Objective: To analyze the internal composition and changes of the hospitalization costs of lung cancer surgery patients, explore the main influencing factors of hospitalization costs, predict the trend of hospitalization costs, and provide an empirical basis for reducing the hospitalization medical burden of lung cancer patients. Methods: The information on the front pages of the hospitalization medical records of lung cancer surgery patients in a certain third-level Class-A hospital from 2018 to 2022 was collected. The new grey correlation and structural change degree analysis methods were used to study the internal structural changes of hospitalization costs and the correlation degree among them. Through univariate analysis and multiple linear regression analysis, the main influencing factors of hospitalization costs were explored. The GM(1,1) model was used to predict the hospitalization costs from 2023 to 2025. Results: (1) From 2018 to 2022, the average hospitalization cost per case of lung cancer surgery patients in this hospital decreased year by year, with an average annual decrease of 6.67%. (2) Drug costs, diagnostic costs, and surgical treatment costs were the main factors for the structural changes of hospitalization costs, with a cumulative structural change degree of 33.76% and a cumulative contribution rate of 86.23%. (3) The top three in the correlation degree ranking were material costs (0.952), comprehensive medical service costs (0.843), and diagnostic costs (0.697) in turn. (4) Multiple linear regression analysis showed that higher age, more number of complications/accompanying diseases, the medical payment method of urban employee basic medical insurance, and more hospitalization days were the influencing factors for the increase of hospitalization costs of lung cancer surgery patients (P < 0.05); the marital status of being widowed or divorced and emergency admission were the influencing factors for the decrease of hospitalization costs of lung cancer surgery patients (P < 0.05). (5) The GM(1,1) model predicted that the hospitalization costs would further decrease in the next three years. Conclusion: The control of hospitalization costs for lung cancer surgery in this hospital has achieved certain results, especially in controlling drug costs. The costs of surgical treatment that reflect the labor value of medical staff have increased. Diagnostic costs and material costs are the key points for the hospital to further control hospitalization costs in the next step. Clinically, the hospitalization costs of lung cancer surgery patients can be further reduced by early detection, early diagnosis, early treatment, and scientifically reducing the number of hospitalization days. Comprehensive measures should be taken to optimize the composition of patients' hospitalization costs, strengthen the management of controllable factors, and reduce the hospitalization medical burden of lung cancer surgery patients.

Objective To investigate the factors affecting hospitalization costs of hospitalized patients with chronic obstructive pulmonary disease (COPD), so as to reduce the burden of patients, promote the rational allocation of medical resources, and provide a basis for formulating healthcare policies.Methods The medical record homepage data of chronic obstructive pulmonary hospitalized patients in a tertiary general hospital in Beijing from 2019 to 2022 were selected to study the influencing factors of the hospitalization costs through descriptive analysis, rank sum test, correlation analysis, and multifactor regression analysis.Results Male patients (66.0%) outnumbered female patients (34.0%) among 1 053 COPD patients, the proportion of patients aged 60-89 years old was the highest (82.8%), the number of medicare-paid patients was the highest (88.2%), emergency admissions (57.1%) were higher than outpatient admissions (42.9%), and the percentage of hospitalization days with 10-19 days was the the most (45.3%). The high incidence seasons of chronic obstructive pulmonary disease were fall and winter (51.9%), and common comorbidities were coronary heart disease (78.3%), hypertension (73.0%), and pulmonary heart disease (48.5%). Chinese and Western medicine (36.75%), medical services (29.57%), and diagnosis (22.82%) accounted for the largest share of hospitalization costs. There was a statistical difference in hospitalization costs for variables of age, medical payment method, number of hospitalization days, comorbidities of hypertension, coronary heart disease, respiratory failure, pulmonary heart disease, treatment with antimicrobials, and ventilator-assisted therapy (P<0.05) . Regression analysis showed that the older the age, the longer the hospitalization days, the higher the number of comorbidities, the more use of antimicrobial drugs and ventilator therapy, the higher the hospitalization costs. Compared to medical insurance patients, public medical care was positively correlated with hospitalization costs (P<0.05).Conclusion Health education should be strengthened, early screening and intervention for elderly patients and COPD patients with a history of cardiovascular disease should be carried out, and multidisciplinary diagnostic and treatment modes and improved clinical pathways should be utilized to standardize the diagnostic and treatment processes, logically shorten the average number of hospitalization days, reduce the waste of medical resources and alleviate the patients′ economic burden.

Objective To understand the influencing factors of perioperative death of elective surgery patients in a hospital, and to provide data reference for hospitals to strengthen perioperative management and reduce postoperative mortality.Methods The information of patients who underwent elective surgery from January 1, 2020 to December 31, 2022 was retrieved from the medical record homepage management system of a tertiary general hospital, and the main diagnosis, surgical method, surgical department and causes of postoperative death were retrospectively analyzed.Results From 2020 to 2022, 81 722 patients underwent elective surgery in the hospital, of which 103 patients died after the surgery, with a mortality rate of 0.13%; the top three primary diseases were circulatory system disease, tumor minor and congenital disease, accounting for 85.43%; the main surgical types of patients who died after elective surgery cardiac surgery, aortic surgery and craniocerebral surgery, accounting for 46.07%; postoperative death cases were mainly concentrated in the departments of cardiothoracic surgery, cardiovascular surgery, cardiovascular medicine, vascular surgery, neurosurgery and intervention; the main cause of death was surgical complications, accounting for 44.66%, followed by primary disease aggravation and other diseases after the surgery, accounting for 32.04% and 23.30% respectively.Conclusion The relevant surgical departments should strengthen the management of preoperative, intraoperative and postoperative perioperative patients. The functional departments should carry out special management for the departments with more deaths of elective postoperative patients, which is of great significance to reduce the postoperative mortality of patients undergoing elective surgery.

Metabolomics is a disciplinary field that investigates all small-molecule metabolites within the biological organism. Utilizing advanced technological platforms such as mass spectrometry and nuclear magnetic resonance, comprehensive and high-throughput detection of metabolites can offer new avenues for early disease diagnosis, elucidation of pathogenic mechanisms, and personalized therapeutic approaches. Due to the diversity, high dimensionality, dynamics, noise, and variability inherent in metabolomics data, it poses formidable challenges for the research and development of data analysis methods. This paper aims to provide a comprehensive overview of recent advancements of machine learning methods for statistical analysis on metabolomics data, with particular focus on improved approaches. By synthesizing these methodologies, the intention is to offer a crucial foundation for effective data analysis and to fully harness the potential of metabolomics in medical research.

