Providing scientific advice and recommendations for public decision making entails identifying, selecting and weighing evidence derived from multiple sources of information through a systematic approach, while taking into account ethical, cultural and societal factors. Integrated in the evaluation process are exchanges between regulatory agencies, private firms, scientific experts and government representatives. In the case of drugs and medical devices, health technology assessment (HTA) agencies are increasingly commissioned to evaluate innovations in order to provide government with recommendations and advice on reimbursement and/or pricing. To undertake this task, HTA agencies [1–6] in Europe and elsewhere have developed methodological guidelines on the economic evaluation of health technologies [7]. One component of these guidelines deals with ways for both manufacturers (pharmaceutical and medical device firms) and HTA agencies evaluators (modelers, economists and public health experts) to address uncertainty. Several types of uncertainty have indeed been identified in HTA: methodological, parameter and structural uncertainty. Most guidelines describe quite well how to deal with the first two categories, although there is still room for improvement. However, recommendations about how to tackle structural uncertainty remain largely elusive. HTA agencies and decision makers may thus be exposed to oversimplifying assessments and recommendations by putting aside complex forms of uncertainty such as struc-tural ‘deep’ uncertainty [8]. The editorial is not intended to promote new approaches to exploring structural uncertainty, rather to emphasizeconcerns related to the topic, such as definition and analysis. Our aim is therefore to highlight the need to renew the analytical framework guidance for HTA.