A large amount of studies show that real-world study has strong external validity than the traditional randomized controlled trials and can evaluate the effect of interventions in a real clinical setting, which open up a new path for researches of integrative medicine in coronary heart disease. However, clinical data of integrative medicine in coronary heart disease are large in amount and complex in data types, making exploring the appropriate methodology a hot topic. Data mining techniques are to analyze and dig out useful information and knowledge from the mass data to guide people's practices. The present review provides insights for the main features of data mining and their applications of integrative medical studies in coronary heart disease, aiming to analyze the progress and prospect in this field.