Objective To explore the structure and importance ranking of average hospitalization costs for patients with depression, and to provide a basis for improving the structure of patients′ hospitalization costs and effective cost control.Methods Information on the hospitalization costs of patients with depression in a tertiary hospital in Guangzhou City from 2018 to 2023 was collected, and the degree of association, composition ratio, and change of each cost with the average hospitalization costs per-time were evaluated by using the degree of structural variation and new gray correlation analysis.Results From 2018 to 2023, the average hospitalization cost per-time of patients with first gradually increased and then decreased, the proportion of diagnostic fee and examination fee continued to increase, and the proportion of nursing fee and drug fee continued to decrease. The degree of structural change of average hospitalization cost per-time during the 6-year period was 33.84%, and the degree of annual average structural change was 5.64%. The top 3 contributors to the structural change were drug fee (26.77%), diagnostic fee (23.43%) and medical service fee (19.77%), and the cumulative contribution of the three amounted to 69.97%. The results of the new gray correlation analysis showed that the treatment fee (0.939) had the greatest impact on the average hospitalization cost per-time of depressed patients, followed by the diagnostic fee (0.883), the examination fee (0.866) and the medical service fee (0.817).Conclusion Treatment fee, diagnostic fee and examination fee are the main factors affecting the hospitalization cost of depressed patients, and the income of nursing fee and drug fee continues to decrease. It is recommended to continuously optimize the cost structure and establish a reasonable, stable and efficient cost control program.

The introduction of DIP (Diagnosis-Intervention Packet, paying by disease scores) and DRG (Diagnosis-Related Groups, paying by disease diagnosis related groups) payment models marks the transformation of China's medical insurance payment method from the traditional "post-payment" to the "pre-payment" model, which puts forward higher requirements for the financial management and budget management of public hospitals. This paper analyzes the impacts of DIP/DRG payment reform on aspects such as hospital financial management, medical record management, cost accounting and information systems, and points out that it promotes a systematic change in the hospital management model. Secondly, based on the process management theory, it explores the construction path of the comprehensive budget management system in public hospitals, mainly including the improvement of budget management systems, the clarification of budget objectives, the optimization of budget management processes, and the establishment of budget supervision and evaluation mechanisms. Through investigations and combing relevant literature, this paper proposes optimization strategies for the budget management system in view of the characteristics of DIP/DRG payment reform. The aim is to enhance the operational performance and financial management level of public hospitals under the new payment model and promote the high-quality development of hospitals.

Objective To analyze the operation index data of public hospitals in Jiangsu Province, in order to provide insights for optimizing resource allocation and management of medical resources in public hospitals in Jiangsu Province.Methods Data envelopment analysis (DEA) was employed to assess the operational efficiency of second-level and above public hospitals in sub-cities of Jiangsu from 2015 to 2022.Results From 2015 to 2019, the technical efficiency, scale efficiency and comprehensive efficiency of public hospitals in Jiangsu Province were all 1, indicating that DEA was strong and effective, while the return to scale remained unchanged. From 2020 to 2022, except for 2021, when the technical efficiency was 1, the scores of technical efficiency, scale efficiency and comprehensive efficiency were less than 1, and in 3 years, the scale efficiency and comprehensive efficiency were not effective. Notably, Suzhou, Zhenjiang, and Suqian maintained a scale compensation coefficient of 1 from 2015 to 2022, while other areas experienced fluctuations in scale compensation.Conclusion The operational efficiency of public hospitals in Jiangsu Province varies over time and across regions, indicating uneven development. There is still room for optimizing the allocation of medical resources and scale among public hospitals in many cities.

Objective To assess the causal effect of schizophrenia on substance abuse and alcohol use disorder, to clarify the causal associations between diseases and behaviors, and to provide new ideas and protocols for improving clinical treatment and prognosis.
Methods Summary statistics from genome - wide association studies of schizophrenia, substance abuse, and alcohol
use disorder were used to exclude instrumental variables with confounding factors and directionally harmonize the data, provided that the three major assumptions of Mendelian randomization of instrumental variables were met. Two - sample Mendelian randomization of the data was performed using the inverse variance weighted method as the main analytical method, with the weighted median method, MR Egger method, simple mode and weighted mode as supplementary analytical methods. Sensitivity analyses were performed using Cochran Q test, MR - Egger intercept analysis and leave - one - out method to test for heterogeneity and pleiotropy and to assess the stability and reliability of the results.
Results In order to exclude the effect of weak instrumental variables and to make instrumental variables strongly correlated with exposure, a more stringent threshold than that of previous studies was used, and a total of 64 single nucleotide polymorphism loci were included as instrumental variables with the P - value threshold set at 5×10⁻¹⁰. The inverse variance weighted method estimated that the risk (OR) of developing substance abuse in schizophrenia was 1.19 times higher than that of the general population (95% CI: 1.126 - 1.261, P = 1.499×10⁻⁹), and the results of the other four analyses also indicated that schizophrenia increased the risk of substance abuse. For the data on
schizophrenia and two groups of alcohol use disorder, the inverse variance weighted method estimated that the risk (OR) of alcohol use disorder in patients with schizophrenia was 1.17 times (95% CI: 1.105 - 1.239, P = 7.398×10⁻⁸) and 1.13 times (95% CI:1.072 - 1.187, P = 3.124×10⁻⁶) that of the general population, respectively. The evaluation results of the weighted median method, simple mode and weighted mode also provided evidence that schizophrenia increased the risk of alcohol use disorder.
Conclusion The existence of a positive causal effect of schizophrenia with substance abuse and alcohol use disorders provides an important idea and basis for subsequent clinical research.

