The implementation of the “14th FiveYear Plan” national medical security plan has accelerated the pace of perfecting the multi-tiered medical security system, continuously improved the medical insurance payment mechanism, and announced the implementation of the DRG/DIP payment mode reform three-year action plan in order to improve the quality, reduce the cost and increase the efficiency of the medical insurance funds. Medical insurance payment policy is closely related to performance management of hospitals. Therefore, this paper analyzes the impact of DRG/DIP payment reform on performance management of public hospitals from the perspective of performance management. And from the five aspects of cost accounting and analysis, talent construction, performance evaluation system construction, information construction and culture construction, it explores the performance management path of public hospitals under the background of DRG/DIP payment, and puts forward targeted suggestions for the performance managemet of public hospitals, in order to inject momentum into the high-quality development of public hospitals.

Objective To understand the current status and hotspots of DRG research in China in order to provide reference for the focus and direction of subsequent research.Methods The literatures related to DRG were retrieved from China National Knowledge Network (CNKI). Descriptive analysis was made on the number of DRG literatures and the years of publication. Social network analysis was used to analyze the core authors, cooperative groups, high-frequency keywords and their relationships in DRG literatures.Results There were 2 602 journal articles with the theme of ‘DRG’ or ‘diagnosis related groups’. After 2015, the number of DRG literatures in China showed a multiple increase, with the annual literatures in 2021 and 2022 exceeding 500. There were 1 072 articles from core journals (41.20%) and 1 530 articles from non-core journals (58.80%). There were 188 core authors in the field of DRG research, mainly forming 7 cooperative groups led by Hu Mu and Guo Moning, with a total of 1 425 publications (54.77%). The network cograph and centrality analysis of high-frequency keywords showed that payment method, DRG prepaid, first page of medical records , hospital management, hospitalization cost and performance evaluation were the high-frequency keywords in the field of DRG research, and their point degree centrality and proximity centrality ranked first. However, the first page of medical records and CMI were more mediation-centered.Conclusion The number of literatures in the field of DRG research increases rapidly in recent years, but the quality of literatures needs to be evaluated and improved. The core authors are relatively concentrated and have strong overall influence and academic leading role. The research hotspot of DRG focuses on DRG payment and DRG performance evaluation and hospital management.

Objective To construct a machine learning model to predict the risk of deep venous thrombosis (DVT) in patients undergoing total hip arthroplasty (THA), and to identify key risk factors influencing DVT using shapley additive explanations (SHAP) method.Methods We retrospectively analyzed data from 416 patients who underwent THA in Wenzhou People′s Hospital from January 1, 2017 to July 31, 2022, and randomly divided them into a training set and a test set in a 4∶〖KG-*2/3〗1 ratio. Recursive feature elimination and five-fold cross-validation were used to select the best features. Six machine learning algorithms were utilized to develop predictive models, and various performance metrics were employed to evaluate them. The SHAP method was used to analyze the interpretability of the optimal model.Results Four hundred and sixteen patients were included in the final study, including 333 in the training set and 83 in the test set. The XGBoost model was the most accurate on the test dataset, achieving a sensitivity of 0.817, specificity of 0.783, F1 score of 0.860, ROC-AUC of 0.800, and a Brier score of 0.106. SHAP summary plots showed that age, cholesterol, postoperative bed time, fibrinogen, and preoperative plasma D-dimer levels were the top five determinants for post-THA DVT. SHAP values feature dependence plots revealed complex non-linear effects of these factors on DVT risk, with age, bed rest, and fibrinogen showing an inverted U-shaped relationship, and cholesterol displaying a positive correlation. Individual SHAP values offered insights into each predictor′s role in DVT risk.Conclusion This study developed an efficient and interpretable machine learning model to predict DVT risk in THA patients, which is helpful for clinical health professionals in identifying high-risk patients and providing personalized intervention.

Objective To provide a multi-dimensional, efficient, and high-quality statistical analysis method for some indicators related to the first page of medical records in the performance appraisal of tertiary public hospitals.Methods Microsoft SQL Server query analyzer was used to connect with the back-end database of the medical record statistics management system, and the data could be statistically analyzed by writing structured query language (SQL).Results By executing the prepared SQL statements, the required data could be queried quickly. The generated statistical results could be intuitive, accurate, and easy to operate. It met diversified statistical needs and effectively improved the data quality, which played an essential role for hospitals to make management decisions.Conclusion The application of SQL statements can effectively solve the difficulties during statistical work in hospitals, and improve the work efficiency and work quality compared with traditional statistical methods. Hospital statisticians in the new era should improve their working skills, innovate their working methods, and provide better services for hospital management.

