatic “real world” evaluations.

Increasingly, health technology assessment (HTA) is used to aid decisions on the reimbursement of pharmaceuticals or recommendations for their use. The pharmaceutical industry seeks to work in partnership with HTA agencies; however, this presents a number of challenges. Clinical trials will need to include appropriate measures that capture economic and patient benefits as well as relevant clinical endpoints, and the industry will want to seek international harmonization of the many guidelines for economic evaluation. The problem of demonstrating cost-effectiveness of a product before it is available for use must be addressed, possibly by conditional reimbursement to allow collection of real world evidence. It is also important that reimbursement decision makers minimize bias, play fair, and adhere to the written rules they issue. If the industry fairly demonstrates the value of a product using the best available evidence, HTA agencies should be transparent in the rationale for their recommendations.