Using the Delphi method to propose foods for special medical purposes health effect evaluation indicators

Abstract

Abstract Objective The Delphi method was used to propose health effect evaluation indicators to assess foods for special medical purposes (FSMPs). This lays the foundation for the formation of a big data model for human health testing, as well as a big data platform for the health and safety evaluation of special medical foods. Methods The Delphi method was used to conduct two rounds of expert consultation on the constructed FSMP health effect evaluation indicators. Results Ten major items were identified after two rounds of expert consultation. Among these, there were 10 primary entries, 32 secondary entries, 50 tertiary entries, and 28 quaternary entries. Conclusion The complete list of evaluation indicators contains 10 entries, which can comprehensively and systematically monitor adverse reactions to the use of FSMPs. The present findings lay the foundation for a big data platform to evaluate the health and safety of special foods.