Objective To investigate the risk factors of early diabetic nephropathy and construct a risk prediction model based on BP neural network algorithm. Methods A total of 1 048 diabetic patients admitted to Yongkang Hospital of Traditional Chinese Medicine from January 2020 to December 2022 were retrospectively analyzed, including 115 diabetic nephropathy patients (10.97%), and were divided into the DKD group (115 diabetic nephropathy patients) and the DM group (933 diabetic patients). The relevant data of patients were collected and matched according to 1∶1 nearest proximity method after the confounding factors were excluded by propensity score matching (PSM). The prediction model was built based on the correlation factors by using the statistically significant indicators in the single factor analysis and BP neural network algorithm. Mean absolute error (MAE) was used to analyze the model efficacy, the predictive value of the risk prediction model was evaluated by receiver operating characteristic curve (ROC), and external validation was performed. The model consistency was evaluated by calibration curve.Results The confounding factors were gender, hypertension, fasting blood glucose and uric acid. After the modeling set was 1∶1 and PSM was performed by the nearest method, the confounding factors were excluded: 95 cases in DKD group and 95 cases in DM group. Univariate results indicated that there were significant differences in age, type 2 diabetes, total cholesterol, urinary protein excretion rate, diabetes course, and cystatin C(CysC) between groups (P<0.05). The prediction accuracy was BP neural network algorithm, decision tree, support vector machine and logistic regression in the descending order. The results of BP neural network showed that the top 4 factors affecting the occurrence of early diabetic nephropathy were proteinuria excretion rate, age, diabetes course and cystatin C(CysC) in order. The AUC  of the prediction model was 0.959 (95%CI: 0.917-1.000), the Yoden index was 0.867, and the corresponding sensitivity and specificity were 0.867 and 1.000, respectively. The external validation-AUC was 0.958 (95%CI: 0.922-0.995), and its sensitivity and specificity were 0.804 and 1.000, respectively. The calibration curve in the calibration diagram was close to the standard curve.Conclusion The BP neural network algorithm model based on machine learning, which takes age, disease course, urinary protein excretion rate, TC, CysC and type 2 diabetes as predictive features, has good predictive value for early diabetic nephropathy, and can be clinically applied to the management and identification of high-risk population.

Objective To predict the outpatient volume of a tertiary general hospital in Zhejiang Province by establishing the seasonal ARIMA model, and to provide a basis for the rational allocation of outpatient human resources.Methods Based on the outpatient visits data of a tertiary general hospital in Zhejiang Province from January 2013 to June 2023, the seasonal ARIMA model was constructed by SPSS software to predict the annual outpatient visits from July 2023 to December 2023. By comparing the measured outpatient visits, the accuracy of the seasonal ARIMA model was evaluated.Results The outpatient volume of the general hospital showed an increasing trend year by year, and showed the characteristics of periodic fluctuations. The optimal seasonal ARIMA model fitted was ARIMA(0,1,1)(1,0,1)12, BIC (Bayesian information criterion) was 5.273, MAPE (mean absolute percentage error) was 14.265, R2 (module determination coefficient) was 0.408, and the overall relative error was 1.83%, indicating good prediction results.Conclusion The seasonal ARIMA model can simulate the change trend of the outpatient volume in the time series of the tertiary general hospital well, and provide a theoretical basis for the short-term forecast of the outpatient volume in the hospital.

Colorectal Cancer (CRC) statistics are updated by American Cancer Society every 3 years based on morbidity provided by the population cancer registry and mortality provided by the National Center for Health Statistics. In 2023, about 153 020 people will be diagnosed with CRC and 52 550 will die from the disease, including 19 550 cases and 3 750 deaths among people under 50 years old. The magnitude of the decline in CRC incidence has changed, from 3%4% per year in 20002010 to 1% per year in 20112019. The proportion of rectal cancer increased from 27% in 1995 to 31% in 2019, and CRC incidence was migrating to the left colon. From 2011 to 2020, CRC mortality overall decreased by 2% per year, but CRC mortality increased by 0.5%3.0% per year in the native Americans under 50 years old and under 65 years old. In summary, despite the continual decline in overall mortality, CRC is rapidly shifting towards younger, more advanced stages and development in the left colon/rectum. In this paper, the important contents of the updated data are sorted out and briefly interpreted. At the same time, compared with the present situation of CRC in our country, we can reveal and analyze the cause of the rising incidence of CRC to provide reference for CRC diagnosis and treatment.

Objective To explore the relationship between childhood trauma experience and anxiety, depression and suicide risk in HIV/AIDS patients, and to provide evidence support and epidemiological basis for early identification and intervention of psychological problems of people living with HIV/AIDS (PLWHA).Methods Participants were recruited at an AIDS outpatient department. The generalized anxiety disorder scale-7 items (GAD-7) was used to assess patients′ anxiety levels; patient health questionnaire-9 items (PHQ-9) was used to assess patients′ depression; the brief international neuropsychiatric interview suicide questionnaire section was used to assess suicide risk; and the childhood trauma questionnaire was used to assess childhood trauma. Count data were described with frequency and composition ratios, and comparisons between groups were made using chi-square tests, and the strength of association was expressed by OR and its 95% confidence interval(CI).Results Among the 470 patients investigated, 64.7% of PLWHA had traumatic childhood experiences, and the prevalence of childhood emotional and physical abuse was higher than that of patients without anxiety symptoms (P<0.05); 54.5% of PLWHA suffered from depressive symptoms. Those who were emotionally and physically abused in childhood had 4.8 times (OR=4.792, 95% CI:1.896-12.110) and 3.1 times (OR=3.130, 95% CI:1.430-6.851) the risk of suicidal ideation than those who were not, respectively.Conclusion PLWHA with childhood traumatic experiences are more likely to develop anxiety depression and increase the risk of suicide. Special attention should be paid to the mental health status of PLWHA, especially those who have experienced childhood emotional and physical abuse, and appropriate psychological interventions should be designed as early as possible to prevent suicide and other adverse events. 

