Abstract: In recent years, with the rapid development of information technology and the increasing demand for evidence-based healthcare practice and policy decisions, the value of real-world data has received extensive attention. One of the most important applied areas of real-world data is disease management. Its core concepts lie in the application of rigorous and pre-specified designs to data of large volume, multiple sources, and high quality. By doing so, the high-quality real-world evidence for disease burden, diagnosis, prevention, treatment, and prognosis is generated to inform the development of guidelines, clinical pathways, and technical standards for disease management, which ultimately improves healthcare quality and safety. This paper systematically discussed important issues regarding the use of real-world data for research on disease management.