Objectives: The aim of this study was to compare Bayesian methods with the standard methods that are used for evidence-based policy making.

Methods: We performed a Bayesian reanalysis of the data underlying a reimbursement advice by the Dutch National Health Insurance Board (CVZ) regarding the anti-diabetic drug exenatide (an alternative to insulin). We synthesized evidence from various sources that was available when the CVZ advice was drafted: expert opinion (as elicited from internists), experimental data (from direct comparison studies), and observational data. Subsequently, the original frequentist results and the results from the Bayesian reanalysis were compared in terms of outcomes and interpretations. These results were presented in a meeting with staff from CVZ, whose opinions about the usefulness of a Bayesian approach were assessed using a questionnaire.

Results: The Bayesian approach yields outcomes that summarize different pieces of evidence, which would have been difficult to obtain otherwise. Moreover, there are conceptual differences, and the Bayesian approach allows for determining probabilities of clinically relevant differences. The staff at CVZ were fairly positive with respect to the use of Bayesian methods, although practical barriers were also seen as important.

Conclusions: The Bayesian outcomes are different and could be more suited to the informational needs of policy makers. The response from staff at CVZ provides some support for this statement, but more research at the interface of science and policy is needed.

Background: Many jurisdictions delivering health care, including Canada, have developed guidance for conducting economic evaluation, often in the service of larger health technology assessment (HTA) and reimbursement processes. Like any health intervention, personalized medical (PM) interventions have costs and consequences that must be considered by reimbursement authorities with limited resources. However, current approaches to economic evaluation to support decision making have been largely developed from population-based approaches to therapy—that is, evaluating the costs and consequences of single interventions across single populations. This raises the issue as to whether these methods, as they are or more refined, are adequate to address more targeted approaches to therapy, or whether a new paradigm for assessing value in PM is required.

Objectives: We describe specific issues relevant to the economic evaluation of diagnostics-based PM and assess whether current guidance for economic evaluation is sufficient to support decision making for PM interventions.

Methods: Issues were identified through literature review and informal interviews with national and international experts (n = 10) in these analyses. This article elaborates on findings and discussion at a workshop held in Ottawa, Canada, in January 2012.

Results: Specific issues related to better guiding economic evaluation of personalized medicine interventions include: how study questions are developed, populations are characterized, comparators are defined, effectiveness is evaluated, outcomes are valued and how resources are measured. Diagnostics-based PM also highlights the need for analyses outside of economic evaluation to support decision making.

Conclusions: The consensus of this group of experts is that the economic evaluation of diagnostics-based PM may not require a new paradigm. However, greater complexity means that existing approaches and tools may require improvement to undertake these more analyses.

Similar to the triaging of patients by health care workers, legal and public health professionals must prioritize and respond to issues of law and ethics in declared public health emergencies. As revealed by the 2009-2010 H1N1 influenza outbreak and other events, there are considerable inconsistencies among professionals regarding how to best approach these issues during a public health emergency. Our project explores these inconsistencies by attempting to assess how practitioners make legal and ethical decisions in real-time emergencies to further critical public health objectives. Using a fictitious scenario and interactive visualization environment, we observed real-time decision-making processes among knowledgeable participants. Although participants' decisions and perspectives varied, the exercise demonstrated an increase in the perception of the relevance of legal preparedness in multiple aspects of the decision-making process and some key lessons learned for consideration in future repetitions of the exercise and actual, real-time emergency events.

(Disaster Med Public Health Preparedness. 2011;5:S242-S251)

Aim – To develop predictive models to allocate patients into frequent and low service users groups within the Italian Community-based Mental Health Services (CMHSs). To allocate frequent users to different packages of care, identifing the costs of these packages. Methods – Socio-demographic and clinical data and GAF scores at baseline were collected for 1250 users attending five CMHSs. All psychiatric contacts made by these patients during six months were recorded. A logistic regression identified frequent service users predictive variables. Multinomial logistic regression identified variables able to predict the most appropriate package of care. A cost function was utilised to estimate costs. Results – Frequent service users were 49%, using nearly 90% of all contacts. The model classified correctly 80% of users in the frequent and low users groups. Three packages of care were identified: Basic Community Treatment (4,133 Euro per six months); Intensive Community Treatment (6,180 Euro) and Rehabilitative Community Treatment (11,984 Euro) for 83%, 6% and 11% of frequent service users respectively. The model was found to be accurate for 85% of users. Conclusion – It is possible to develop predictive models to identify frequent service users and to assign them to pre-defined packages of care, and to use these models to inform the funding of psychiatric care.

Objectives: Controversy exists regarding the optimal method of providing dialysis in critically ill patients with acute renal failure. We sought to determine the cost-effectiveness of treatment strategies.