Meta-analysis is the statistical combination of results from two or more studies, but the results are influenced by some factors including publication bias. Funnel plots and tests for funnel plot asymmetry have been widely used to examine bias in the implementation of meta-analysis, but they are often wrongly used by some researchers. In this paper we introduce some basics about funnel plots and contour-enhanced funnel plots, and show some cases of incorrect or correct use of funnel plots in some published articles in domestic and foreign journals, and we also provide some recommendations for rational use of funnel plots and asymmetry tests of funnel plots.

Objective To use Power BI Desktop for multidimensional comparative analysis and data visualization of hospital DIP subgroup details, in order to identify the causes of DIP losses in hospitals.Methods The data were extracted from the DIP subgroup discharge settlement details of a tertiary oncology hospital in 2022. Methods such as data import, data type conversion, data relationship establishment, data modeling, and data visualization were used to build dynamic analysis reports for different dimensions such as the entire hospital, departments, and disease categories.Results Power BI Desktop can effectively enhance the level of fine management for DIP, improve work efficiency, accurately analyze the causes of losses, guide departments in making improvements, and effectively reduce the DIP insurance fund losses for the hospital.Conclusion Power BI Desktop is characterized by its low cost, customization, high level of visualization and automation, as well as a user-friendly interface, making it suitable for promotion in hospitals, especially those with low levels of informatization, insufficient specialized operational personnel, and limited budget for DIP fine management.

Objective To explore a data statistical analysis and visualization display method based on Power BI under the background of performance evaluation in tertiary public hospitals, so as to improve the efficiency of hospital statisticians′ data statistics and analysis; to promote the efficiency and quality of medical management by using visualization, to assist in daily indicator monitoring, and to assist management and decision-making.Methods The first page data of medical records were extracted from a tertiary public hospital from January 1, 2022 to June 30, 2023 to establish a power BI based first page index data query system for performance evaluation of tertiary public hospitals based on the statistical caliber of the first page index data of medical records for performance evaluation of tertiary public hospitals, for data analysis and visual display.Results The performance evaluation medical record homepage indicator data query system for tertiary public hospitals based on Power BI can quickly query multi-dimensional and multi scenario indicator data, which is practical and easy to operate.Conclusion Power BI can be used as a tool for hospital statistical staff to conduct data analysis and visual display, which is worth promoting and using. Hospital statistical staff can combine this study to apply Power BI to practical work, improve work efficiency, and assist daily statistical work.

Objective To evaluate the current status of chemotherapy for malignant tumors in the surgical department in a tertiary hospital in southern Guangzhou with Diagnosis Related Groups indicators, and to provide reference for the hospital to formulate treatment strategies for chemotherapy patients.Methods The first page data of medical records of the patients in RU14 group classified by CN-DRG (version 2019) were collected in a hospital discharged from the surgical department and the oncology department in 2019. Total weight, time consumption index, and cost consumption index were used to describe the development of the surgery department. Multiple linear regression was used to analyze the relationship between the time consumption index and cost consumption index and different departments.Results In this hospital, 64.5% of RU14 group patients were admitted to the surgery department, mainly with postoperative chemotherapy. The number of patients admitted to the RU14 group ranked first in the surgical department, but the weight output was low. The time consumption index of the surgery department was 0.77, and that of oncology department was 1.05. By multiple linear regression analysis, the time consumption index of the surgery department was lower than that of the oncology department (t=-9.650, P<0.001). The cost consumption index of the surgery department was 1.14, and that of the oncology department was 1.09. According to multiple linear regression analysis, the relationship between the cost consumption index and the departments was not statistically significant (t=1.117, P=0.264).Conclusion The application of DRG index to analyze the current situation of patients treated with chemotherapy for malignant tumors in the surgery department can provide important guidance for the development of the department.

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 reveal the causal relationship between depression and interstitial lung disease (ILD) by using Mendelian randomization method, and to provide new ideas for the prevention, treatment and prognosis of ILD.Methods The genetic loci closely associated with depression were selected as instrumental variables using pooled data from the Genome-Wide Association Study (GWAS). The inverse variance weighting method was used as the primary analysis method, and the weighted median method and MR-Egger regression were used as auxiliary methods to perform two-sample Mendelian randomization analysis; OR values were used to evaluate the causal relationship between depression and ILD, and heterogeneity tests, gene multiplicity tests and sensitivity analyses were performed to assess the stability and reliability of the results.Results Thirty-seven single nucleotide polymorphism (SNP) loci were included as instrumental variables. MR-Egger regression estimated that the risk of lung cancer in patients with depression was 1.21 times that of healthy people (95%CI: 1.075-1.361, P=0.002). The weighted median method also supported a causal effect between depression and interstitial lung disease (95% CI: 1.118-1.564, P=0.001). The heterogeneity test results of the inverse variance-weighted method and MR-Egger regression showed that there was no heterogeneity; MR-Egger regression intercept term and MR-PRESSO method tests showed that the results were less likely to be affected by gene pleiotropism; no non-specific SNPs were found in leave-one-out analysis.Conclusion There may be a positive causal association between depression and ILD.

