Objective To identify the key factors affecting the risk of medical surges and their coupling relation5 ships,providing strategic support for medical institutions to optimize risk management and emergency governance.Methods 17 influencing factors were determined based on WSR theory,and an expert scoring method was employed to assess the impact strength among the factors.The DEMATEL method was applied to calculate the centrality,cau5 sality,influence,and being influenced degrees of the influencing factors.The ISM method was used to construct a hierarchical structure of the influencing factors related to medical surge risks,thereby revealing the connections and interaction mechanisms among these factors.Results Seven critical influencing factors were identified,including the crisis decision-making capacity and leadership effectiveness of emergency managers,the completeness of the emer5 gency system and dynamic execution capabilities,and the cross-departmental coordination mechanism and com5 mand collaboration efficiency.Deep driving factors and coupling pathways were also revealed.Conclusion The risk of medical surges exhibits multi-factorial coupling cascade effects;attention should be directed towards the construc5 tion of mid-to-deep level mechanisms such as information systems,institutional frameworks,and organizational management,to enhance targeted capabilities and systemic resilience in risk governance.

Objective Exploring the components of complex scenarios of healthcare surges triggered by major epidemics to provide a theorical basis for building resilience in healthcare organizations.Methods A hybrid analysis method is used to summarize macro-meso-micro multi-level and multi-source heterogeneous information,extract the elements of complex scenarios of medical surge and evaluate the rationality.Fault Tree Analysis method is used to clarify the logical relationship between various scenario elements and construct scenario reasoning paths.Results 10 scenario states,11 disaster-bearing,24 emergency management and 23 scenario results are summarized and extracted to form the key elements of complex surge scenarios.Among them,M4 expansion and coordinated scheduling of key positions,B2 conventional drug inventory emergency/insufficient core treatment drugs,B emergency medical material transportation breakage,S3 disease symptom spectrum shift to severe disease,R13 prevention and control awareness laxity,and M5 media information dissemination management are the key driving factors that promote a major turning point in the scenario.The most positive scenario result is the orderly operation of the medical service system,and the most negative scenario result is the paralysis of the medical service system.Conclusion Medical institutions need to improve emergency plans based on the complex evolution scenarios of medical surges and agile governance capabilities targeting key turning points,focus on dynamically expanding and scheduling personnel in key positions,strengthen material rotation and reserve mechanisms,maintain smooth emergency logistics channels,and improve efficient management of media and public opinion,so as to comprehensively improve overall resilience.

Objective To explore the coupling mechanism between medical surge response resources and the spread of secondary risks during public health emergencies,as well as the effectiveness of relevant interventions.Methods Based on complex network theory,a dual-layer network model of medical resources and secondary events was constructed.The interactive feedback between medical resource status and secondary event risk,as well as the effects of network structure,were analyzed through MATLAB simulations,REPAST agent-based modeling,and mean-field analysis.Results Simulation and prediction results show that an increase in first-layer resource-deficient nodes significantly raises the activation rate and transmission speed of secondary events,while the clustering and spread of secondary events in the second layer,in turn,intensify resource depletion,creating a negative feedback loop.Mean-field analysis indicates a nonlinear positive correlation between the adequacy of medical resources and the likelihood of secondary events.Network structure analysis reveals that when the average node degree exceeds 8,resource allocation efficiency improves markedly.Conclusion There exists a dynamic coupling and bidirectional feedback relationship between medical resource status and secondary event risks.Enhancing the flexible allocation and responsiveness of medical resources,improving multi-sectoral collaborative monitoring and coordinated regulation,optimizing network connectivity and coordination mechanisms for resource distribution,and establishing dynamic monitoring and tiered early warning systems are key strategies for strengthening the resilience of healthcare systems and effectively containing the spread of secondary events.

Objective To define the conceptual connotation of network dynamic collaboration capacity in medical surge response and construct its theoretical model.Methods A mixed concept analysis method was employed,integrating multidisciplinary literature and collecting empirical evidence through semi-structured expert interviews to extract the concept of network dynamic collaboration capacity in medical surge response.By integrating complex systems,network science,synergetics,and dynamic capability theory,and combining the interview results,the study used the analogy of flood control in hydraulic engineering to develop a"network-dynamic-collaboration"triangular capacity theoretical model.Results It reveals one antecedents(sudden external shocks have led to an abnormal and continuous surge in medical demand),six core attributes(information interconnection accessibility,dynamic resource adaptability,risk perception responsiveness,multi-party collaborative interactivity,service process adaptability elasticity,and learning iterative evolution),and four consequences(mitigation of crowding risk,protection of service continuity,minimization of crisis spillover,and enhancement of system resilience)for the network dynamic collaboration capacity in medical surge response.The theoretical model elucidates the coupling mechanisms among network structural resilience,dynamic regulation processes,and collaborative co-evolution in resisting medical surge.Conclusion The new concept and theoretical model proposed in this study deepen the understanding of medical surge response system mechanisms and offer a theoretical framework and practical guidance for strengthening the full-chain resilience of health emergency systems.

