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ObjectiveTo establish the clinical comprehensive evaluation index system for Chinese patent medicine（CPM） based on Evidence and Value：Impact on DEcisionMaking（EVIDEM） framework， so as to promote the scientific， systematic and standardized implementation of clinical comprehensive evaluation of CPM. MethodThe clinical comprehensive evaluation index system was determined through literature review， semi-structured interview and Delphi method， and the weights of each index were clarified by analytic hierarchy process（AHP）. ResultThe recovery rates of both rounds of expert consultation were 100%， and the authority coefficient of experts was 0.90 and 0.905， respectively. Kendall's coordination coefficients（W） of the second- and third-level indicators in the first-round consultation were 0.320 and 0.283（P<0.001）， and in the second round were 0.411 and 0.351， respectively（P<0.001）. The finally constructed clinical comprehensive evaluation index system for CPM included 6 first-level indicators， 13 second-level indicators and 28 third-level indicators. Among the first-level indicators， the weights of effectiveness， safety， economy， innovation， suitability and accessibility were 37.34%， 32.68%， 11.85%， 5.87%， 5.79% and 6.47%， respectively. ConclusionThis study has constructed a universal clinical comprehensive evaluation index system for CPM， and the domain and criteria are introduced and interpreted in detail， which can provide reference and information for carrying out the clinical comprehensive evaluation of CPM， but it needs to be refined and improved in combination with the clinical practice of CPM for specialized diseases.
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ObjectiveBased on knowledge mapping， the studies on prediction models in the field of traditional Chinese medicine （TCM） were visually analyzed， which provided a reference basis for the excavation and evolution of the future research direction by combing the development process and summarizing the research hotspots and dynamic trends. MethodChina National Knowledge Infrastructure and Web of Science Core Collection databases were searched to obtain studies on prediction models in the field of TCM from inception to February 28， 2023. Endnote X20 software was used for document management. Knowledge mapping generated by CiteSpace software and VOSviewer software was used to visually analyze the characteristics of publication， institutional cooperation relationship， author cooperation network， co-citation， and keywords. ResultA total of 264 pieces of Chinese literature and 266 pieces of English literature were included， and the overall number of research publications showed an increasing trend year by year. The cooperation relationship between the issuing institutions showed obvious regional characteristics， with the closest cooperation relationship between the universities of TCM and their affiliated hospitals， as well as secondary units subordinate to scientific research institutions. The number of research teams and team members publishing papers in English was higher， and cooperation between different teams was more frequent. Groundbreaking and/or referential studies were widely cited and referred to. The highly cited literature was mainly published in complementary and alternative medicine journals and pharmaceutical journals. Research hotspots mainly focused on clinical prediction models of TCM， quantitative models of TCM， and specific modeling methods. The application of artificial intelligence technologies such as machine learning and deep learning in the field of TCM will be the most cutting-edge research direction in the future. ConclusionThe field of TCM is paying more and more attention to the studies on prediction models， while the research cooperation mode involving multiple organizations and teams has increasingly become the mainstream. With the continuous development of multi-disciplinary integration， studies on prediction models are closely related to the development and rise of innovative techniques and methods， and any breakthrough in theory or application will induce and guide a new round of research upsurge. Systematic reviews of topic-specific prediction models should be carried out in the future to provide evidence-based evidence.
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Health research priority setting， based on the existing disease burden or healthcare needs， screens out specific areas or topics with relatively high research priority by scientific and systematic methods， and optimizes the allocation of health resources by influencing healthcare decision-making， so as to alleviate the imbalance between regional or global health and development. Many developed countries have carried out related research and practical work on different scales， and the World Health Organization （WHO） attaches great importance to the transformation and application of relevant achievements in developing countries. As the largest developing country in the world， China's research in this field started relatively late， and only a small number of scholars have carried out part of the localization methodology research and practice according to the specific national conditions. However， health research priority setting has not yet attracted the attention of large-scale research institutions or government organizations in China. Although the priority setting is rarely mentioned in the research on traditional Chinese medicine （TCM）， the research and decision-making on the diseases responding specifically to TCM can also be regarded as the practical work of exploring the priority of TCM. Policymakers have a sense of priority support in the "priority of TCM research"， but the decisions from the top design are mainly based on the consensus reached by high-level think tanks. There is a lack of extensive research， and moreover， the data of multiple stakeholders are not included. Therefore， it is urgent to introduce appropriate priority setting methods to solve the problem of transparency and scientificity in the decision-making process. Given the perspective of the specific implementation， the present study introduced three international priority setting methods， i.e.， the James Lind Alliance and Priority Setting Partnerships（JLAPSP，）the Child Health and Nutrition Research Initiative（CHNRI）， and the Council on Health Research and Development （COHRED）， and presented relevant recommendations on how to apply them in the research of TCM， which is expected to provide references for the local research.