Objective To evaluate the reports of adverse events of vortioxetine and data analysis to provide reference for drug safety in clinical practice.Methods The data of vortioxetine adverse events from September 2013 to August 2022 were retrieved from OpenFDA database, and risk signals were mined using the Reporting Odds Ratio (ROR) and Proportional Reporting Ratio (PRR) methods of the Ratio Imbalance Method. Statistical classification and analysis of the mined signals were performed using the preferred system organ class (SOC) of the Medical Dictionary for Regulatory Activities (MedDRA).Results Totally 16 569 reports of vortioxetine related adverse events were retrieved, with a predominantly adult population and a higher proportion of female patients (62.2%). The top 3 reporting countries were USA, France and Canada. The reporting population was mainly consumers or nonhealth professionals, accounting for 47.8%. The main indication was depression. The proportion of serious adverse events was 45.1%. Fifty suspicious signals were screened according to the positive criteria, involving a total of 10 SOC classifications, with psychiatric disorders having the highest number of signals (20), followed by systemic disorders and various reactions at the site of administration (9). Twenty-five of the 50 suspicious signals were consistent with the instructions. Among the 50 suspicious signals, the top 3 signals in terms of intensity were feeling guilty (ROR=171.616, PRR=169.288), decreased appetite (ROR=92.452, PRR=91.141) and apathy (ROR=38.309, PRR=37.404).Conclusion Based on the OpenFDA database, the adverse event data of vortioxetine can help to identify the potential risk signals of vortioxetine in the real world, suggesting that clinics should pay attention to these potential risk signals not mentioned in the instructions, in addition to those included in the instructions, and take timely interventions to ensure the drug safety of patients.

Meta-analysis is a common statistical technique used to combine findings, results, and data of several independent studies. The selection of the appropriate statistical model is critically important in the process of traditional meta-analysis, but in practice some researchers usually choose the models by mistake. In this paper we introduce some new views of the statistical models, and show some cases that were incorrect or correct selection of models in some published articles of domestic and foreign journals, and we also provide some recommendations and evidence for rational use of the model.

Objective To take 57 tertiary general hospitals in Shandong Province as study samples, to evaluate the medical quality and operation efficiency, and to provide references for strengthening connotation construction and improving the refined management level.Methods Entropy weighted technique for order preference by similarity to ideal solution (TOPSIS) and data envelopment analysis (DEA) were respectively used to evaluate the medical quality and operation efficiency in sample hospitals, by constructing the evaluation index system.Results In terms of medical quality, there was significant difference in highlevel surgical proportion and CMI among sample hospitals, with the maximum weight of both. The top ranked hospitals were A1, A2, A3, A4 and A29, all of which were tertiary and mostly provincial hospitals. In terms of operation efficiency, the overall efficiency of 57 sample hospitals was relatively high, but imbalance development still existed, with 22 hospitals DEA effectiveness, 12 hospitals DEA weakly effectiveness, and 23 hospitals DEA ineffectiveness. There was a positive correlation between medical quality and  technical efficiency.Conclusion There is a big space for improvement of the medical quality and operation efficiency in some sample hospitals. They should focus on functional orientation, continuously enhance medical technology level and internal management capability, optimize resources allocation, and transform from scale expansion to quality and efficiency improvement, in order to promote the high-quality development of hospitals. 

Objective To explore the association of cognition impairment with education status and mortality among the Chinese elderly and to provide recommendations for cognitive management of the Chinese elderly.Methods The study population was from the elderly aged 65 and above in the Chinese longitudinal healthy longevity survey (CLHLS) in 2005 and 2008. The traditional Cox proportional hazard model and additive Cox proportional hazard model were used to estimate the associations of cognitive impairment with education status and all-cause mortality. Data analysis included univariable analysis, stratified analysis and interaction analysis. The additive Cox proportional hazard model results were presented in the form of images.Results Among 15 860 eligible participants included in the study, 11 044 died during follow-up. The results showed that cognitive impairment would increase the mortality risk of the elderly (HR=1.32, 95%CI:1.26-1.39). And after stratified by education status, the hazardous effects diminished as education status decreased (years of schooling >6 years HR=1.47, 95%CI: 1.08-2.00; years of schooling 1-6 years HR=1.44, 95%CI: 1.26-1.63; years of schooling 0 year  HR=1.32, 95%CI:1.25-1.39). In addition, the association of education status and mortality was inconsistent across cognitively diverse populations. The protective effect of education status on mortality was observed among the people with normal cognitive function (HR=0.83, 95%CI: 0.77-0.91) but not observed among the people with cognitive impairment (HR=1.09, 95%CI: 0.81-1.47).Conclusion It is suggested that the community health centers should manage the cognitive function of the elderly according to their education status.

Objective To analyze the research hotspots and development trends of the teaching model of Medical Statistics.Methods NoteExpress software was used to modify and integrate the 569 valid literatures related to the teaching model of Medical Statistics into a form that could be recognized by CiteSpace software, and then CiteSpace 6.1.R2 software was used for visual analysis, including the growth trend of related literatures, high-yield institutions, core authors, high-frequency keywords, keyword clustering, emerging words, etc.Results The number of publications related to the teaching model of Medical Statistics showed an overall upward trend. There was almost no academic cooperation among institutions in this research field. The top three authors published 26, 23 and 12 papers respectively. A total of 378 nodes and 912 connections were identified in the network map, and the network density was 0.013, and the top 3 keywords were "teaching reform" with 129 times, "teaching methods" with 53 times, and "teaching" with 50 times. The keywords were clustered into 11 classes, of which the module value was 0.623 and the average outline value was 0.858. A total of 19 emergent words were identified, among which the top 3 keywords for emergent intensity were "teaching methods", "flipped classroom" and "medical statistics".Conclusion At present, scholars′ research on the teaching model of Medical Statistics is in a period of stable development. There is little academic cooperation among institutions in this field, but there is close cooperation between prolific scholars. Research hot topics include teaching reform, teaching methods, teaching, teaching effects, and teaching modes. Medical schools are the main research trend of the teaching reform model of Medical Statistics.