Objective To empirically analyze multiple pathways for enhancing medical surge response capacity and provide useful references for improving the resilience of health systems.Methods A comprehensive theoretical analysis framework for improving medical surge response capacity was constructed based on the 4S theory and collaborative governance theory.68 interview texts on medical surge response capacity conducted in July 2024 were selected as analysis samples.Using fuzzy-set Qualitative Comparative Analysis(fsQCA),7 conditional variables were selected from four dimensions:management system,information system,materials,and personnel to analyze their impact on medical surge response capacity.Results(1)A single conditional variable does not constitute a necessary condition for improving medical surge response capacity;(2)After the combination of conditions,8 specific configuration paths for capacity improvement were identified.Through systematic and comprehensive refinement,they were summarized into three modes of comprehensive configuration capacity improvement paths,namely:rapid response and collaborative operation mode,information empowerment and precise response mode,and resource conditions and resilience construction mode.Conclusion It is necessary to explore and construct systematic,combined,modularized and path-oriented capacity building strategies,refine the operational implementation paths for improving China's medical surge response capacity,target the linkage and configuration modes of different conditional variables,promote the formulation and implementation of modular construction schemes oriented by key capacity,and make efforts from multiple aspects to enhance the resilience of the health system.

Objective:To explore the method for selecting characteristic prices of Chinese patent medicines based on informa-tion entropy theory.It involves analyzing the connotative differences among various price indicators and utilizing information entropy metrics to validate the scientific rigor of characteristic price selection so as to optimize the pricing model for Chinese patent medi-cines and improve the accuracy of price evaluation.Methods:A correlation analysis and information entropy calculation are con-ducted on the median price of the smallest preparation unit,average daily cost,and average course cost of TCM.It compares the information diversity and uncertainty of different pricing indicators.Results:The average daily cost exhibits the highest information diversity and uncertainty among all the pricing indicators examined.Conclusion:It is recommended that the average daily cost be used as the dependent variable for characteristic prices in TCM pricing research.This choice plays an important role in optimizing TCM pricing models and enhancing the accuracy of price evaluation.

Objective:To establish a scientific,systematic,and objective indicator system for the characteristic price variables of Traditional Chinese Patent Medicines(TCPM),providing a reference framework for the pricing mechanism of TCPM.Methods:The brainstorming method was initially used to screen related variable indicators.The Nominal Group Technique(NGT)and Delphi methods were applied to gather expert opinions,and SPSS 28.0 was employed for data statistical analysis.It led to the development of a TCPM characteristic price variable indicator system consisting of 6 dimensions,14 characteristic variables and 26 measurement indicators.Results:The authority coefficient of the experts exceeded 0.7,indicating the representativeness of the results.Expert opinions were generally concentrated.Based on the collected opinions and statistical analysis,the scope of selected TCPM characteristic price variables was preliminarily established.Conclusion:The TCPM characteristic price variable indicator system was initially developed.However,due to the complexity of the pricing mechanism and divergent expert opinions,further qualitative and quantitative research methods,along with a dynamic adjustment mechanism,are needed to verify and refine the system.

The National Essential Medicines System could protect public health and ensure access to essential medications.Although the current selection methods for China's National Essential Medicines Lists(NEMLs)are becoming more scientific and standardized,there are still problems such as much emphasis on expert experience and the lack of transparency of decision-making basis.To address these issues,it proposes an evidence-based decision-making pathway for NEMLs selection guided by clinical value.This approach ensures a strong integration of evidence and decision-making,offering valuable insights for improving the adjustment procedures and selection criteria of the NEMLs in China.

Objective:To explore the method for selecting characteristic prices of Chinese patent medicines based on informa-tion entropy theory.It involves analyzing the connotative differences among various price indicators and utilizing information entropy metrics to validate the scientific rigor of characteristic price selection so as to optimize the pricing model for Chinese patent medi-cines and improve the accuracy of price evaluation.Methods:A correlation analysis and information entropy calculation are con-ducted on the median price of the smallest preparation unit,average daily cost,and average course cost of TCM.It compares the information diversity and uncertainty of different pricing indicators.Results:The average daily cost exhibits the highest information diversity and uncertainty among all the pricing indicators examined.Conclusion:It is recommended that the average daily cost be used as the dependent variable for characteristic prices in TCM pricing research.This choice plays an important role in optimizing TCM pricing models and enhancing the accuracy of price evaluation.

Objective:To establish a scientific,systematic,and objective indicator system for the characteristic price variables of Traditional Chinese Patent Medicines(TCPM),providing a reference framework for the pricing mechanism of TCPM.Methods:The brainstorming method was initially used to screen related variable indicators.The Nominal Group Technique(NGT)and Delphi methods were applied to gather expert opinions,and SPSS 28.0 was employed for data statistical analysis.It led to the development of a TCPM characteristic price variable indicator system consisting of 6 dimensions,14 characteristic variables and 26 measurement indicators.Results:The authority coefficient of the experts exceeded 0.7,indicating the representativeness of the results.Expert opinions were generally concentrated.Based on the collected opinions and statistical analysis,the scope of selected TCPM characteristic price variables was preliminarily established.Conclusion:The TCPM characteristic price variable indicator system was initially developed.However,due to the complexity of the pricing mechanism and divergent expert opinions,further qualitative and quantitative research methods,along with a dynamic adjustment mechanism,are needed to verify and refine the system.