OBJECTIVES: In 2021, the Danish Medicines Council adopted a quality-adjusted life year model to evaluate healthcare interventions for reimbursement. Denmark does not communicate an explicit cost-effectiveness threshold; thus, there is a lack of transparency surrounding the reimbursement criteria. It is not clear what makes a reimbursement decision positive or negative regarding cost-effectiveness. Estimating the cost-effectiveness threshold can help increase understanding of the Danish pharmaceutical landscape, and in turn patient access. The present study aims to increase understanding of the cost-effectiveness threshold used in the new Danish health technology assessment process since its implementation, in addition to examining the characteristics of the medicines that have undergone this new process.

METHODS: This was achieved using two methods. The first approach employed a novel back-calculation method which used data from Norwegian health technology assessments (Nye metoder). The second method utilized an average discount rate published by Amgros, a Danish procurement service.

RESULTS: The estimated cost-effectiveness threshold from the novel back-calculation method was 458,134 DKK/QALY (61,505 €/QALY), and from the Amgros calculation method the estimated threshold was 969,518 DKK/QALY (130,159 €/QALY). The proportion of negative to positive reimbursement recommendations was found to be almost equal in decisions made using the new assessment process in Denmark. Furthermore, it was observed that majority of medicines had one indication, and the medicines that had more than one indication belonged to oncology. Through additional analyses of disease areas, a high number of oncology, rheumatology and neurology medicines being submitted for appraisal was observed.

CONCLUSIONS: The estimated cost-effectiveness threshold in Denmark falls between 458,134 – 969,518 DKK/QALY. This study serves as a starting point for further research on the cost-effectiveness threshold used in Denmark’s new HTA process. With more decisions to draw data from in the future, more concrete conclusions can be made.