Objective To find out the dynamic change rule of surgical operation volume in a hospital from 2011 to 2020 through statistical analysis, so as to provide information reference for hospital management and medical resource allocation.Methods The moving average seasonal index method was used to dynamically analyze the surgical volume data from 2011 to 2020 and establish a prediction model.Results Except for the decline in 2020 due to the COVID-19 epidemic, the number of surgical operations in other years has increased to varying degrees, with a cumulative increase of 227.27% and an average growth rate of 8.56% per year in 10 years. In the second and third quarters of a year, the number of operations was more, and the seasonal index was more than 100%. The number of operations in the first and fourth quarters was small, and the seasonal index was lower than 1.Conclusion The number of surgical operations in the hospital has obvious regularity with seasonal changes. Hospital managers should reasonably allocate medical resources according to the change and development rules of surgical operations to ensure medical safety and service efficiency.

Objective To analyze and evaluate the hospital bed efficiency in 11 cities of Zhejiang Province.Methods Four indexes, including the number of hospital bed turnover, the working days of hospital bed, the utilization rate of hospital beds and the average hospitalization days, were collected from 11 cities of Zhejiang Province and evaluated comprehensively with TOPSIS method. Results The average number of hospital bed turnover was 28.6 times, the working days of beds was 281.3 days, the utilization rate of bed was 76.9%, and the average hospitalization days was 9.7 days in 2020. The top 3 cities with the highest bed utilization efficiency were: Taizhou, Jinhua and Huzhou, with evaluation scores of 0.871, 0.835 and 0.803, respectively. The bottom 3 cities were: Zhoushan, Lishui and Wenzhou, with evaluation scores of 0.000, 0.295 and 0.387, respectively.Conclusion In order to realize the reasonable allocation of bed resources and to improve the hospital bed efficiency, it is suggested to give full play to the overall coordination role of the government in the allocation of bed resources, optimize the dynamic allocation mechanism of beds within hospitals, strengthen the linkage between hospitals and grass-roots medical institutions, and improve the level of medical technology and management.

Objective To analyze the relevant factors affecting the efficacy of patients with sudden sensorineural hearing loss accompanied by hypertension, and to provide reference basis for the prevention and treatment of sudden sensorineural hearing loss.Methods Clinical data of patients with sudden sensorineural hearing loss and hypertension admitted to a certain hospital in Jiaxing from 2019 to 2022 were collected to analyze the relationship between variables and treatment efficacy of patients with the logistic regression model.Results The majority of 165 cases with sudden deafness accompanied by hypertension were female, with the majority engaged in manual labor occupations. The highest incidence of the condition occurred in summer. The results of the univariate analysis indicate that the efficacy of treatment for patients is correlated with age, accompanying tinnitus, classification of sudden deafness, platelet count, and treatment method (P<0.05). The multivariate logistic regression model analysis shows that older age (OR=1.073, 95%CI: 1.023-1.125), high serum potassium (OR=9.693, 95%CI: 5.829-15.633), high thyroidstimulating hormone (OR=5.023, 95% CI: 1.833-13.764) are independent risk factors for ineffective treatment, while high platelet count (OR=0.872, 95%CI: 0.652-0.978) and comprehensive treatment with hyperbaric oxygen (OR=0.137, 95%CI: 0.056-0.339) are protective factors for effective treatment.Conclusion Sudden sensorineural hearing loss accompanied by hypertension has a higher rate of adverse prognosis, and various factors collectively influence the treatment outcome of patients with sudden sensorineural hearing loss accompanied by hypertension.

The quality evaluation of clinical research literature is an important aspect of metaanalysis. In this article, we provide a review of research methodological quality (risk of bias) evaluation tools, introduce commonly used evaluation tools for randomized controlled trials and nonrandomized intervention studies, and summarize common misuse cases through case analyses. This provides a reference for the rational selection of literature quality evaluation tools.

Objective To explore the latent profiles of mindfulness levels among chronic HBV infected patients, and to analyze the population characteristics and influencing factors of different profiles.Methods From April 2020 to January 2021, chronic HBV infected patients from an infectious disease hospital in Shandong Province were selected by successive sampling method and investigated using a general information questionnaire, the Mindful Attention Awareness Scale and the Social Support Rating Scale. The latent profiles were analyzed using the Mindful Attention Awareness Scale score as an exogenous indicator, and the influencing factors of different profiles of mindfulness were explored by univariate analysis and binary logistic regression.Results Positive thinking level of chronic HBV-infected patients could be categorized into low positive thinking level group (39.68%) and medium-high positive thinking level group (60.32%). Univariate analysis of variance showed that gender, self-assessment of health status, satisfaction with support, severity of discrimination, and social support (objective support, subjective support, and utilization of support) were predictive of the 2 potential categories of positivity level in chronically HBV-infected patients with statistically significant differences (P<0.05). Binary logistic regression showed that gender (OR=0.499, P=0.017), self-assessment of health status (OR=1.789, P=0.001), severity of discrimination (OR=0.718, P=0.025), and subjective support (OR=1.066, P=0.016) would have an effect on the latent profiles of the level of positive thinking among people with chronic HBV infection.Conclusion Heterogeneity exists in the level of mindfulness among chronic HBV infected patients, and healthcare workers can identify population characteristics and influencing factors of different profiles by categorizing chronic HBV infected patients to provide more precise intervention programs to improve their mindfulness level.