Methods: Adult subjects requiring renal replacement therapy in a critical care setting who are candidates for intermittent hemodialysis (IHD) or continuous renal replacement therapy (CRRT) were considered within a Markov model. Alternative strategies including IHD, and standard or high dose CRRT were compared. The model considered relevant clinical and economic outcomes, and incorporated data on clinical effectiveness from a recent systematic review and high quality micro-costing data.

Results: In the base-case analysis, CRRT was associated with similar health outcomes but higher costs by ($3,679 more than IHD per patient). In scenarios considering alternate cost sources, and higher intensity of IHD (including daily and longer duration IHD), CRRT remained more costly. Sensitivity analysis indicated that even small differences in the risk of mortality or need for long-term chronic dialysis therapy among surviving patients benefits led to dramatic changes in the cost-effectiveness of the modalities considered.

Conclusions: Given the higher costs of providing CRRT and absence of demonstrated benefit, IHD is the preferred modality in critically ill patients who are candidates for either IHD or CRRT, although this conclusion should be revisited if future clinical trials establish differences in clinical effectiveness between modalities. Future interventions that are proven to improve renal recovery after acute renal failure are likely to be cost-effective, even if very resource intensive.

Objectives: The objective of this study was to analyze preferences for activities comprised in comprehensive cardiac rehabilitation programs among former cardiac patients from three different hospitals in Copenhagen County, Denmark.

Methods: A discrete choice experiment was applied to elicit the preferences for the offer of participation in various cardiac rehabilitation program activities: smoking cessation course, physical exercise program, personal meetings with cardiac nurse, group meetings managed by cardiac nurses, and nutritional counseling guidance. The questionnaire was sent to 742 former cardiac patients. We had a response rate of 69 percent.

Results: We found that preferences differed with respect to gender and age and that the offer of participation in cardiac rehabilitation activities was not highly valued by older patients, in particular among older men.

Conclusions: The discrete choice experiment proved a valuable instrument for the measurement of preferences for cardiac rehabilitation. The study provides important information on patients' preferences for cardiac rehabilitation for healthcare professionals and decision makers.

Objectives: The aim of the study was to investigate the feasibility and effectiveness of searching selected databases to identify information required to populate a decision-analytic model.

Methods: Methods of searching for information to populate a decision-analytic model were piloted using a case study of prophylactic antibiotics to prevent recurrent urinary tract infections in children. This study explored how the information requirements for a decision-analytic model could be developed into searchable questions and how search strategies could be derived to answer these questions. The study also assessed the usefulness of three published search filters and explored which resources might produce relevant information for the various model parameters.

Results: Based on the data requirements for this case study, 42 questions were developed for searching. These questions related to baseline event rates, health-related quality of life and outcomes, relative treatment effects, resource use and unit costs, and antibiotic resistance. A total of 1,237 records were assessed by the modeler, and of these, 48 were found to be relevant to the model. Search precision ranged from 0 percent to 38 percent, and no single database proved the most useful for all the questions.

Conclusions: The process of conducting specific searches to address each of the model questions provided information that was useful in populating the case study model. The most appropriate resources to search were dependent on the question, and multiple database searching using focused search strategies may prove more effective in finding relevant data than thorough searches of a single database.

Objectives: Many evaluations underestimate the utility associated with diagnostic interventions by failing to capture the nonclinical value of diagnostic information. This is a cause of bias in resource allocation decisions. A study was undertaken to investigate preferences for the assessment of cardiac risk, testing the suitability of conjoint analysis, a multiattribute preference elicitation method, in the field of clinical diagnosis.

Methods: Two conjoint analysis models focusing on selected characteristics of cardiac risk assessment in asymptomatic patients 40–50 years of age were applied to elicit preferences for cardiac risk assessment from samples of general practitioners and the general public in the United Kingdom and Italy. Both models were based on rankings of alternative scenarios, and the results were analyzed using multivariate analysis of variance and an ordered probit model.

Results: In both countries, members of the public attached at least three times more importance to prognostic value (relative to clinical value) than did general practitioners. Significantly different patterns were found in the two countries with regard to other characteristics of the assessment. Variation within samples was partly associated with personal characteristics.

Conclusions: Only a fraction of the value of cardiac risk assessment to individuals and physicians in this study was linked to health outcomes. The study confirmed the appropriateness and validity of conjoint analysis in the assessment of preferences for diagnostic interventions. A wider use of this technique might significantly strengthen the existing evidence-base for diagnostic interventions, leading to a more efficient use of health-care resources.

Objectives: To assess the cost-effectiveness of alternative initial strategies in the management of uninvestigated dyspepsia in adult patients presenting to a primary care physician in Canada.

Methods: Clinical decision-making was modeled based on outcomes data from the literature and expert opinion. Costs were obtained from official reimbursement lists, and a detailed microcosting analysis of a gastroscopy. Costs were analysed over a one-year period after initial presentation, including consideration of a single relapse of symptoms. The main outcome was a symptomatic cure. The seven management strategies based on different initial tests were endoscopy, double-contrast barium meal, empirical eradication therapy, empirical antisecretory treatment, urea breath test (UBT), laboratory serology, and sequential testing (laboratory serology followed, if Helicobacter pylori positive, by UBT).

