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 literature 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 represented 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.