Identification of causal effects on binary outcomes using structural mean models

Structural mean models (SMMs) were originally formulated to estimate causal effects among those selecting treatment in randomized controlled trials affected by nonignorable noncompliance. It has already been established that SMMs can identify these causal effects in randomized placebo-controlled trials under fairly weak assumptions. SMMs are now being used to analyze other types of study where identification depends on a no effect modification assumption. We highlight how this assumption depends crucially on the unknown causal model that generated the data, and so is difficult to justify. However, we also highlight that, if treatment selection is monotonic, additive and multiplicative SMMs do identify local (or complier) causal effects, but that the double-logistic SMM estimator does not without further assumptions. We clarify the proper interpretation of inferences from SMMs by means of an application and a simulation study. © 2010 The Author

From efficacy to equity: Literature review of decision criteria for resource allocation and healthcare decisionmaking

Objectives Resource allocation is a challenging issue faced by health policy decisionmakers requiring careful consideration of many factors. Objectives of this study were to identify decision criteria and their frequency reported in the literature on healthcare decisionmaking. Method An extensive literature search was performed in Medline and EMBASE to identify articles reporting healthcare decision criteria. Studies conducted with decisionmakers (e.g., focus groups, surveys, interviews), conceptual and review articles and articles describing multicriteria tools were included. Criteria were extracted, organized using a classification system derived from the EVIDEM framework and applying multicriteria decision analysis (MCDA) principles, and the frequency of their occurrence was measured. Results Out of 3146 records identified, 2790 were excluded. Out of 356 articles assessed for eligibility, 40 studies included. Criteria were identified from studies performed in several regions of the world involving decisionmakers at micro, meso and macro levels of decision and from studies reporting on multicriteria tools. Large variations in terminology used to define criteria were observed and 360 different terms were identified. These were assigned to 58 criteria which were classified in 9 different categories including: health outcomes; types of benefit; disease impact; therapeutic context; economic impact; quality of evidence; implementation complexity; priority, fairness and ethics; and overall context. The most frequently mentioned criteria were: equity/fairness (32 times), efficacy/effectiveness (29), stakeholder interests and pressures (28), cost-effectiveness (23), strength of evidence (20), safety (19), mission and mandate of health system (19), organizational requirements and capacity (17), patient-reported outcomes (17) and need (16). Conclusion This study highlights the importance of considering both normative and feasibility criteria for fair allocation of resources and optimized decisionmaking for coverage and use of healthcare interventions. This analysis provides a foundation to develop a questionnaire for an international survey of decisionmakers on criteria and their relative importance. The ultimate objective is to develop sound multicriteria approaches to enlighten healthcare decisionmaking and priority-settin

Species relationships in the genus Vasconcellea (Caricaceae) based on molecular and morphological evidence

Validity of the taxa currently recognized in the genus Vasconcellea was analyzed by investigating morphological and molecular data from 105 specimens of this genus and six specimens of the related genus Carica. Taxon identification of these specimens was compared with clustering in two phenetic dendrograms generated with 36 morphological characters and 254 amplified fragment length polymorphic (AFLP) markers. Moreover, cytoplasmic haplotypes were assessed using polymerase chain reaction restriction fragment length polymorphism (PCR-RFLP) of one mitochondrial and two chloroplast DNA regions. Results show that the morphological data set, containing mainly vegetative characteristics, merely reveals external resemblance between specimens, which is not directly associated with genetic relationships and taxon validity. Phenotypic plasticity and intercompatibility between several species are likely to confuse morphological delimitation of the taxa. Based on the results of our study, several specimens that could not be identified with the currently used identification key (1) could be attributed to a known taxon, which should be extended to include a higher range of morphological variability or (2) could be hypothesized to be of hybrid origin. Because of the high intraspecific variation within V. microcarpa and V. X heilbornii, revision of these taxa is recommended

Stakeholder involvement in Multi-Criteria Decision Analysis

This brief perspective highlights the importance of decision maker buy-in and ownership through stakeholder engagement in the co-construction of the multi-criteria decision analysis (MCDA) model. A brief historical overview of MCDA is presented before outlining the importance of bridging the gap (and to gain trust) between the tool developers and users. The issues with the current MCDA tool development and testing efforts are highlighted, and the ownership and routine adoption of the MCDA process is discussed

Bridging health technology assessment (HTA) with multicriteria decision analyses (MCDA): field testing of the EVIDEM framework for coverage decisions by a public payer in Canada

<p>Abstract</p> <p>Background</p> <p>Consistent healthcare decisionmaking requires systematic consideration of decision criteria and evidence available to inform them. This can be tackled by combining multicriteria decision analysis (MCDA) and Health Technology Assessment (HTA). The objective of this study was to field-test a decision support framework (EVIDEM), explore its utility to a drug advisory committee and test its reliability over time.</p> <p>Methods</p> <p>Tramadol for chronic non-cancer pain was selected by the health plan as a case study relevant to their context. Based on extensive literature review, a by-criterion HTA report was developed to provide synthesized evidence for each criterion of the framework (14 criteria for the MCDA Core Model and 6 qualitative criteria for the Contextual Tool). During workshop sessions, committee members tested the framework in three steps by assigning: 1) weights to each criterion of the MCDA Core Model representing individual perspective; 2) scores for tramadol for each criterion of the MCDA Core Model using synthesized data; and 3) qualitative impacts of criteria of the Contextual Tool on the appraisal. Utility and reliability of the approach were explored through discussion, survey and test-retest. Agreement between test and retest data was analyzed by calculating intra-rater correlation coefficients (ICCs) for weights, scores and MCDA value estimates.</p> <p>Results</p> <p>The framework was found useful by the drug advisory committee in supporting systematic consideration of a broad range of criteria to promote a consistent approach to appraising healthcare interventions. Directly integrated in the framework as a "by-criterion" HTA report, synthesized evidence for each criterion facilitated its consideration, although this was sometimes limited by lack of relevant data. Test-retest analysis showed fair to good consistency of weights, scores and MCDA value estimates at the individual level (ICC ranging from 0.676 to 0.698), thus lending some support for the reliability of the approach. Overall, committee members endorsed the inclusion of most framework criteria and revealed important areas of discussion, clarification and adaptation of the framework to the needs of the committee.</p> <p>Conclusions</p> <p>By promoting systematic consideration of all decision criteria and the underlying evidence, the framework allows a consistent approach to appraising healthcare interventions. Further testing and validation are needed to advance MCDA approaches in healthcare decisionmaking.</p