Objectives: A linked evidence approach (LEA) is the synthesis of systematically acquired evidence on the accuracy of a medical test, its impact on clinical decision making and the effectiveness of consequent treatment options. We aimed to assess the practical utility of this methodology and to develop a decision framework to guide its use.

Methods: As Australia has lengthy experience with LEA, we reviewed health technology assessment (HTA) reports informing reimbursement decisions by the Medical Services Advisory Committee (August 2005 to March 2012). Eligibility was determined according to predetermined criteria and data were extracted on test characteristics, evaluation methodologies, and reported difficulties. Fifty percent of the evidence-base was independently analyzed by a second reviewer.

Results: Evaluations of medical tests for diagnostic (62 percent), staging (27 percent), and screening (6 percent) purposes were available for eighty-nine different clinical indications. Ninety-six percent of the evaluations used either the full LEA methodology or an abridged version (where evidence is linked through to management changes but not patient outcomes). Sixty-one percent had the full evidence linkage. Twenty-five percent of test evaluations were considered problematic; all involving LEA (n = 22). Problems included: determining test accuracy with an imperfect reference standard (41 percent); assessing likely treatment effectiveness in test positive patients when the new test is more accurate than the comparator (18 percent); and determining probable health benefits in those symptomatic patients ruled out using the test (13 percent). A decision framework was formulated to address these problems.

Conclusions: LEA is useful for evaluating medical tests but a stepped approach should be followed to determine what evidence is required for the synthesis.

Objectives: To promote the further development of HTA, this study aims to design a model for HTA priority setting, which would address national needs for a country with little experience in the field of HTA, and assess its feasibility for the health system.

Methods: Literature search and review, as well as qualitative research have been used in the design and testing of the model for HTA priority setting. To test the model and the methodology, a three-round Delphi study was conducted in 2011 in the form of an electronic questionnaire, which was distributed to the panel of eleven national experts. The panel was composed of experts representing various fields of the health care sector: policy-makers, health care service professionals and academics, with diverse professional roles.

Results: The designed model consists of four stages: (i) selection of experts for the panel, (ii) indication and selection of health policy topics, (iii) identification of health technologies, and (iv) priority setting. Three rounds of the Delphi study were performed to test the model and reach expert consensus on a list of health technologies for assessment, including pharmaceuticals, vaccines, medical devices, diagnostic methods, public health interventions, organizational systems, etc.

Conclusions: Based on the Delphi technique as a method for consensus building, the model for HTA priority setting was developed for Lithuania; however, it could also be used for other countries with little experience in the field of HTA.

Objectives: The aim of this study was to gather qualitative and quantitative data on criteria considered by healthcare decision makers.

Methods: Using snowball sampling and an online questionnaire with forty-three criteria organized into ten clusters, decision makers were invited by an international task force to report which criteria they consider when making decisions on healthcare interventions in their context. Respondents reported whether each criterion is “currently considered,” “should be considered,” and its relative weight (scale 0–5). Differences in proportions of respondents were explored with inferential statistics across levels of decision (micro, meso, macro), decision maker perspectives, and world regions.

Results: A total of 140 decision makers (1/3 clinical, 2/3 policy) from 23 countries in five continents completed the survey. The most relevant criteria (top ranked for “Currently considered,” “Should be considered,” and weights) were Clinical efficacy/effectiveness, Safety, Quality of evidence, Disease severity, and Impact on healthcare costs. Organizational and skill requirements were frequently considered but had relatively low weights. For almost all criteria, a higher proportion of decision makers reported that they “Should be considered” than that they are “Currently considered” (p < .05). For more than 74 percent of criteria, there were no statistical differences in proportions across levels of decision, perspectives and world regions. Statistically significant differences across several comparisons were found for: Population priorities, Stakeholder pressure/interests, Capacity to stimulate research, Impact on partnership and collaboration, and Environmental impact.

Conclusions: Results suggest convergence among decision makers on the relevance of a core set of criteria and on the need to consider a wider range of criteria. Areas of divergence appear to be principally related to contextual factors.

In the original publication of ‘Assessing the Impacts of Citizen Deliberations on the Health Technology Process’ the title was published incorrectly. The correct title should be: Assessing the Impacts of Citizen Deliberations on the Health Technology Assessment Process. The publisher regrets this error.