Objective To investigate the composition and change of respiratory diseases in a tertiary hospital in Hainan Province, and to provide reference for scientific prevention and control of diseases, dynamic allocation of medical resources and discipline development planning.Methods The home page information of respiratory patients in a tertiary hospital in Hainan Province from 2019 to 2023 was selected, and the diseases were classified according to ICD-10 classification standard, and the gender, age, disease distribution and seasonal distribution of inpatients were retrospectively analyzed.Results A total of 25 003 inpatients were hospitalized from 2019 to 2023, with a male/female ratio of 1.60∶1; the majority of inpatients were middle-aged and the elderly, the least were children and adolescents, but the proportion of both increased year by year; the most patients were hospitalized in winter and the least in autumn; the rank change of inpatient diseases was statistically significant (P<0.001), influenza and pneumonia always ranked first, chronic lower respiratory diseases showed a downward trend year by year, and other diseases of respiratory system showed an upward trend year by year; the inpatient diseases were mainly influenza and pneumonia (48.2%), the proportion of inpatient diseases in infants (0-3 years old) was the highest (81.9%), and the proportion of inpatient diseases in adolescents (7-17 years old) was the lowest (37.3%).Conclusion It is necessary to strengthen health education, improve disease cognition, dynamically allocate medical resources according to the distribution of diseases, and strengthen the discipline construction and special disease management of pediatrics, geriatrics and respiratory medicine.

Objective To compare the changes in hospitalization expenses before and after the implementation of DIP payment reform measures in hospitals, and further analyze and evaluate the performance of medical services.Methods The data of the first quarter of 2023 before DIP payment reform and the data of the first quarter of 2024 after DIP payment implementation in a hospital were collected in this research to analyze the the changes in hospitalization expenses and medical service performance.Results After DIP payment reform, the total hospitalization expense and the out-of-pocket expense for patients were significantly reduced, and the difference was statistically significant (P<0.05). The ratio of medical expenses was significantly increased, and medical service performance indicators such as CMI, total DRG, time consumption index, cost consumption index, and low-risk mortality rate were improved.Conclusion DIP payment reform is effective in controlling hospitalization expenses, reducing patients′ out-of-pocket expenses, building acceptable hospitalization expense structure, and significantly improving medical services performance.

Objective To analyze the impact of age and surgical procedures on hospitalization costs for lung cancer patients undergoing surgery.Methods The study focused on surgical patients who were primarily diagnosed with lung cancer (C34.) in a tertiary hospital in Ningbo from January 1, 2022 to December 31, 2022, and analyzed their DRG enrollment status. Differential analysis of patient costs in the DRG group using t-test and analysis of variance based on age and surgical procedures.Results A total of 2 489 lung cancer surgery patients were all assigned to the EB1 chest surgery group. There was no statistically significant difference (P>0.05) in the impact of age and surgical procedures on patient costs between EB11 major chest surgery with severe complications and comorbidities. The hospitalization costs of patients over 60 years old in the group of EB13 major chest surgery with general complications and comorbidities and in the group of EB15 major chest surgery without complications and comorbidities were significantly higher than those of patients under 60 years old (P<0.05). As age increased, hospitalization costs increased, and the amount of medical insurance losses in hospitals increased, with statistical significance (P<0.05). Except for no difference in hospitalization costs between lobectomy and total pneumonectomy, there was a statistically significant difference in hospitalization costs among other surgical procedures in the EB13 group (P<0.05). Except for no difference in hospitalization costs between partial lobectomy, lobectomy and pneumonectomy, all other surgical procedures showed statistically significant differences (P<0.05) in the EB15 group. As the surgical resection range increased, hospitalization costs increased, the medical insurance losses increased in the hospital, and the difference was statistically significant (P<0.05).Conclusion The hospitalization costs of lung cancer patients undergoing surgery are greatly influenced by age and surgical procedures. When optimizing the DRG grouping scheme, it is necessary to improve the compatibility with clinical practice and further refine it with full consideration of the actual clinical situation.

Objective To explore the latent profile category of team Cha-xu among clinical nurses and its influence on job withdrawal behavior, and provide some reference for the management of clinical nurses.Methods Clinical nurses were selected from two tertiary hospitals in Wenzhou, Zhejiang Province from January to April 2023 by convenience sampling. The basic data questionnaire, perceived climate of team Cha-xu scale and job withdrawal behavior scale were used in the investigation.Results A total of 392 clinical nurses were included in the study. The score of perceived climate of team Cha-xu in clinical nurses was 41.15±8.07. The model fitting effect of three latent profile categories was best, namely "insider" with low scores, accounting for 28.06%; "intermediate", accounting for 41.07% and "outsider" with higher scores, accounting for 30.87%. Nurses with different professional titles, work relationship and monthly income showed significant differences in perceived climate of team Cha-xu (P<0.05). The score of job withdrawal behavior was 18.13±3.39. The nurses in different perceived climate of team Cha-xu category had different job withdrawal behaviors (F=4.883, P<0.05). The pairwise comparison results showed that there was no significant difference between "insider" and "middleman" (P>0.05), while there was significant difference between "outsider" and "insider", "outsider" and "middleman" (P<0.05).Conclusion Nursing managers should pay attention to the impact of perceived climate of team Cha-xu on job withdrawal behaviors, strive to improve their own management level, create a harmonious working atmosphere, and give clinical nurses full support and care, so as to reduce the perceived climate of team Cha-xu and the job withdrawal behavior.

In February 2024, the International Agency for Research on Cancer team updated and published Global Cancer Statistics Report 2022 in the authoritative journal CA: A Cancer Journal for Clinicians under the American Cancer Society. This report covers updated data on the incidence and mortality of 36 types of cancer from 185 countries and regions worldwide, and analyzed the recent trends, potential influencing factors, and prospects for global cancer prevention and control of 10 major cancer types from 20 different regions worldwide. The report predicts the heavy burden of cancer by 2050 based on global population trends and emphasizes the urgency of investing in cancer prevention and control. The team from the Cancer Hospital of the First Affiliated Hospital of Xinxiang Medical University has reviewed the report and provided a brief interpretation based on the prevalence trends and disease burden of major cancers in China.

