Objective To explore the application effect of a standardized management method based on failure mode and effect analysis （FMEA） in optimizing the whole-process quality control system of the intravenous admixture service （PIVAS）. Methods The quality control management system of the PIVAS was optimized by establishing six quality control groups led by the head nurse, with full participation of pharmacy, nursing, and logistical staff, ensuring comprehensive coverage and traceability of all quality control links. Each group conducted risk priority number （RPN） scoring for potential failure modes in their respective quality control processes, and targeted improvement measures were formulated based on the scoring results. The RPN values of failure modes and quality control-related evaluation indicators before and after implementation were compared to achieve closed-loop management. Results After one year of management, the RPN values of the six major failure modes significantly decreased compared to those before implementation （P<0.05）. The compounding error rate dropped to 0.13%, the dispensing error rate decreased to 0.95%, the compounding efficiency increased to 98%, the delivery time was shortened by 0.45 h per batch, the intervention rate for irrational prescriptions rose to 94.87%, satisfaction improved to 96.78%, and the participation rate of quality control personnel reached 95.36% （P<0.05）. Conclusion FMEA-based identification of potential failure modes in the whole-process quality control system of the IVAS, combined with risk quantification and targeted interventions, significantly reduced high-risk failure modes, improved compounding accuracy and efficiency, and ensured the safety of clinical intravenous medication and the effectiveness of healthcare quality management.

Objective To explore the application effect of a standardized management method based on failure mode and effect analysis （FMEA） in optimizing the whole-process quality control system of the intravenous admixture service （PIVAS）. Methods The quality control management system of the PIVAS was optimized by establishing six quality control groups led by the head nurse, with full participation of pharmacy, nursing, and logistical staff, ensuring comprehensive coverage and traceability of all quality control links. Each group conducted risk priority number （RPN） scoring for potential failure modes in their respective quality control processes, and targeted improvement measures were formulated based on the scoring results. The RPN values of failure modes and quality control-related evaluation indicators before and after implementation were compared to achieve closed-loop management. Results After one year of management, the RPN values of the six major failure modes significantly decreased compared to those before implementation （P<0.05）. The compounding error rate dropped to 0.13%, the dispensing error rate decreased to 0.95%, the compounding efficiency increased to 98%, the delivery time was shortened by 0.45 h per batch, the intervention rate for irrational prescriptions rose to 94.87%, satisfaction improved to 96.78%, and the participation rate of quality control personnel reached 95.36% （P<0.05）. Conclusion FMEA-based identification of potential failure modes in the whole-process quality control system of the IVAS, combined with risk quantification and targeted interventions, significantly reduced high-risk failure modes, improved compounding accuracy and efficiency, and ensured the safety of clinical intravenous medication and the effectiveness of healthcare quality management.

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 clarify the evidence of the frequency and risk factors for falls in knee osteoarthritis(KOA)of adults by meta-analysis.Methods Computerized searches of the CNKI,VIP,Wanfang data,CBM,PubMed,Cochrane Library,Embase,Web of Science were conducted for literature on risk factors for falls in adults with KOA from the inception of the databases to August 2024.After literature screening,data extraction,and quality evaluation,RevMan 5.4 software was used for Meta-analysis.Results A total of 26 articles were involved.Meta-analysis result showed that the rate of falls was 29.0％.Factors associated with increased risk of falls included being female(OR=1.35),decreased lower limb muscle strength(OR=1.72),decreased knee flexion muscle strength(OR=7.05),decreased static posture stability(OR=1.28),opioid use(OR=1.79),antidepressant use(OR=1.69),frequent stair climbing(OR=7.58),combined neurological disease(OR=1.77),history of falls(OR=3.29)and fear of falling(OR=2.54).Conclusion The rate of falls of patients with KOA is high.The adults with KOA who are women,have lower muscle strength of lower limbs and knee flexion muscle strength,poorer static posture stability,use opioids,antidepressant,frequent stair climbing,combined neurological disorders,previous falls in the past year and fear of falls are at higher risk of falls.Healthcare professionals should dynamically assess and detect the risk of falls in the patients with KOA and adopt targeted,individualized interventions to prevent falls.

Objective To examine the changing prevalence and antimicrobial resistance profiles of Burkholderia cepacia in 52 hospitals across China from 2015 to 2021.Methods A total of 9 261 strains of B.cepacia were collected from 52 hospitals between January 1,2015 and December 31,2021.Antimicrobial susceptibility of the strains was tested using Kirby-Bauer method or automated antimicrobial susceptibility testing systems according to a unified protocol.The results were interpreted according to the breakpoints released in the Clinical & Laboratory Standards Institute(CLSI)guidelines(2023 edition).Results A total of 9 261 strains of B.cepacia were isolated from all age groups,especially elderly patients.The proportion was 11.1％(1 032 strains)in children,significantly lower than the proportion in adults.About half(46.5％,4 310/9 261)of the strains were isolated from patients at least 60 years old and 42.3％(3 919/9 261)of the strains were isolated from young adults.Most isolates(71.1％)were isolated from sputum and respiratory secretions,followed by urine(10.7％)and blood samples(8.1％).B.cepacia isolates were highly susceptible to the five antimicrobial agents recommended in the CLSI M100 document(33rd edition,2023).B.cepacia isolates showed relatively higher resistance rates to meropenem and levofloxacin.However,the resistance rates to ceftazidime,trimethoprim-sulfamethoxazole,and minocycline remained below 8.1％.The percentage of B.cepacia strains resistant to levofloxacin was the highest compared to other antibiotics in any of the three age groups(from 12.4％in the patients＜18 years old to 20.6％in the patients aged 60 years or older).Conclusions B.cepacia is one of the clinically important non-fermenting gram-negative bacteria.Accurate and timely reporting of antimicrobial susceptibility test results and ongoing antimicrobial resistance surveillance are helpful for rational prescription of antimicrobial agents and proper prevention and control of nosocomial infections.

Objective To summarize the changing prevalence of carbapenem resistance in Enterobacterales based on the data of CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021 for improving antimicrobial treatment in clinical practice.Methods Antimicrobial susceptibility testing was performed using a commercial automated susceptibility testing system according to the unified CHINET protocol.The results were interpreted according to the breakpoints of the Clinical & Laboratory Standards Institute(CLSI)M100 31st ed in 2021.Results Over the seven-year period(2015-2021),the overall prevalence of carbapenem-resistant Enterobacterales(CRE)was 9.43％(62 342/661 235).The prevalence of CRE strains in Klebsiella pneumoniae,Citrobacter freundii,and Enterobacter cloacae was 22.38％,9.73％,and 8.47％,respectively.The prevalence of CRE strains in Escherichia coli was 1.99％.A few CRE strains were also identified in Salmonella and Shigella.The CRE strains were mainly isolated from respiratory specimens(44.23±2.80)％,followed by blood(20.88±3.40)％and urine(18.40±3.45)％.Intensive care units(ICUs)were the major source of the CRE strains(27.43±5.20)％.CRE strains were resistant to all the β-lactam antibiotics tested and most non-β-lactam antimicrobial agents.The CRE strains were relatively susceptible to tigecycline and polymyxins with low resistance rates.Conclusions The prevalence of CRE strains was increasing from 2015 to 2021.CRE strains were highly resistant to most of the antibacterial drugs used in clinical practice.Clinicians should prescribe antimicrobial agents rationally.Hospitals should strengthen antibiotic stewardship in key clinical settings such as ICUs,and take effective infection control measures to curb CRE outbreak and epidemic in hospitals.