Real-world evidence (all types of evidences coming from routine clinical practice) has gained substantial attention from pharmaceutical industry and medical society over the last several years. Neither agreed Russian-language term, nor the clear understanding of the processes necessary for the studies based on real-world data (RWD) exist so far. The goal of this article is to actualize the role of real-world data in the process of obtaining of scientific evidence. The authors clarify RWD and RWE definitions, including the peculiarities of Russian-language terms, provide the classification of data sources based on the source type, describe the main RWD features. Assessment and analysis of these data are crucial in study planning and assurance of data quality and RWE validity. This article ensures key factors and practical algorithm for planning of the studies based on real-world data (gap-analysis and multifactor assessment of real-world data). These aspects enhance the creation of valid RWD-based study. Unlike controlled clinical trial, analysis of RWD features significantly higher accent on identification, control and compensation of possible confounders and bias. Accordingly, article defines the main goals and issues that need to be addressed at the stage of RWD analysis. Based on the material provided, authors conclude that RWD are essential in obtaining of valid RWE, and, consequently, decision making. Systemic approach based on versatile work with RWD will enhance the quality of RWE obtained. The article has important applied value: provided algorithms and assessments can be implemented by study sponsors and investigators into their daily practice.