Objective To analyze the epidemiological characteristics of malignant tumors collected from the monitoring points of China′s cause of death surveillance system in 2021, to grasp the loss of life expectancy due to malignant tumors in China′s population and analyze the factors affecting it, and to estimate the burden of disease due to malignant tumors in China in.Methods The malignant tumour mortality rate and potential years of life lost of Chinese residents were calculated by different age and gender groups by using Excel 2021 and SPSS 26.0 software. Results The mortality rate of malignant neoplasms in our cause of death surveillance system in 2021 was 164.2/100000, and the median rate was 156.7/100000. The top 5 in potential years of life lost and mortality were lung, liver, stomach, colorectal, and esophageal cancers. The potential years of life lost due to cancer deaths in our population in 2021 totaled 4575932 person - years, resulting in a loss of 370.54 billion yuan in GDP for the whole society. Conclusion The burden of malignant tumors in China remains heavy, with obvious regional, age and gender differences in the burden of malignant tumors. Measures such as improving the cancer prevention and treatment system and promoting measures such as cancer screening and early diagnosis and treatment are crucial to reducing the burden of malignant tumors.

Objective To analyze the main disease composition of inpatient deaths in a tertiary comprehensive hospital
from 2016 to 2022, and provide a basis for the hospital to further reduce case fatality rates. Methods Medical record data suchas name, gender, age, discharge diagnosis, disease code, etc. were extracted from the electronic medical record system of a tertiary comprehensive hospital from January 1, 2016 to December 31, 2022. According to the International Classification of Diseases (ICD - 10), Excel 2016 and SPSS 25.0 were used to perform statistical analysis on the data. Results From 2016 to 2022,the number of deaths was 3777, with the case fatality rate of 1.14%. Among them, the case fatality rate of male (1.60%) was higher than that of female (0.73%), and the difference was statistically significant (χ² ＝ 564.778, P ＜ 0.001). With the increase of age, the case fatality rate gradually increased, with the highest case fatality rate 5.09% for those aged 90 and above,and the highest number of deaths occurring in the 70 - 79 age group. The top three causes of death were tumors, circulatory system diseases, and respiratory diseases. Conclusion It is necessary to pay attention to the health status of male and elderly groups,and strengthen the promotion of health knowledge. Tumors, circulatory system diseases, and respiratory system diseases are the
main causes of death. It is necessary to strengthen talent development and technological innovation in corresponding departments to reduce case fatality rates.

Objective To explore the risk factors of unplanned re-intubation in patients with acute respiratory failure treated with nasal high-flow oxygen therapy (HFNC), and to construct a risk prediction model based on independent risk factors to analyze the predictive value of these risk factors. Methods A total of 198 patients with acute respiratory failure who were hospitalized in our hospital and received HFNC treatment from September 2020 to August 2023 were retrospectively selected. According to whether there was unplanned re-intubation, the patients were divided into the re-intubation group (n = 37) and the non-re-intubation group (n = 161). Univariate analysis and multivariate logistic regression analysis were used to obtain independent risk factors. A risk prediction model was constructed based on the regression analysis method, and the predictive efficiency of the model was tested by the receiver operating characteristic curve and the calibration curve. In addition, 85 patients who were treated from September 2023 to June 2024 were selected as the validation set. The ROC curve and calibration curve were drawn using the data of the validation set to externally verify the predictive efficiency of the model. Results The results showed that age, smoking history, Acute Physiology and Chronic Health Evaluation II score (APACHE II score), duration of invasive mechanical ventilation, residual volume of secretions, high oxygen flow rate setting, and comorbid chronic lung disease were independent risk factors for unplanned re-intubation in patients with acute respiratory failure treated with HFNC (P < 0.05). The area under the curve of the constructed risk prediction model was 0.878, indicating good discrimination ability of the model. The mean absolute error of the calibration curve was 0.015, and the calibration curve was close to the ideal curve, suggesting that the model had good calibration performance and was reliable and stable. The results of the ROC curve and calibration curve of the validation set were good, indicating that the model had good external predictive efficiency. Conclusion The occurrence of unplanned re-intubation in patients with acute respiratory failure treated with HFNC is affected by risk factors such as age, smoking history, and APACHE II score. The risk prediction model constructed based on each independent risk factor has good predictive performance, which can provide a basis for preventing unplanned re-intubation clinically and rationally allocating medical resources.

Objective To explore the relationship between respectful leadership, psychological security and employee satisfaction, in order to provide reference for hospital managers to improve employee satisfaction.Methods Respectful leadership scale, psychological safety scale and job satisfaction scale were used to conduct a questionnaire survey on employees for descriptive analysis, correlation analysis and a structural equation model was constructed based on the results.Results The total score of respectful leadership was (45.82±10.25), psychological safety was (17.31±3.43) and employee satisfaction was (26.90±5.88). Pearson correlation analysis showed that there was a significant positive correlation between the three variables, and the absolute value of correlation coefficient ranged from 0.335 to 0.583 (P<0.01). Respectful leadership had no direct predictive effect on employee satisfaction (β=0.05, P>0.05), the indirect effect coefficient of respectful leadership on employee satisfaction was 0.35, the total effect coefficient was 0.40, and the mediating effect accounted for 87.5%. This indicates that respectful leadership indirectly affects employee satisfaction through psychological safety.Conclusion Psychological safety plays an mediating role in the relationship between respectful leadership and employee satisfaction. The management departments can evaluate the performance of respect for subordinates by leaders, advocate respectful leadership, and improve the psychological security and satisfaction of employees.

Objective: To analyze the current situation of the spatial layout of medical services in secondary and tertiary hospitals in Yantai City, and provide a reference for the further construction and planning of medical resources and the improvement of the accessibility of medical services for residents. Methods: Taking the secondary and tertiary hospitals in Yantai City as the center, the actual coverage of medical services was calculated according to the GIS network analysis model, Thiessen polygons and other methods. Results: On average, each tertiary hospital in Yantai City serves 30.15 residential areas, with an average shortest distance to seek medical treatment of 10.19 km, and 80.36% of the residential areas can be covered within 15 minutes. Each secondary hospital serves an average of 15.87 residential areas, with an average shortest distance to seek medical treatment of 4.28 km. The areas within 30 minutes can basically connect the junctions of various districts and counties, and the service range within 60 minutes covers the whole city. Conclusion: The relevant departments should attach importance to the weak areas in the spatial layout of medical services in secondary and tertiary hospitals, improve the current situation of the fragmented distribution of the service areas of tertiary hospitals, promote the rational distribution of medical resources, and form a new pattern of spatial development.

