Objective:To evaluate the service capability and operational efficiency of surgical departments in a hospital using data analysis models such as entropy weight TOPSIS and Boston matrix analysis, for references for optimizing medical resource allocation, promoting refined management and sustainable development of the hospital.Methods:The operational data of 24 surgical departments (A~X) in a tertiary public hospital in 2023 from its information system were extracted. The number of doctors, actual number of open beds, and average length of stay etc., were served as evaluation indicators. The TOPSIS and rank sum ratio methods were used to evaluate the medical service capabilities, the data envelopment analysis (DEA) was used to analyze operational efficiency, and Boston matrix analysis was used for departmental classification.Results:In terms of medical service capabilities, the top 5 departments were F, S, K, D, and C ( Ci>0.41), all of which were in the excellent category; The bottom three departments were L, N, and G ( Ci<0.04), all of which were in the poor range. From the perspective of operational efficiency, 8 departments had achieved strong DEA effectiveness, while the remaining 16 departments were non DEA effective, resulting in resource redundancy or insufficient output. According to the Boston Matrix analysis, 8 departments (stars) had strong medical service capabilities and high operational efficiency; 6 departments (cash cows) had poor medical service capabilities but high operational efficiency, and 8 departments (dogs) had poor medical service capabilities and operational efficiency; 2 departments (question marks) had strong medical service capabilities but low operational efficiency. Conclusions:This study comprehensively applied multiple data models to objectively and comprehensively evaluate the service capabilities and operational efficiency of surgical departments. Hospitals could develop corresponding resource allocation optimization strategies based on the Boston matrix classification results, combined with the disease characteristics and business scale configuration of each department.

Multi-disciplinary diagnosis and treatment (MDT) is an effective means to improve the quality of medical care and optimize medical services. In June 2024, this study analyzed the challenges faced by MDT in public hospitals in China and explored the construction of the " grabbing orders" MDT mode based on resource allocation theory. The connotation, operation process, and prerequisites of this mode were clarified, and it was preliminarily applied in a tertiary hospital in January 2025, achieving flexible allocation of expert resources and improving the efficiency of MDT implementation. Taking stage Ⅲ lung cancer as an example, from January to March 2025, the number of lung cancer MDT cases (4.0 cases per month) carried out through the " grabbing orders" MDT was higher than the traditional MDT mode (3.5 cases) per month in 2024. The " grabbing orders" MDT mode could break through the limitations of fixed members in traditional MDT mode, help to achieve efficient allocation of expert resources, so as to provide reference and guidance for optimizing the operation mode of MDT in public hospitals in China.

Objective:To construct analytical dimensions for policy texts related to the pilot work of Health Impact Assessment (HIA) system in Zhejiang Province and conduct quantitative analysis, thereby providing references for improving the pilot work.Methods:Policy texts issued by Zhejiang Province between February 11, 2018, and February 29, 2024, which involved HIA content, were selected. The policy instruments theory was employed to construct an analytical framework around the dimensions of policy instruments, policy objectives, policy actors, and the interactions between policy instruments and policy objectives, and between policy instruments and policy actors. Based on this framework, a combination of literature analysis and content analysis was used to conduct a multi-dimensional quantitative analysis of the policy texts related to the pilot work of HIA system in Zhejiang Province.Results:Fifty core policy texts were included and 1 588 codes were obtained. In terms of policy instruments, environmental-type instruments were the most widely used (852 items), with internal responsibilities and methodological measures being the most frequently used; supply-type instruments were the second most used (459 items), with mechanism improvement being the most frequently used; demand-type instruments were the least used (277 items), with multi-stakeholder participation being the most frequently used. In terms of policy objectives, the objective of system construction dominated (701 articles, accounting for 56.45%), while the proportion of policy coverage, evaluation technology, and effectiveness evaluation was relatively low. In terms of policy subjects, the Party committee and government were the main policy subjects (434 articles, accounting for 39.20%), followed by health departments and public policy-making departments, while the proportion of public health institutions and social forces was extremely low. In the interaction between policy instruments and policy objectives, policy coverage, system construction, and effectiveness evaluation objectives all responded most frequently to environmental-type instruments, while the evaluation technology objectives responded more frequently to supply-type instruments. In the interaction between policy instruments and policy subjects, the Party committee and government played a dominant role in the use of policy instruments, with the health department and public policy-making department in the middle.Conclusions:The pilot work of the HIA system in Zhejiang Province presented a " environment-driven, system-construction-priority, Party-committee-and-government-led" policy characteristic. The main challenges were the imbalanced structure of policy instruments, insufficient synergy among policy objectives, and the need for greater participation of multiple stakeholders.

