Objectives: The objective of this study was to explore barriers and facilitators influencing the integration of ethical considerations in health technology assessment (HTA).

Methods: The study consisted of two complementary approaches: (a) a systematic review of the literature; and (b) an eighteen-item online survey that was distributed to fifty-six HTA agencies affiliated with the International Network of Agencies for Health Technology Assessment.

Results: The review identified twenty-six relevant articles. The most often cited barriers in the literature were: scarcity, heterogeneity and complexity of ethical analysis methods; challenges in translating ethical analysis results into knowledge that is useful for decision makers; and lack of organizational support in terms of required expertise, time and financial resources. The most frequently cited facilitators included: usage of value-based appraisal methods, stakeholder and public engagement, enhancement of practice guidelines, ethical expertise, and educational interventions.

Representatives of twenty-six (46.5 percent) agencies from nineteen countries completed the survey. A median of 10 percent (interquartile range, 5 percent to 50 percent) of the HTA products produced by the agencies was reported to include an assessment of ethical aspects. The most commonly perceived barriers were: limited ethical knowledge and expertise, insufficient time and resources, and difficulties in finding ethical evidence or using ethical guidelines. Educational interventions, demand by policy makers, and involvement of ethicists in HTA were the most commonly perceived facilitators.

Conclusions: Our results emphasize the importance of simplification of ethics methodology and development of good practice guidelines in HTA, as well as capacity building for engaging HTA practitioners in ethical analyses.

Objectives: Approximately 10–15 percent of individuals with diabetes mellitus develop foot ulcers, which precede 85 percent of amputations. Increased oxygen, through the use of hyperbaric oxygen therapy (HBOT), has been suggested to encourage ulcer healing thus reducing the risk of amputation. The objective of this systematic review is to evaluate the efficacy of systemic HBOT for nonhealing ulcers of the lower limb in diabetes patients.

Methods: A systematic search, using controlled and keyword terms focusing on “HBOT” and “lower limb diabetic ulcers,” was conducted. Databases searched included Medline, EMBASE, CINAHL, PubMed, Wiley's Cochrane Library, and Biosis. Randomized controlled trials (RCTs) and observational studies were included. Pooled estimates of outcomes were determined when appropriate.

Results: Of the 654 citations identified, 157 articles underwent full-text review. Data were abstracted from twelve publications (six RCTs and six comparative observational studies). Pooled analysis of the RCT and observational data showed that treatment with HBOT reduced the risk of major amputation by 60 percent (p = .29) and 61 percent (p = .003) compared with standard wound care, respectively. The RCT data revealed that the relative risk of having an unhealed wound following HBOT was 0.54 (p = .10) and 0.24 (p < .0001) based on observational data.

Conclusions: Due to the limited RCT evidence, it is not possible to conclusively establish the benefits and harms of treating diabetic lower limb ulcers with HBOT. No significant effects on amputation rates were found in the RCT evidence and in the high quality studies, no difference was found.

A decision analytic model often comprises a significant part of a health technology assessment. As health technology assessment in the hospital setting evolves, there is an increased need for modeling methods that account for patient care pathways and interactions between patients and their environment. For example, an evaluation of a computed tomography (CT) scanner for a new indication would need to consider the current and increased demand of the machine and how that may affect service in other areas of the hospital. This problem solving approach views “problems” through a systems perspective.

Objective – To determine the most cost-effective oral therapy for the treatment of Major Depressive Disorder (MDD) in Italy. Method – We conducted a pharmacoeconomic evaluation based on a decision analytic model that examined the treatment of major depressive disorder (MDD) in Italy. The analysis compared the serotonin norepinephrine reuptake inhibitor (SNRI), venlafaxine extended-release (venlafaxine XR), to selective serotonin reuptake inhibitors (SSRIs) and tricyclic antidepressants (TCAs). A meta-analysis was performed to determine the clinical rates of success. The meta-analytic rates were applied to the decision analytic model to calculate the expected cost and expected outcomes for each anti-depressant comparator. Cost-effectiveness was determined using the expected values for both a successful outcome, and a composite measure of outcome termed ‘symptom-free days’. A policy analysis was conducted to estimate the financial impact to the Servizio Sanitario Nazionale (SSN). Results – Treatment of MDD with venlafaxine XR yielded the highest overall efficacy rates for outpatients (73.7%) versus SSRIs (61.4%) and TCAs (59.3%), and inpatients (62.3%) versus SSRIs (58.6%) and TCAs (58.2%). Venlafaxine XR had the lowest dropout rates due to lack of efficacy (4.8%) versus SSRIs (8.4%) and TCAs (6.8%), and adverse drug reactions (10.9%) versus SSRIs (17.4%) and TCAs (23.1%). Initiating treatment of MDD with venlafaxine XR yielded the lowest expected cost for outpatients and for inpatients. The total resulting savings for the SSN at a 5% venlafaxine XR utilization was estimated between L 963 million and L 3,210 million. Conclusion – This study confirms that venlafaxine XR is generally a cost-effective treatment of MDD. Additionally, the results of this investigation suggest that increased utilization of venlafaxine XR will favorably impact the SSN.