Objective To construct a machine learning model for predicting intraoperative blood transfusion, guide clinical blood transfusion strategies, and promote the informatization construction of clinical anesthesia. Methods The characteristics potentially related to blood transfusion of patients undergoing elective surgeries in a hospital in Ji'an City from January 2020 to March 2023 were retrospectively collected. Data analysis was carried out based on Python, R language, and SPSS. Feature screening was performed through logistic regression, lasso regression, and Boruta algorithm. Twelve basic models were constructed by balancing the data set with the Borderline Synthetic Minority Over-sampling Technique (Borderline SMOTE) and the undersampling technique of removing pairs of too-close samples (Tomek Links) algorithm. The final model was selected and explained using SHAP values. Results A total of 12,906 patients were finally included in the study. Age, preoperative hemoglobin, albumin, operation duration, intraoperative blood loss, ASA grade, and body weight were selected as the final features. A prediction model was constructed by combining the Gradient Boosting Decision Tree, Borderline SMOTE, and Tomek Links. The area under the curve was 0.955, the recall rate was 0.947, the specificity was 0.932, the precision was 0.365, the accuracy was 0.925, the negative predictive value was 0.997, the F1 score was 0.527, and the average accuracy was 0.700. An online application program was constructed based on the Streamlit framework. Conclusion This study has constructed a simple, convenient, accurate, and interpretable risk prediction model for intraoperative blood transfusion, providing a theoretical basis for promoting intelligent preoperative anesthesia assessment.

Objective To classify hospitalized patients' diseases based on cost structure, and to provide data reference for controlling medical costs and optimizing the structure of medical income. Methods The first page information of inpatient cases from January 2023 to June 2024 in a tertiary hospital in Beijing was selected to extract inpatient expense details, and patients were categorized based on the ICD - 10 disease diagnosis codes of their primary discharge diagnoses. K - means clustering analysis was used to classify diseases according to cost structure, so as to analyze the characteristics of each category's cost structure. Results Based on cost structure, patient diseases were classified into four categories. Category 1 included diseases with high consumable costs, mainly comprising pyonephrosis, ureteral stones, and unstable angina pectoris; category 2 had the highest diagnostic fees, including unspecified liver cirrhosis, alcoholic liver cirrhosis, chronic hepatitis B without delta agent, etc.; category 3 featured balanced proportions across all fee types, including installation and adjustment of urinary devices, unspecified liver
malignancies, medical abortion without complications, etc.; category 4 had relatively higher medication costs, including other specified medical care, chronic liver failure, and chemotherapy sessions for tumors, among others.Conclusion Although high consumable or medication costs may be due to treatment requirements of certain diseases, it is still necessary to reduce expenses through multiple links such as procurement, usage, and management to effectively control medical costs and improve the quality of medical services.

Objective To construct a prediction model for dysphagia in elderly patients with chronic obstructive pulmonary disease (COPD) based on the BP neural network method. Methods A retrospective analysis was conducted on 313 COPD patients who were treated in the Second People's Hospital of Pingxiang City from June 2021 to June 2024, among whom 58 had dysphagia. SPSS was used for propensity score matching, with gender, the same age (±3 years), and the same Modified Barthel Index (MBI) (±1 point) as the matching factors. Among them, 13 patients with dysphagia did not find matching objects, and the clinical data of 40 patients without dysphagia were missing. Finally, 45 patients were included in the dysphagia group and 155 patients were included in the non-dysphagia group. Questionnaires and surveys were used to collect the general information of the patients. Univariate and logistic regression analyses were used to analyze the significant influencing factors, and a prediction model for dysphagia in COPD patients was constructed based on the BP neural network method.Results The results of logistic regression analysis showed that smoking history, nutritional status, number of missing teeth, whether to concentrate on eating, eating posture, partial pressure of carbon dioxide, types of medications, degree of dyspnea, and severity of the disease were influencing factors of dysphagia in COPD patients (all P < 0.05). When constructing the BP neural network, the prediction accuracy of the modeling set was 88.10%, and the prediction accuracy of the validation set was 89.40%. The area under the curve (AUC) of the model was 0.926 (95% CI: 0.892-0.966), the sensitivity was 80.00%, the specificity was 90.30%, and the Youden index was 0.703. Among them, the degree of dyspnea (100.00%), the severity of the disease (91.80%), and the number of missing teeth (74.60%) were the top three influencing factors in terms of the importance ranking of independent variables. Conclusion The prediction model for dysphagia in elderly COPD patients constructed based on the BP neural network method has good fitting performance and can provide a reference for relevant clinical studies.

Objective To explore the influencing factors of incision infection after open reduction and internal fixation (ORIF) of tibial fractures, develop an individualized nomogram prediction model and verify it. Methods The clinical data of 180 patients with tibial plateau fractures who received ORIF treatment in our hospital from February 2021 to September 2022 were retrospectively analyzed, and the occurrence of postoperative incision infection in these patients was analyzed. The potential warning indicators of incision infection after ORIF of tibial fractures were preliminarily screened by lasso regression; the influencing factors of postoperative incision infection were analyzed by multivariate binary logistic regression; an individualized nomogram prediction model was constructed; the goodness of fit, calibration degree and clinical applicability of the individualized nomogram prediction model were evaluated by Hosmer-Lemeshow test, calibration curve and decision curve; and the receiver operating characteristic (ROC) curve of the model was drawn. In addition, 180 patients with tibial plateau fractures who received ORIF treatment in our hospital from October 2022 to May 2024 were selected for external verification. Results Among 180 patients with tibial plateau fractures who received ORIF treatment, 38 cases had incision infection, with an incidence rate of 21.11%, including 14 cases (7.78%) of deep infection and 24 cases (13.33%) of superficial infection. Compared with the non-infected group, the infected group had a higher body mass index (BMI), a longer operation time, and a higher proportion of smoking, diabetes mellitus, open injury, and American Society of Anesthesiologists (ASA) grade III-IV (P < 0.05). BMI, smoking, diabetes mellitus, open injury, ASA grade, and operation time were potential warning indicators of incision infection after ORIF of tibial plateau fractures. BMI, smoking, diabetes mellitus, open injury, ASA grade, and operation time were influencing factors of incision infection after ORIF of tibial plateau fractures. The Hosmer-Lemeshow test (χ² = 3.998, P = 0.857) suggested that the individualized nomogram prediction model had a high goodness of fit. The calibration and decision curves indicated a high calibration degree and good clinical net benefit. The ROC curve showed that the area under the curve (AUC) was 0.918, the 95% confidence interval (CI) was 0.868-0.954, the sensitivity was 81.58%, and the specificity was 88.73%, suggesting that the individualized nomogram model had a high predictive efficiency. External verification showed that the prediction model established based on the data of the modeling group had good discrimination and consistency. Conclusion The individualized nomogram prediction model constructed in this study based on BMI, smoking, diabetes mellitus, open injury, ASA grade, and operation time can effectively predict the occurrence of incision infection after ORIF of tibial plateau fractures, which is helpful to reduce the occurrence of postoperative incision infection and promote the rapid recovery and good prognosis of patients.