Objective To investigate the ICD-9-CM-3 coding in cerebrovascular interventional operation.Methods The characteristics of common cerebrovascular interventional surgery were sorted out, and ICD-9-CM-3  coding was performed according to the international classification principle of surgery and operation and typical case analysis.Results For ischemic cerebrovascular disease, extracranial percutaneous balloon dilatation is classified in 00.61, and extracranial percutaneous stent placement is classified in 00.63 or 00.64; Intracranial percutaneous balloon dilatation is classified in 00.61, and intracranial percutaneous stent placement is classified in 00.65; Percutaneous thrombectomy is classified in 39.74; Percutaneous cerebrovascular hemolysis is classified as 99.10 or 99.20 according to different thrombolytic agents. Interventional embolization for hemorrhagic cerebrovascular disease is classified as 39.72, 39.75 or 39.76 according to different interventional material.Conclusion The surgical site, operation, disease nature and interventional material should be considered for the correct classification of cerebrovascular intervention operation. Incomprehension of the connotation of the operations and dependence too much on computers easily lead to miscoding.

Objective To explore the difference between ICD-10 and ICD-11 disease coding query and composition, and to provide a better understanding and reference for the current ICD-10 correct coding.Methods Taking primary nasal meningioma as the research object, ICD-10 and ICD-11 coding were compared and analyzed in detail from the aspects of chapter structure, coding composition, site coding, morphological coding and other extended coding.Results The ICD-10 disease code of primary nasal meningioma was found, the codes found in Volume 1 were classified as brain neoplasm, which needed to be revised before they could be used. ICD-11 uses a combination of cluster coding to represent complex neoplasm coding in detail. The morphological classification of ICD-11 is more in line with the actual clinical classification. The ICD-11 extended code can reflect the severity, lateral position and neoplasm stage.Conclusion ICD-11 is conducive to more accurate statistics of medical information, which should be applied as soon as possible.

Objective To introduce the method of simple random sampling and stratified sampling of medical records with Stata, in order to carry out the quality control of medical records.Methods Taking the statistical analysis software Stata as an example, the process of importing, viewing, random sampling, and exporting medical record data was shown, and the Stata command of random sampling required in the management of medical record quality control was provided.Results Compared with random number table method, lottery and subjective sampling, Stata sampling is more convenient, scientific and efficient. Compared with SAS and R language, Stata commands are more concise and easier for beginners to master. Conclusion Stata sampling is practical and efficient in the quality control of medical records, and it is worth learning and mastering by the relevant personnel of medical records.

Objective To analyze the meaning of surgical indicators of performance appraisal workers in tertiary public hospitals, use database query statements to achieve indicator statistics, and provide reference for colleagues engaged in hospital statistics.Methods The operation indexes of the first page of some medical records were explained and analyzed. The index statistics were completed in SQL. The difference was analyzed between the statistical results of this paper and the results of the performance evaluation platform.Results The results of the two statistical methods showed a small difference in the infection rate of Class I incisions, possibly due to factors such as data cleaning and parameter correction on national platforms.Conclusion Hospital statisticians can apply the statistical methods and SQL language in this paper to practical work. SQL language is a necessary artifact for big data query statistics in the new era, which is worth learning and promoting.

Objective To explore the standard cost subdivision scheme and complication index measurement (CCI) of DIP subgroup "spinal stenosis: lumbar interbody fusion, posterior approach", and to provide reference for the improvement of DIP payment scheme and policy formulation by the medical insurance department.Methods The home page data of 1 610 cases of spinal stenosis in a large tertiary hospital in Guangzhou from 2020 to 2022 were selected to screen the main complications of this group. The cost data were further fitted with decision tree model, DIP subgroups of different complications were established, and the complication index of each group was measured. Results The main complications in the spinal stenosis group were hypertension, type 2 diabetes, hyperuricemia and urinary system infection, which occurred in 20.31%, 10.37%, 5.16% and 4.35% cases, respectively. Quantile regression analysis showed that there were statistical differences in total hospitalization costs between the two groups with or without hypertension, type 2 diabetes, urinary tract infection or pneumonia (P<0.05). Four DIP subgroups with spinal stenosis were formed based on the decision tree model. The complication index of the subgroup with hypertension and urinary system infection was 1.04, that of the subgroup with type 2 diabetes was 1.08, and that of the subgroup with other complications was 0.98.Conclusion The complications of spinal stenosis are widely dispersed. The standard cost and complication index of spinal stenosis subdivision program are calculated by using decision tree model, which improves the accuracy of DIP payment and can provide reference for DIP to make subdivision program and improve the standard score database.

Objective To analyze the data of day surgery in an eye hospital, and to summarize the advantages of day surgery.Methods The medical records of 35 025 patients with day surgery in an eye hospital from July 2018 to December 2021 were retrospectively reviewed, including disease type, proportion in all surgery, average hospitalization days, hospitalization cost, and surgery cancellation rate.Results The disease types of day surgery increased year by year, and the top 5 diseases were lens disease, retinopathy, glaucoma, conjunctivopathy, and strabismus. The proportion of day surgery also increased year by year, reaching 81.62% by 2021. Day surgery shortened the average hospital stay by 1.26 days, and the average total cost reduced by 1 416.58 yuan. The surgery cancellation rate decreased year by year, and the average temporary cancellation rate was 1.09%.Conclusion Ophthalmic day surgery makes full use of medical resources to speed up the turnover of beds, has the advantages of short hospitalization time, safety, and low cost, which meet the needs of patients and their families. It is easy to write medical records in daytime, which improves the working efficiency of doctors. With the gradual improvement of medical technology, the number of diseases and operations carried out in day surgery will be increased, so as to promote the improvement of medical quality and service ability of the hospital.