Results: In patients under age 45, endoscopy, double-contrast barium meal, and sequential testing were not cost-effective approaches. UBT was the most effective and most costly strategy costing $8,238 per additional patient cure compared with laboratory serology. In patients over age 45, UBT was again the most effective and most costly strategy, but endoscopy was the most reliable in detecting gastric cancers. Clinical variables that impacted these findings were the probability of symptomatic relapse in patients with nonulcer dyspepsia (NUD) after successful versus failed H. pylori eradication, the probability of finding a duodenal ulcer (DU) in a young dyspeptic patient, the specificity of UBT, and the prevalence of H. pylori in patients with DU.

Conclusions: A “test-and-treat” approach was favored, with UBT being the most effective but most costly initial test in adult dyspeptics under age 45. The choice of the most cost-effective approach is dependent on the benefits of H. pylori eradication in patients with NUD. In patients over age 45, UBT is the most effective and most costly, but endoscopy results in the early detection of most gastric cancers.The authors are indebted to the other members of the UBTAN Group, including Drs. Phil Sherman, Alan Thomson, and Sander Veldhuyzen van Zanten. The authors also thank Paul Sinclair, Eileen Grace, and Lawrence Joseph for their much valued comments and opinions.AB and CAF are research scholars of the Fonds de la Recherche en Santé du Québec. This work was supported in part by an “at arms length” grant from AstraZeneca Canada.

Objectives: Setting funding priorities among research projects for complementary and alternative therapies is especially vulnerable to arbitrary, partisan criteria and opportunistic readings of controversial evidence. This study develops a procedural approach to characterizing, in a transparent and even-handed way, the available evidence on these treatments and demonstrates a simple analytical scheme for prioritizing competing, but typically incommensurable, research projects for public support.

Methods: A simple five-step scheme for categorizing therapies is developed and justified, based on a taxonomy of the study designs used to generate research evidence. Once identified, candidate therapies are assigned to ordered categories along these design criteria and effectively grouped into equivalence classes by type of evidence. Finally, a partial ordering on the therapies is formed within each class by means of secondary screening criteria.

Results: Twenty-five candidate therapies are assigned to equivalence classes. The intent, in effect, is to restrict comparisons to those therapies that fall within a particular class of similar study designs. Within-class orderings avoid the problem of having better-known or better-supported therapies crowd out lesser known ones when it comes to allocating dollars for more research. A set of criteria and procedure for prioritizing spending for further research is demonstrated.

Conclusions: Relying on an open, formal procedure for comparing unconventional therapies offers protection against prejudgment in setting funding priorities, especially when weak clinical evidence relates more to a low investment in research than lack of efficacy.Special thanks are due to Mary Ann Richardson, DrPH, formerly of the UT School of Public Health, currently with the National Center for Complementary and Alternative Medicine, National Institutes of Health, Bethesda, Maryland. Dr. Richardson introduced me to this problem and graciously provided information on several unconventional therapies. Partial funding was provided by UT's Center for Alternative Medicine through a contract with the Office of Alternative Medicine, U.S. National Institutes of Health.

Objective: Our study aims to provide a practical contribution to the field of medical technology assessment within a new paradigm. This paradigm indicates the need for more comprehensive technology assessments in the development stage of a new technology.

Method: We introduce a method, based on Saaty's Analytic Hierarchy Process, which quantitatively supports discussions between the various actors that shape the technology's development and diffusion. These discussions focus on technical, medical, social, and economical requirements relevant to the design and diffusion of the new technology.

Discussion: In contrast to more traditional technology assessments, our method encompasses the perspectives of the diverse actors in the social context of technology development and diffusion. It influences their decision making on technology design and diffusion in order to improve this technology's later clinical as well as social effectiveness.

Objective: To adjust patients' time trade-off (TTO) scores using information on their utility functions for survival time to derive a measure of health state utility equivalent to the standard gamble (SG).

Methods: A sample of 199 cardiovascular patients were asked three TTO and SG questions (to assess their own health state), and three certainty equivalent questions (to assess their utility function for survival time) in an interview.

Results: Patients' utility functions for time were increasingly concave, but being unable to model this successfully, a constant function with an averaged level of concavity was used. The raw TTO scores were significantly higher than SG scores, while the adjusted TTO scores were equivalent to the SG.

Conclusions: Raw time trade-off scores will give biased estimates of health state utility when patients' utility functions for time are not linear, but these can be adjusted to yield true utilities. The constant proportional risk-posture assumption of the conventional QALY model, on which previous attempts to adjust time trade-offs have been based, was not supported by the data.