Under the backdrop of the ‘Healthy China’ strategy, it is essential to evaluate and analyze health service productivity in China. This study aims to investigate the factors influencing health service productivity by systematically examining
and analyzing literatures from both domestic and international sources. Through a comprehensive review of the current state of measuring health production efficiency, influencing factors, and research methods, this study identifies gaps and obstacles in existing research. The goal of this paper is to offer a robust literature foundation and theoretical framework for a more precise evaluation of health service productivity efficiency, as well as for enhancing healthcare resource allocation and service quality.

Objective To analyze the internal composition and correlation of hospitalization expenses of negative difference cases in gynecological DRG disease group, so as to provide decision - making reference for hospitals to optimize the cost structure and realize the fine management. Methods The medical insurance year - end liquidation data of the DRG group (a total of 13 groups) with more than 100 cases of gynecological diseases in a tertiary hospital in 2023 were collected. The structural change degree method was used to analyze the changes in the internal composition of hospitalization expenses, and the new grey correlation analysis was used to evaluate the correlation between each subdivision cost and the total hospitalization cost.Results The proportion of negative balance in 8951 cases was 50.2%. There were 8 groups with more than 50% negative difference cases in each DRG group. The three groups with the highest degree of structural change were NZ13 (other diseases of female reproductive system with general complications and comorbidities), NB13 (female reproductive system reconstruction surgery with general complications and comorbidities), and RE13 (malignant proliferative diseases chemical and/or targeted, biological treatment with general complications and comorbidities). The contribution rate of inspection fee was higher in each group, followed by

operation fee. The top three of the correlation degree of the subdivision cost and the average cost with hospitalization expenses were operation cost (0.744), inspection cost (0.743) and drug cost (0.712). Conclusion It is necessary to pay attention to the fees of surgical items, carry out reasonable inspections, scientifically control the proportion of drug consumption and rationally adjust the cost structure, standardize the quality of the medical record home page,optimize the clinical pathway, and reduce the occurrence of negative difference cases through various measures.

Objective To analyze and summarize the research literature on the integration of medical care and elderly care in China, and provide theoretical support for the healthy and orderly development of the integration of medical care and elderly care in China. Methods Taking the literature from domestic core journals included in CNKI, Wanfang, and VIP databases as the data source, CiteSpace and Excel software were used to analyze the number of published papers, authors, research institutions, and keywords of the research on the integration of medical care and elderly care in China from 2014 to 2024. Results The overall number of published papers on the integration of medical care and elderly care in China showed a trend of first increasing and then decreasing; the teams engaged in the research on the integration of medical care and elderly care were concentrated in various universities and scientific research institutes, and many productive authors emerged; in terms of regional distribution, they were mostly concentrated in economically developed regions such as Beijing, Shanghai, Nanjing, Zhejiang, and Wuhan; however, there was a lack of cooperation among institutions and authors, and no authoritative research institutions and authors had been formed yet; the research in the field of the integration of medical care and elderly care in China involved many aspects such as the service subjects, service contents, service objects, and service models of the integration of medical care and elderly care; the analysis combining keyword clustering and burst keywords showed that the field of the integration of medical care and elderly care in China was roughly divided into three stages: the main research stage (2014-2017), the reflection stage (2018-2020), and the deepening stage (2021-2024). Conclusion Certain achievements have been made in the research field of the integration of medical care and elderly care in China, and the academic community has conducted in-depth research on various aspects of this field. However, there is a lack of authoritative research institutions and authors.

Objective To linearly weight the results of inverse distance weighted interpolation (IDW), ordinary Kriging interpolation (OK) and thin plate spline interpolation (TPS), and fit a comprehensive model of ensemble interpolation to objectively and comprehensively reveal the spatial pattern of diseases. Methods Taking the mortality rate of liver cancer at county level in Guangxi for example, we revealed the death risk via IDW, OK and TPS interpolation models, and compared the mean prediction error (MPE), root - mean - square prediction error (RMSE), R - square (R2) value and the fitting smoothness of spatial interpolation maps between the IDW model, the OK model and the TPS model. Then, we used the RMSE of above specific models to generate weights to linearly weight single interpolation models, and estimated the death risk of liver cancer across Guangxi by a comprehensive model of ensemble interpolation.
Results The fitting indicators of IDW, OK and TPS models were somewhat inconsistent, and each model had its advantages and disadvantages. Specifically, from small to large, the MPE was TPS (0.002), OK (0.004) and IDW (0.020), respectively, and the accuracy of TPS was better than that of OK. From small to large, RMSE was OK (0.349), TPS (0.362) and IDW (0.390), respectively, and the variability of OK was better than that of TPS. From small to large, R2 was OK (0.47), TPS (0.44) and IDW (0.37), respectively, and OK was better than TPS in fitting accuracy. The comprehensive model of ensemble interpolation integrated the advantages of above three models and overcame the instability of specific models, with MPE, RMSE and R2 being 0.005, 0.352 and 0.43, respectively. Conclusion IDW, OK and TPS interpolation models have their own advantages in estimating the spatial patterns of diseases, but findings of different models are inconsistent to some extent. The comprehensive model of ensemble interpolation reduces the uncertainty of each single model, balances the advantages and disadvantages of each single model and generated a comprehensive evidence to reveal the spatial pattern of diseases, via weighting above three single models.

