OBJECTIVES: Apply a MCDA-based model to support and streamline policy and clinical decisionmaking for growth hormone (GH) therapy in patients with Prader-Willi syndrome (PWS), a rare genetic disorder with serious long-term consequences including short stature and morbid obesity. METHODS: An extensive literature review was performed to identify and synthesize available evidence  on GH for PWS for 19 criteria of the EVIDEM framework using a standardized methodology. Evidence tables, quality assessment of studies, and synthesis of data by criterion, were validated by a wide range of experts using an interactive web site. The framework was used to develop CPG questions and structure development of international recommendations during a consensus workshop. RESULTS: The web site provided transparent access to synthesized evidence at 3 levels of detail for 13 scientific criteria of the EVIDEM MCDA model including: disease severity, size of population, therapeutic context and unmet needs, treatment outcomes (efficacy/effectiveness, safety, patient-reported outcomes), type of treatment benefit at population and individual levels, and economic impact on medical and non-medical expenditures. Quality assessments of studies were hyperlinked to synthesized evidence. Evidence for the six contextual and ethical criteria, including utility, efficiency, fairness, system capacity, stakeholder pressures, and political/historical context, was synthesized. CPG questions were developed following this format. CONCLUSIONS: The “by criteria” web model provides a pragmatic means for systematic consideration of a wide range of criteria, seamless access to information and development of CPGs to guide evidence-based decisions. This work will serve to structure deliberations of a pan-Canadian taskforce to examine the conditions for successful implementation (obstacles and facilitating factors) of evidence-based CPG. The ultimate goal is to bridge the gap between researchers, policy decision-making, clinical practice and patient concerns to optimize resource allocation and health care system sustainability.