County medical community serves as pivotal instruments for the hierarchical diagnostic and treatment system. Since their nationwide implementation in December 2023, there has been a pressing demand for governance theories to direct practical applications. Based on polycentric-collaborative governance theory, this study articulated a framework that modeled county medical community as accountable care organizations, anchored by a foundation of primary health care and a polycentric-collaborative governance structure. The framework encompassed critical dimensions, including problem orientation, diverse governance actors, multi-dimensional governance mechanisms, governance objectives, and evaluative metrics. This research also introduced 17 governance instruments, delineated 13 priority action fields, and pinpointed 5 potential reform areas, with a pronounced focus on bolstering governance capacity through value-based payment reforms and technological underpinnings of digital innovation. The framework′s viability and efficacy have been substantiated through a case study in Zhejiang Province. The framework presented herein could offer a comprehensive and systematic guide for county medical community practice, capturing the essence of the reform through a problem-oriented lens, fostering multi-actor involvement, and ensuring the harmonization of multi-dimensional governance mechanisms, thereby fortifying the reform′s systematic, integrative, and collaborative attributes.

Objective:To construct a measurement index system for the high-quality development of public traditional Chinese medicine (TCM) hospitals and conduct an analysis of the coupling coordination degree, providing a reference for the high-quality development of public TCM hospitals.Methods:The characteristics and principles for the high-quality development of public TCM hospitals were conceptualized and operationalized based on the new development philosophy. The Delphi method was adopted to establish a coupled and coordinated measurement index system for the high-quality development of public TCM hospitals. The empirical study was conducted using the data from 240 teritiary grade A public TCM hospitals at the manicipal level and above in 2022, selected from the comprehensive statistical system of the Monitoring and Statistical Research Center. The comprehensive evaluation index method was adopted to comprehensively evaluate the level of high-quality development, and the coupling coordination degree model was used to calculate the level of coupling coordination development.Results:The constructed measurement index system for the high-quality development of public TCM hospitals included 5 first-level indicators (inheritance and innovation, service quality improvement, efficient operation, element openness, and resource sharing), 10 second-level indicators and 32 third-level indicators. The 240 public TCM hospitals basically presented a development level state of resource sharing>element openness>efficient operation>service quality improvement>inheritance and innovation in the subsystem dimensions. The average coupling coordination degree among subsystems was 0.498, which belonged to the primary coordination stage. The coupling coordination degree of element opening and resource sharing with other subsystems was relatively high, while the coupling coordination degree of inheritance and innovation with other subsystems was relatively low.Conclusions:The role of inheritance and innovation in driving the development of public TCM hospitals still needs to be improved. There are significant differences in the coupling and coordination degree among subsystems. It is suggested that the capacity building of advantageous specialties in TCM be further strengthened, the quality and level of services be improved, the regional coordinated development strategy of public TCM hospitals be further implemented, the regional development gap be narrowed, and the coordinated development of various subsystems of high-quality public TCM hospitals be promoted.

Objective:To analyze the current development status and spatial distribution characteristics of traditional Chinese medicine (TCM) hospitals in China, predict the changing trends of the number of TCM hospitals, the number of beds, and the number of physicians, and provide references for the development of TCM hospitals and the formulation of related policies.Methods:From the official websites of the National Bureau of Statistics and the State Administration of Traditional Chinese Medicine, the total population and number of TCM hospitals of 31 provinces (excluding China′s Hong Kong, Macao, and Taiwan) in China from 2013 to 2022 were included, as well as the number of beds and practicing (assistant) physicians in TCM hospitals from 2013 to 2021. The grey prediction model was applied to predict the changing trends of the number of TCM hospitals, beds and physicians. Using the global Moran′s I index in spatial autocorrelation analysis, the distribution of TCM hospitals per 10 000 people in China was analyzed by spatial correlation analysis, and local G coefficient was analyzed by local hot spots.Results:From 2013 to 2027, the number of TCM hospitals, beds and practicing (assistant) TCM physicians in China all showed an increasing trend year by year. The number of TCM hospitals per 10 000 people in China showed a spatial correlation between 2013 and 2022 ( P<0.05). The hot spots of TCM hospitals were mainly concentrated in North China and Northeast China, while the cold spots were mainly concentrated in southeast coastal areas and Northwest China. Conclusions:The number of TCM hospitals in China is increasing year by year, but it is necessary to control the reasonable increase and avoid blind expansion. It is necessary to formulate regional policies of TCM hospitals according to local conditions and pay attention to the individuation of policies. Focus on hot and cold areas to promote balanced development of TCM hospitals.