Objective To construct a medical mental damage compensation model based on Ordinary Least Squares (OLS) regression, so as to analyze the influencing factors of mental damage compensation in medical damage liability dispute cases. Methods Taking 830 medical damage dispute cases as the research objects, relevant factors were included in the OLS regression analysis through analysis of variance, and a linear regression model was constructed. Results The medical mental damage compensation model showed that the western and northeastern regions in the factor of "region" were negatively correlated with mental damage compensation (P < 0.05), while hospital liability, claimed compensation amount, and disability grade were positively correlated with mental damage compensation (P < 0.05). Conclusion The medical mental damage compensation model is simple with simplified indicators, which is convenient for judges to refer to the data. It is helpful for the pre-litigation settlement of medical disputes and further plays the role of people's mediation in doctor-patient disputes.

Objective The study aimed to sort out the research hotspots and development trend in this field in the past 10 years, and to provide reference for the research of cancer prognosis prediction model, through the econometric statistics and
visual analysis of the related research of cancer prognosis prediction model. Methods Web of Science, PubMed, and CNKI databases were used as the search sources, and the literature on cancer prognosis prediction model published in the Chinese and English search sources from Jan. 1st, 2013 to June 15th, 2024 was analyzed and visualized based on CiteSpace, VOSviewer software, and the bibliometrix package of the R language.Results A total of 1341 Chinese articles were retrieved through the CNKI database, with 1322 valid articles remaining after duplication. From the WOS and PubMed databases, 2069 and 3284 English articles were retrieved, respectively. After merging and duplication, 4908 valid English articles were retained. The overall trend of publications from 2013 to 2024 was upward. The country with the most publications in English literature was China (2270 articles), the institution with the most publications was Fudan University (268 articles), and the institution with the most publications in Chinese literature had only five articles. The authors who have published the most Chinese literatures were Wang Debin (5 articles), Chai Jing (5 articles), and Liu Yang (5 articles), and the author who published the most English literature was Wang Wei (24 articles). The high - strength emerging words in both Chinese and English literature were breast cancer (Chineseemergent strength: 8.95, English emergent strength: 11.06), and the clustering results showed that the related studies of colorectal cancer, bladder cancer, prostate cancer, machine learning were more prominent. Conclusion Cancer prognostic prediction modeling is receiving more and more attention from experts and scholars, covering more cancer types and richer research methods. Machine learning algorithms are being used more often, and the nomogram visualizes the results to better guide clinical practice. The application of genome - wide association analysis in the field of cancer prognosis prediction is expected to be a potentially promising research direction. Universal collaboration among countries, institutions, and authors has not yet been established, and there is a need to further strengthen the cooperation for deeper academic cross - fertilization. The cancer - suppressive mechanisms of
iron death and copper death have received more attention and have a broad clinical research prospect.

Objective To understand the hospitalization situation of diabetic patients in Tianjin and the changing trends of the composition of their hospitalization expenses before and after the implementation of the DRG payment reform policy, and to analyze the effectiveness of the DRG policy reform and the possible existing problems. Methods Based on the medical insurance settlement data in Tianjin before and after the implementation of DRG from 2021 to 2023, the degree of structure variation (DSV), grey correlation analysis (GRA) and interrupted time series (ITS) analysis were used to study the impact of the DRG policy on the hospitalization situation and expenses of diabetic patients. Results Compared with before the reform, the emergency admission rate of hospitalized diabetic patients increased after the reform ($P < 0.001$), while the length of hospital stay, hospitalization expenses, comprehensive medical service fees, drug fees, health material fees and individual out-of-pocket expenses all decreased ($P < 0.001$). The results of DSV and GRA analysis showed that the main factors affecting the hospitalization expenses of diabetic patients were examination fees, laboratory test fees, comprehensive medical service fees and drug fees. The results of ITS analysis showed that after the DRG reform, the average inpatient expense per visit decreased by 281.50 yuan ($P < 0.001$), and the monthly growth rate reversed from 56.15 yuan before the reform to -42.51 yuan ($P < 0.001$), and the reduction rate of individual out-of-pocket expenses increased ($P < 0.001$). Except for the examination fees, the growth trends of the composition of various hospitalization expenses all reversed ($P < 0.001$). Among them, the comprehensive medical service fees had the largest reduction, and the monthly growth rate reversed from 21.68 yuan before the reform to -17.23 yuan ($P < 0.001$), followed by drug fees, laboratory test fees and health material fees. Conclusion The DRG payment method reform in Tianjin has achieved remarkable results, with obvious achievements in reducing costs and increasing efficiency, effectively reducing the economic burden on patients. However, the increase in the emergency admission rate and the still unreasonable expense structure suggest that the DRG reform still needs further optimization.

Objective  To systematically evaluate the effect of dapagliflozin on glucose and lipid metabolism in patients with stage Ⅲ of diabetic nephropathy (DN-Ⅲ). Methods  Randomized controlled studies (RCTs) on the effect of dapagliflozin on glucose and lipid metabolism in patients with DN-Ⅲ were retrieved. Literature was screened, the data were extracted, and RevMan 5.4.1. was used for quality evaluation. Results  A total of 2107 patients were included in 23 studies. Meta results showed that compared with the control group, dapagliflozin significantly reduced HbA1c, FBG, PBG, HOME-IR and significantly increased HOME-β in patients with DN-Ⅲ, but it had little impact on ΔFIns; compared with the control group, dapagliflozin significantly reduced TC, TG, LDL-c and significantly increased HDL-c in patients with DN-Ⅲ; compared with the control group, dapagliflozin significantly reduced SBP and DBP in patients with DN-Ⅲ. In addition, compared with the control group, dapagliflozin could significantly reduce BMI, but there was no significant difference in the incidence of ADR. Conclusion  Dapagliflozin can improve the glucose and lipid metabolism in patients with DN-Ⅲ, and it is safe and effective. However, in view of the limitations of the inclusion study, it still needs to be verified by a well-designed large-scale clinical randomized controlled study.

