OBJECTIVES : Drug value assessment is an actual challenge for any healthcare system. The aim of our research was to identify value preferences of Russian healthcare stakeholders based on established criteria list and to create multiple-criteria decision analysis (MCDA) based tool for overall value aggregating.

METHODS : Preferences were evaluated in a population consisting of healthcare policy makers, clinicians and pharmacists. The questionnaire focused on relevant criteria that were defined by literature review. Discrete choice experiment (DCE) survey was provided using online platform. A conditional logistic model was used for data processing. Choice of experiment design, questionnaire creation and conditional logistic analysis were conducted using «support.CE» package in RStudio. The final weights were obtained using log-likelihood and coefficient range methods in Microsoft Excel.

RESULTS : The criteria list used in this study included five criteria: efficacy, safety, ease of administration, burden of disease and unmet therapeutic needs. Questionnaire created in RStudio consisted of 18 questions, either of which included two alternatives with random assigned attribute’s level. The following weights using log-likelihood method were obtained: efficacy – 0,653, safety – 0,234, ease of administration – 0,031, burden of disease – 0,032, unmet therapeutic needs – 0,050. Weights received by coefficient range method were generally comparable, with the exception of criteria of efficacy and ease of administration, the weights of which amounted to 0,49 and 0,20 respectively. During the validation of two MCDA tools based on different weight sets on five oncology drugs the results consistency was determined.

CONCLUSIONS : Developed tool enables estimation of therapeutic value for oncology drugs using different features attendant not only for drugs, but also for clinical condition. Further, this tool can be used as a part of health technology assessment (HTA) to inform the decision making process or as a basis for value-based pricing.