ObjectiveTo investigate the construction strategy of a knowledge base for health technology assessment (HTA) indicators based on a multi-granularity knowledge representation model, in order to meet the users' diverse demands for HTA knowledge services. MethodsFirstly, we constructed a multi-granularity HTA indicator knowledge representation model based on systematically analyzing the content and structure of the HTA indicator system in literature. Secondly, we extracted multi-granularity HTA indicator knowledge from literatures and conduct subject indexing in a human-computer collaborative way. Finally, based on the HTA knowledge service requirements, a prototype of the HTA indicator knowledge base-HTA Indicators was designed and developed. ResultsA multi-granularity HTA indicator knowledge representation model was constructed, covering 5 core knowledge units(indicator systems, indicator items, formulas, measurement variables, and subjects), 20 types of attributes, and 12 types of relationships. This model represents the intrinsic characteristics and connections between multi-granularity indicator knowledge units. Knowledge extraction and subject indexing of multi-grain HTA indicators were conducted based on 227 HTA indicator documents, forming instance data. Finally, a prototype of the HTA indicator knowledge base, named HTA Indicators, was developed.HTA Indicators provides services such as multi-granularity HTA indicator knowledge retrieval, navigation, and linking. ConclusionThe construction strategy of the HTA indicator knowledge base based on the multi-granularity knowledge representation model is feasible. The indicator knowledge base can achieve multi-dimensional semantic organization of indicator knowledge, provide multi-level and multi-dimensional indicator knowledge retrieval and discovery services, and meet the users' demand for precise HTA knowledge. In the future, we will explore the use of cutting-edge technologies such as large language models to achieve the automated construction of large-scale HTA knowledge, thereby enhancing the efficiency and intelligence level of knowledge base construction.