Objective  To analyze the changes in the structure of outpatient and inpatient costs in a public hospital in Binzhou under the background of new medical reform, and provide references and theoretical basis for further implementing healthcare reform policies in Binzhou. Methods  Outpatient and inpatient cost data from a public hospital in Binzhou City from 2013 to 2022 were collected, and grey correlation method and structural change degree were used to analyze the indicators. Results  Grey relational analysis revealed that, from 2013 to 2022, the top three correlated factors in outpatient expenses were medication expenses, examination fees, and laboratory fees; in inpatient expenses, medication expenses, health material fees, and examination fees were the top three expenses. The results of the structural correlation analysis showed that in both outpatient and inpatient expenses, the change in medication expenses was the largest contributor with a negative change. Conclusion  Under the background of the new medical reform, there have been initial achievements in controlling medication expenses. However, examination fees and health material fees have shown an upward trend and accounted for a relatively high proportion, which requires attention. Technical service fees have been increasing annually but still have a relatively low proportion.

Objective To improve the theoretical level and practical application ability of medical postgraduate students in multivariate statistical analysis, so as to meet the demand for medical practitioners to master statistical analysis methods due to the growth of medical data. Methods By comprehensively using literature resources, a computer simulation case database, a structured case database for data analysis, and an open case database for medical applications were established at multiple levels respectively. The application and implementation of the case database were carried out in the way of "classroom demonstration of simulation case database + structured case guidance in class and after class + open case expansion after class", and various teaching methods were used. At the same time, formative evaluation was adopted. Results Through simulation experiment cases, students' understanding and application ability of the theory of multivariate statistical methods were promoted; through the structured case database, students' statistical analysis ability was improved; through the open case database, students' ability to comprehensively use statistical knowledge to solve complex practical problems was cultivated. In the application and implementation of the case database, students deepened their understanding and application of knowledge by preparing cases in advance, having classroom discussions and completing reports after class. Teachers discovered and solved students' problems in a timely manner through formative evaluation. Conclusion Case databases at different levels complement each other. Through this teaching method, students can be systematically trained to achieve learning goals, and the ability and quality of medical postgraduate students to use multivariate statistical methods to solve practical problems can be improved.

Objective To explore the reasons for the behavior of uploading minor diagnostics with no resource consumption, analyze the impact of this behavior on medical insurance payment, improve the awareness and attention of medical institutions to this problem, and seek targeted solutions from two aspects of hospital management and medical insurance supervision.Methods By comparing medical record filling information and DRG enrollment results, quality control was carried out on randomly selected medical insurance settlement lists, and theoretical research was carried out on cases that received more medical insurance payments. The process of the behavior of uploading minor diagnostics with no resource consumption was sorted out to analyze the deep causes. Results The behavior of uploading minor diagnostics with no resource consumption is prominent, and the high - score group leads to high medical insurance payment. This problem is even more pronounced in comprehensive medical institutions, but existing regulatory instruments are not working well. Conclusion The key to solving this problem is, on the one hand, to strengthen training management in these hospitals, and on the other hand, to solve the practical problems of medical institutions and steer in the right direction.

Objective To explore the problems and countermeasures of medical staff in public hospitals in dealing with public health emergencies, in order to provide valuable reference for improving the emergency response capacity of public hospitals. Methods A stratified sampling method was used to randomly select 593 medical staff from 33 wards of 7 departments in a public Grade Three general hospital in Shandong Province, which were closely related to public health. In order to improve comparability and assess the overall performance level more accurately, this study converted scores into grades, so as to analyze the current situation and influencing factors of public hospital medical staff in responding to public health emergencies, and put forward improvement measures and suggestio.Results The participation rate of medical staff in emergency drills, emergency training and emergency handling in response to public health emergencies was 45.14%, and the qualified rate was 58.40%, both at a low level. The qualified rate of medical staff who did not participate in such activities was only 40.78%, compared with 79.83% who participated in activities, the difference was statistically significant (P < 0.05). The overall score rate of these three aspects was 56.11%, indicating that the level of emergency ability was low, and the average score was (2.81 ± 0.88), which
was significantly lower than the qualified score (P < 0.001). Among the three dimensions, the score rate of emergency rescue ability was the highest (75.34%), followed by personal emergency attitude (73.52%), and the ability to master emergency knowledge was the lowest (65.23%). Conclusion In response to public health emergencies, medical staff in the public hospital need to improve their participation in emergency practice activities, ability to grasp emergency knowledge, personal monitoring and early warning ability, and mental health. It is suggested to strengthen the training of basic emergency knowledge and practical skills of medical staff, improve the monitoring and early warning system, and improve the psychological intervention ability of medical staff.

Objective To retrospectively analyze the inpatient death cases in a tertiary general hospital, so as to understand and master the death situation and causes of inpatients in the hospital in recent years, and provide a scientific and reasonable management basis for the hospital. Methods The inpatient death cases in a tertiary general hospital from 2021 to 2023 were collected and retrospectively analyzed from the aspects of age, gender, department, and disease diagnosis at death. Results There were 819 death cases in this hospital from 2021 to 2023, with a total inpatient mortality rate of 0.58%. The male-female ratio was 1.96:1, and those aged 60 and above accounted for 82.42%. The departments with the most deaths were mainly ICU, Department of Cardiology, Department of Respiratory Medicine, and Department of Neurosurgery. The top three diseases were tumors, circulatory system diseases, and respiratory system diseases. Conclusion With the aggravation of population aging, tumors, circulatory system diseases, and respiratory system diseases have become the main causes of inpatient death in this hospital, and elderly patients are the key objects that need attention.

Objective To explore the correlation between professional self - concept and personal career planning of undergraduate nursing students. Methods Convenience sampling method was used to select 191 nursing undergraduate students from a nursing college in Shandong Province as the survey subjects. The questionnaire survey was conducted by using a general information questionnaire, a professional self - concept scale, and a personal career planning scale. Results The average score of the professional self - concept scale items for undergraduate nursing students was (2.99 ± 0.37), which was above the average; the average score of the items in the personal career planning scale was (3.56 ± 0.54), which was at a moderate level; there was a positive correlation between the two groups (the typical correlation coefficients were 0.661 and 0.412, respectively); and professional self - concept, learning status, and relationships with classmates were the main influencing factors of personal career planning (P < 0.05), jointly explaining 44.2% of the total variation in personal career planning for undergraduate nursing students.
Conclusion The personal career planning of undergraduate nursing students is above the medium level. Education managers and nursing students themselves should attach importance to the cultivation of professional self - concept to improve their personal career planning level.