Integration of economical analysis into clinical trials becomes a widespread practice over the past two decades because it provides a number of advantages and feasibility for cost-effectiveness studies. At the same time, weaknesses related to trial-based “artificial” nature of such studies represent challenges for proper conduction of economical evaluations. Thus development of effective practical approaches focused on assurance reliability of economic data generated alongside a clinical trial is of great interest. Application of risk-based management in “piggyback” evaluations is a perspective way helping to couple with issues that hamper collection of sound health-economic data in each particular trial. It is rational to forecast risks that compromise data validity at the stage of trial planning and elaborate a plan of its mitigating using risk-proportionate approach. Identification of risks should include analysis of risk factors causing issues in a particular trial-based economical evaluation by following areas: trial design, subjects’ enrollment and randomization, data collection and analysis. It is reasonable to monitor economic data quality and completeness using key risk indicators enabling to control identified risks influence in real time. In this way, quality assurance measures are implemented in a proportionate manner according to risks value. Sponsors and researches involved in clinical trials with economical evaluations should pay special attention to elaboration of quality risk management plan including risk identification, assessment and control. It is important to implement key points of this plan during all stages of economic data collection. Applying key risk indicators during study monitoring, study sponsors will successfully integrate health-economic data into clinical trial data management system ensuring its robustness and validity in a rational manner. Thus, application of quality risk management is an effective strategy for overriding challenges of cost-effectiveness analysis alongside clinical trial strengthening its position as an important tool of generating evidence-based clinical and economic data.