Objective:To analyze the salary satisfaction and influencing factors of medical staff in public hospitals in Guangxi under the background of salary system reform, and to provide suggestions for deepening the salary system reform of public hospitals in Guangxi.Methods:From July to December 2022, medical staff from 39 public hospitals that have carried out salary system reform were selected through stratified random sampling, and self-made questionnaires were used to survey them, which mainly included salary, salary expectations and salary satisfaction. Descriptive analysis of the questionnaire data was performed, and binary logistic regression was used to analyze the influencing factors of salary satisfaction.Results:A total of 10 299 valid questionnaires were obtained. 6 869 (66.7%) medical staff had a lower average monthly income after tax than those employed in urban non-private units in Guangxi in that year; 8 100 (78.6%) medical staff expected to be paid 30%~50% higher than the current salary level; 4 073 (39.5%) were satisfied with the overall salary satisfaction, of which 2 377 (23.1%) were satisfied with the salary increase after the reform of the salary system in 2017. The results of multivariate analysis showed that education, hospital type, hospital level, professional title, position and job type were the main influencing factors of salary satisfaction of medical staff ( P<0.05), and hospital level interacted with education, hospital type and job type respectively ( P<0.05). Conclusions:The external competitiveness of the salary of medical staff in Guangxi was insufficient, and the salary satisfaction was not high. It is suggested to pay attention to the inter-embeddedness of the reform of the salary system and the reform of the " three-medical linkage" , pay attention to the balanced development of different levels and types of hospitals, scientifically calculate the value coefficient of different positions, and effectively improve the salary level of medical staff.

Objective:Exploring the association rules of factors influencing high hospitalization costs for cancer patients, providing references for hospitals to optimize medical cost management measures.Methods:In the inpatient case information system of a tertiary general hospital, the medical record homepages of inpatients in the DRG groups of the oncology department in 2022 were obtained. The upper four scores of hospitalization costs was used as the threshold for patient grouping. Patients with hospitalization costs≥this threshold were the high-cost group, while other patients were control group; 12 factors, including age, gender, and admission condition, etc, were considered as potential influencing factors of high hospitalization costs. FP-Growth and Apriori algorithms were used to excavate the potential association rules between the influencing factors of high hospitalization costs. Logistic regression was used to analyze the independent influencing factors of high hospitalization costs.Results:A total of 5 512 hospitalized patients were included, including 1 378 patients in the high-cost group. Thirteen validated strong association rules for factors influencing high hospitalization costs were obtained, of which the rule antecedents included age (≥70 years), number of days in hospital (≥7 days), other diagnoses (≥5), surgery, planned readmission, use of antibiotics, admission (general/critical), living admission score (61~99), level of care (level 1/level 2), non-day ward, criticality during hospitalisation. Logistic regression results showed that all nine influencing factors except gender, use of antibiotics, and readmission plans were independent influences on high hospitalization costs ( P<0.05). Conclusions:The joint application of FP-Growth and Apriori algorithm could effectively explore the association rules of high hospitalization costs for oncology patients. The early warning information mainly included the number of hospitalization days, the number of other diagnoses, surgeries, and so on. It was suggested that medical institutions can reasonably control the high hospitalization costs through clinical pathway management, diagnosis and treatment process reengineering, admission risk assessment, and multidisciplinary collaborative diagnosis and treatment strategies.

Hospitals presently confront multiple challenges, including rapid technological advancements, escalating healthcare demands, and continuously rising healthcare costs, thereby necessitating the introduction of new quality productive forces to drive high-quality hospital development. Adopting the perspective of new quality productive forces, the authors examined the transformation trend from conventional fragmented medical services towards integrated digital healthcare systems. Through the establishment of digital infrastructure characterized by big data, cloud computing, the Internet of Things, and artificial intelligence, hospitals could realize deep integration between inpatient and outpatient care, as well as seamless online and offline service delivery. Concurrently, oriented by the healthcare needs of residents, a precise and efficient " prevention-diagnosis-treatment-rehabilitation" service mode was proposed. This mode could facilitate the extension of innovation and industrial chains originating from healthcare services, expedite the translation of research outcomes into practice, and promote scientifically meticulous hospital management. Collectively, these measures could enable hospitals to develop patient-centered, comprehensive life-cycle healthcare service systems, thereby promoting the high-quality development of hospitals.

The new quality productive forces of medical and health provides a new impetus for the high-quality development of hospitals. Based on a systematic analysis of the development connotation of hospitals′ new quality productive forces and the innovation of hospital service mode, this study found that hospitals at all levels were actively attempting to expand their service boundaries and service delivery paths due to the innovation of the medical mode and the change of the public health concept. However, constrained by such bottlenecks as the lagging construction of modern hospital management system and the consolidation of organizational management system, hospitals generally encountered problems such as the weak transformation of service concept and the insufficient endogenous impetus for reform. Additionally, the poor repeatability of some medical innovation practices and the delayed social promotion resulted in a lag in the iterative upgrading of hospital service modes, which was difficult to meet the escalating health needs of the people. Therefore, the authors proposed to construct the innovation path of hospital service mode oriented to new quality productive forces with the support of the dynamic capacity theory, build the hospital innovation environment with the assistance of innovation policies, strengthen the building of the hospital′s multidisciplinary and interprofessional innovation team guided by clinical needs and the provision of special disease services, improve the system construction to realize the full life cycle management of hospital service model innovation activities. To enhance the collaborative creation of multi-institution medical and health service models and promote multi-point application and promotion, thereby further enriching the supply of medical and health services and facilitating the in-depth implementation of the Healthy China strategy.