Patient preferences (PPs) are an important source of evidence in health technology assessment (HTA). However, a methodological framework to achieve their integration in decision-making is lacking. We aim to investigate the potential role of evaluative frameworks to integrate PP evidence into HTA and decision-making.

We undertook a scoping review to identify potential methodological frameworks to consider PP evidence in HTA and evidence of the acceptability of these frameworks for decision-makers. We searched PubMed, Cochrane, and the grey literature to identify relevant studies, reports, or guidance documents. We restricted our search to the use of PP rather than patient experience data and excluded articles solely relating to deliberative approaches.

Frameworks identified as having the potential to integrate PP evidence included cost-utility analysis, cost-consequence analysis (CCA), the efficiency-frontier approach, and multi-criteria decision analysis. All have been used in various HTA contexts, but not necessarily for inclusion of PP evidence. Distinct benefits and challenges of integrating PP data were identified for each framework. These included the theoretical basis of the frameworks, their ability to consider non-health as well as health outcomes, and their ability to separate outcomes based on PPs from outcomes based on population preferences. There is limited evidence and no consensus on the application of these frameworks to consider PPs in HTA or on their acceptability for decision-makers. However, CCA has the advantage that it is both based on economic decision theory and it leaves patient preferences disaggregated from population preferences in an HTA.

The frameworks identified in this review offer potential approaches to systematically and transparently integrate PPs into HTA and decision-making. Based on the review findings, we propose a research agenda to explore the potential of CCA in particular. We anticipate that our findings will augment the recommendations of the Innovative Medicines Initiative PREFER project, which are expected to report in 2022.