This article highlights solution of the problem of determining the medications’ effectiveness based on sentiment analysis of patient reviews collected in the medical segment of social media. Public opinion about media subjects (physicians, nurses, clinics, pharmaceutical companies, etc.) can be determined based on the information collected in medical social media. One of the most discussed topics in medical social media is related to medications (drugs), their effectiveness, and determining public opinion based on collected user comments is one of the current issues. To analyze patient reviews about drugs, the Kaggle platform drugsComTest_raw.csv medical database is used, lexicon-based sentiment analysis, statistical methods and machine learning algorithms are applied. The problem is solved in stages on the patient-disease, disease-drug and patient-drug segments, the issues of which diseases are most often used for drugs, and which drugs are most often used for each disease are resolved. Based on the integration of the results obtained from the problem solutions, a mechanism for forming public opinion on the effectiveness of drugs is developed. The proposed approach takes into account not only positive but also negative opinions when determining public opinion about the effectiveness of drugs. Such results can be used to support appropriate decision-making in the healthcare sector, specifically in pharmaceutical companies (pp.60-67).