Objective The complexity of the concept of multivariate statistics can easily lead to difficulties in students′ understanding. This article uses simulation experiments to examine the impact of various characteristics of data on the analysis results, in order to strengthen students′ understanding of the principles of multivariate statistics and facilitate their correct application of multivariate statistical methods.Methods Six simulation experiments were designed, and R 4.2.2 was used to generate simulation data and conduct statistical analysis to explore the impact of data characteristics on the 6 statistical analysis methods.Results According to the statistical analysis results of simulation experiments, the multicollinearity among independent variables in multilinear regression will make the regression coefficient estimation of the regression equation inaccurate. The correlation structure between variables in principal component and factor analysis affects the dimensionality reduction effect. In logistic regression, the nonlinear influence of independent variables on dependent variables should be considered, otherwise the results will affect the accuracy of the estimation results. When the proportion of deletion in Cox regression is too large, especially after reaching 60%, the results of the Cox regression model have a significant deviation. The correlation structure between variables affects the results of canonical correlation analysis. When there is a large difference in the proportion of categories, Bayesian discrimination and logistic regression are more appropriate for discrimination, because Bayesian discrimination with prior probability is more flexible.Conclusion The application of multivariate statistical methods needs to fully consider applicable conditions such as data characteristics. Through simulation experiments, students are encouraged to independently run simulation experiments, intuitively understand abstract multivariate concepts, and facilitate the understanding and application of multivariate statistical methods.

In recent years, China has put forward a series of policies on controlling medical consumables. In order to improve the level of detailed management of consumables, medical institutions have carried out a series of studies based on the datadriven evaluation index system of refined management of consumables. This study systematically reviews the policy requirements of consumable control in China since 2009, and studies the evaluation index system of consumables from the perspectives of consumable access and consumable use, and discusses some problems that exist objectively and need to be avoided in the construction of index system. We hope to provide ideas of refinement control of consumables in medical institutions.

Objective To comprehensively evaluate the effect of the inpatient performance distribution scheme based on DIP in a hospital, so as to find the existing defects in the current performance distribution scheme and explore the rationality and feasibility of the performance distribution scheme based on DIP.Methods Thirteen data from 10 surgical departments in a tertiary general hospital in Qingyuan City in 2021 were selected as comprehensive evaluation indexes. Delphi expert consultation method was used to determine the weights of evaluation indexes, and the efficacy coefficient method was used to calculate the total efficacy coefficient and rank it.Results Except for obstetrics with simple disease types, the results of comprehensive evaluation of other surgical departments were consistent or basically consistent with the actual allocation results.Conclusion The current performance allocation scheme based on DIP can relatively reasonably reflect the service quality and medical value of the departments. It is of practical guiding significance to comprehensively evaluate the results of performance distribution of the hospital with the efficiency coefficient method.

Objective To study the disease diagnosis related groups and hospitalization expense standard of cataract patients, and to provide reference for medical institutions to formulate hospitalization expense groups and improve the system.Methods The data of the first page of medical records of cataract patients from January 1 to December 31, 2021 were selected from a tertiary specialized hospital in Shanghai. The influencing factors of hospitalization expenses were analyzed by single factor analysis and multiple linear regression, and the classification node variables were screened out. The decision tree model was used to construct the grouping scheme and cost standard of cataract hospitalization costs.Results Totally 6 321 cataract inpatients were included in this study. The results of single factor analysis showed that the hospitalization expenses of patients with different age, hospitalization days, hospitalization times, surgical condition, and treatment or main surgical methods were statistically significant (P<0.05). The results of multiple linear regression analysis showed that age, hospitalization days, hospitalization times, and treatment or main surgical methods were the main factors affecting hospitalization expenses (F=385.47，P＜0.01，R2=0.328). The decision tree model formed a total of 6 groups and corresponding cost standards (risk value of the model was 0.03, CV of each group was 0.03-0.13, RIV=0.32).Conclusion It is reasonable to group the hospitalization expenses of cataract cases through the decision tree model. It is recommended that medical institutions refine the cost control of cataract diseases based on case grouping, further reasonably control medical operating costs, and adjust and optimize disease diagnosis related grouping by the medical insurance management department.

Objective To investigate the characteristics of patients with malignant tumors of digestive system and analyze the influencing factors of hospitalization expenses.Methods Medical record first page data of patients with digestive system cancer from 2017 to 2021 were collected to analyze the characteristics of tumor patients and the hospitalization costs with gray correlation method and structural variation degree.Results The top four malignant tumors of 4 505 cases of digestive system were colorectal cancer, gastric cancer, liver cancer, and gallbladder and cholangiocarcinoma. The number of cases increased with age and there were more men than women. From 2017 to 2021, the average hospitalization cost of patients with digestive system cancer showed an increasing trend. The top two influencing factors of hospitalization expenses of gastrointestinal cancer patients were consumables and western medicine. The contribution rate of the structural change of western medicine and consumables cost was 60.80%.Conclusion Early screening of digestive system tumors in the elderly is recommended. The costs of Western medicine and consumables were the main influencing factors of hospitalization expenses. It is suggested to reasonably adjust and optimize the structure of hospitalization expenses, implement the refined and digital management of drugs and consumables, and further improve the return on knowledge value of medical technicians.