Objectives: Due to potential advantages (e.g., using all available evidence), Bayesian methods have been proposed to assist healthcare decision making. This review provides a detailed description of how Bayesian methods have been applied to economic evaluations of patient level data. The results serve both as a reference and as a means by which to examine the appropriate application of Bayesian methods to inform decision making.

Methods: MEDLINE, EMBASE, and Cochrane Economic Evaluation databases were searched to identify studies, published up to November 2007, meeting three inclusion criteria: (i) the study conducted an economic evaluation, (ii) sampling uncertainty was incorporated using Bayesian methods, (iii) the likelihood function was informed by patient level data from a single source. Data were collected on key study characteristics (e.g., prior distribution, likelihood function, presentation of uncertainty).

Results: The search identified 366 potentially relevant studies, from which 103 studies underwent full-text review. Sixteen studies met the inclusion criteria. Half of the studies used uninformative priors; most studies incorporated the potential dependence between costs and effects, and presented cost-effectiveness acceptability curves. Results were sensitive to changes in the priors and likelihoods.

Conclusions: Limited use of informative priors, among the included studies, gives policy makers little guidance on one of the main benefits of Bayesian methods, the ability to integrate all available evidence to capture the uncertainty inherent in decision making.

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 determine the cost-effectiveness (CE) and cost-utility (CU) of drug-eluting stents (DES) compared to bare metal stents (BMS) in Ontario using a large prospective “real-world” cohort study and determine the extent to which results vary by patient risk subgroups.

Methods: A field evaluation was conducted based on all stent procedures in the province of Ontario between December 1, 2003, and March 31, 2005, with a minimum subject follow-up of 1 year. Effectiveness data from the study using a propensity-score matched cohort were combined with resource utilization and cost data and quality of life (QOL) data from the published literature in a decision analytic modeling framework to determine 2-year cost-effectiveness (cost per revascularization avoided) and cost-utility (cost per quality-adjusted life-year ([QALY] gained). Stochastic model parameter uncertainty was expressed using probability distributions and analyzed using a probabilistic model. Modeling assumptions were assessed using traditional deterministic sensitivity analysis.

Results: Significant differences in revascularization rates were found for patients with two or more high risk factors. Despite these differences, the CE and CU of DES remained high (e.g., $419,000 per QALY gained in the most favorable patient risk subgroup). In sensitivity analysis, the difference in cost between DES and BMS had an impact on the CE and CU results. For example, at a price differential of $500, the CU of DES was $20,000/QALY for one patient subgroup and DES was dominant (i.e., less costly and more effective) in another.

Conclusions: At current prices, the CE/CU of DES compared with BMS is high even in patient high risk subgroups. As the relative price of DES decrease, the value for money attractiveness of DES increases, especially for selected high risk patients.

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.

Objectives: Erectile dysfunction (ED) is a complex condition, which is variously influenced by physical, emotional, societal, and relationship factors. ED has serious implications for the quality of life (QoL) enjoyed by an affected male and his partner. It is very important, therefore, to understand the impact of ED on the QoL of those affected by it. Our objective was to determine if the eight-question Patient Reported Erectile Function Assessment (PREFA) could act as an independent, comprehensive disease-specific instrument in the assessment of QoL as it is impacted by ED.

Methods: During the development and validation of the Erectile Function–Visual Analog Scale (EF-VAS) (14), a new ED-specific preference-based instrument, a series of questions were included at the beginning of the assessment that would act as a way to encourage respondents to focus on their own experience with ED. Upon analysis of the EF-VAS data, it became apparent that the eight-question “warm up” section might act as a stand-alone assessment. Accordingly, the eight questions were named PREFA, and a validation analysis was undertaken to determine their consistency, feasibility, reliability, validity, and responsiveness.

Results: The PREFA questionnaire was found to be feasible and simple to complete, reliable, and valid, with excellent responsiveness. Overall, the PREFA has demonstrated that it can perform as a stand alone, validated assessment of the impact of ED on QoL, assessing areas of QoL not previously captured in existing instruments.

Conclusions: The PREFA is suitable for use in clinical and research settings as a disease-specific QoL assessment tool.