Background. Multiple criteria decision analysis (MCDA) has been identified as a prospective methodology for assisting decision makers in evaluating the benefits of new medicines in health technology assessment (HTA); however, limited empirical evidence exists from real-world applications. Objective. To test in practice a recently developed MCDA methodological framework for HTA, the Advance Value Framework, in a proof-of-concept case study with decision makers. Methods. A multi-attribute value theory methodology was adopted applying the MACBETH questioning protocol through a facilitated decision-analysis modelling approach as part of a decision conference with four experts. Settings. The remit of the Swedish Dental and Pharmaceutical Benefits Agency (Tandvårds- och läkemedelsförmånsverket [TLV]) was adopted but in addition supplementary value dimensions were considered. Patients. Metastatic castrate-resistant prostate cancer patients were considered having received prior chemotherapy. Interventions. Abiraterone, cabazitaxel, and enzalutamide were evaluated as third-line treatments. Measurements. Participants’ value preferences were elicited involving criteria selection, options scoring, criteria weighting, and their aggregation. Results. Eight criteria attributes were finally included in the model relating to therapeutic impact, safety profile, socioeconomic impact, and innovation level with relative importance weights 44.5%, 33.3%, 14.8%, and 7.4% per cluster, respectively. Enzalutamide scored the highest overall weighted preference value score, followed by abiraterone and cabazitaxel. Dividing treatments’ overall weighted preference value scores by their costs derived “costs per unit of value” for ranking the treatments based on value-for-money grounds. Limitations. Study limitations included lack of comparative clinical effects across treatments and the small sample of participants. Conclusion. The Advance Value Framework has the prospects of facilitating the evaluation process in HTA and health care decision making; additional research is recommended to address technical challenges and optimize the use of MCDA for policy making.
A hybrid multiple-criteria decision analysis framework for corporate social responsibility implementation applied to an extractive industry case study