Objective To study the medical records of patients with malignant tumors in a tertiary hospital, to grasp the composition and change trend of the main malignant tumor diseases, and to provide scientific reference for the prevention and treatment of malignant tumors in the local area.Methods Data of the first page of medical records of malignant tumor patients in a hospital from 2017 to 2021 were collected and retrospectively analyzed in terms of disease composition, sequence structure, age and gender distribution of patients with malignant tumors in the hospital.Results Totally 19 198 patients with malignant tumor were admitted, and the gender ratio was 1.3∶1. The proportion of hospitalized patients aged 50-69 was the highest (50.66%), and the mortality rate of malignant tumor was 4.96%. The top 5 malignant tumors were lung cancer, liver cancer, nasopharynx cancer, breast cancer, and colon cancer. The average medical cost of malignant tumor patients was 23 711.55 yuan, the average medicine cost was 4 851.93 yuan and the average hospitalization days were 13.03 days.Conclusion It should be aimed at highrisk groups and common types of malignant tumors. It is necessary to formulate comprehensive prevention and treatment measures for local population with malignant tumors over 50 years old, carry out cancer screening for early diagnosis and treatment, and strengthen control over medical expenses.

Objective To understand the level of nutrition and health knowledge of adult residents in Wuning County, Jiangxi Province under the background of healthy China, analyze the existing shortcomings of nutrition and health knowledge, and discuss the relevant influencing factors of residents′ nutrition and health knowledge awareness, so as to provide a scientific basis for the formulation of nutrition intervention policies.Methods A total of 895 local residents aged 18-64 years old in Wuning County, Jiangxi Province were selected to carry out a questionnaire survey on nutrition and health knowledge, the awareness rate was calculated, the acquisition channels of nutrition knowledge were analyzed and compared, and the main factors affecting the awareness rate of nutrition and health knowledge were analyzed by variance analysis and multivariate logistic regression method.Results The average age of 895 respondents was 39.49±12.08 years old, and males accounted for 51.62%. The awareness rate of high-oil and high-salt food was the highest (85.59%), followed by the best calcium supplement food (55.75%), and the daily salt intake of healthy adults (41.68%). The average score of nutrition knowledge was 11.01±2.38 points. The most extensive way for respondents to obtain nutrition knowledge was WeChat /Weibo /Tiktok /Kuaishou, accounting for 91.28% of the total number of respondents. There were statistically significant differences in the average scores and awareness rates of different age groups (F=30.80, P<0.001), different education level groups (F=22.26, P<0.001), different occupational groups (F=20.06, P<0.001), and different health status groups (F=5.34, P=0.005). Logistics regression analysis showed that education level and occupation type were the influencing factors of nutrition knowledge score (P<0.05).ConclusionThe awareness rate of nutrition and health knowledge among adult residents in Wuning County, Jiangxi Province is related to age, occupation, education level and health status, and it is necessary to focus on the weak links and take corresponding measures according to the characteristics of different groups of people, and strengthen the dissemination of health and nutrition knowledge through multiple channels.

Objective To investigate the current status of burnout among nurses in pediatric wards and analyze its contributing factors.Methods Pediatric ward nurses from 10 tertiary hospitals in Shandong Province were selected in groups using the convenience sampling method, and their questionnaires were surveyed using the General Data Questionnaire and the Maslach Burnout Scale.Results The total score of burnout among 335 nurses in the pediatric wards was (76.60±20.08), of which 220 (65.7%) nurses had burnout, 99 (29.6%) had mild burnout, 84 (25.1%) had moderate burnout, and 37 (11.0%) had high burnout. The results of optimal scale regression analysis showed that selfperceived health status, job satisfaction, establishment, job title, number of night shifts per week, leadership and family care, and pediatric working years were the main influencing factors of burnout among nurses in pediatric wards (P<0.05), among which selfperceived health status was the most important (0.212).Conclusion The situation of burnout of nurses in pediatric wards is grim, and it is recommended that managers adopt humanized management, such as caring for the physical and mental health of pediatric nurses, optimizing pediatric nursing human resources, improving performance appraisal and promotion mechanism, and improving job satisfaction, etc., to reduce burnout and stabilize the pediatric nursing team.

Objective To establish a time series model suitable for predicting the number of cases of brucellosis in China, and provide a scientific basis for preventing and controlling this disease.Methods This study utilized data on the number of cases from January 2015 to December 2021 to establish SARIMA and prophet models, respectively. Subsequently, the predictive performance of these two models was validated by using data from January 2022 to April 2023, and the results of the model predictions were compared by using three indicators: RMSE, MAPE, and MAE. Finally, the prophet model with higher accuracy was used to predict the number of cases from May 2023 to April 2024.Results The overall number of cases of brucellosis in China is rising, reaching its peak from June to July each year, showing a clear seasonal trend. Compared to the SARIMA model, the RMSE, MAPE, and MAE values of the prophet model are lower, indicating that the prophet model has higher accuracy in predicting brucellosis. The predicted peak of the number of cases in 2023 is lower than the actual peak in 2021 and 2022.Conclusion The prophet model can better fit the monthly reported number of cases of brucellosis in the country and can be used for short-term prediction.