The digital transformation of education requires new approaches in practice-oriented disciplines like management. To solve the lack of personalized and self-directed learning in existing courses, this conceptual and design-oriented study developed a digital textbook for virtual operations simulation. Guided by embodied learning theory and Kolb's experiential learning model (Kolb, 1984), the textbook adopts a four-stage approach: "Theoretical Preloading - Sandbox Simulation - Reflective Review - Competency Transfer." It integrates a custom virtual simulation and an AIpowered guidance system, such as knowledge bubbles and a virtual teaching assistant, to support "learning by doing, reflecting, and applying." This study explains the textbook's design, architecture, and implementation. It also conceptually discusses its potential role in moving management training from standardized knowledge-sharing to personalized competency development, and proposes future research directions to provide a reference for developing similar digital textbooks. It should be noted that the textbook has not yet been formally implemented in teaching, with empirical verification of its educational effectiveness reserved for future research.

BACKGROUND:The burden attributable to body mass index (BMI) remains a major public health concern in China and imposes substantial socio-economic costs. METHODS:Data from the Global Burden of Disease Study 2023 and economic projections were integrated to estimate and project the burden among Chinese adults aged 20-64 years. A multi-method approach was utilised, including burden estimation, joinpoint regression for trend analysis, demographic decomposition, age-period-cohort (APC) modelling, and Bayesian age-period-cohort (BAPC) modelling for future projections. This study introduced and applied the B-PALY framework, which integrates the BAPC model with productivity-adjusted life years (PALYs), to systematically predict the productivity impact and macroeconomic burden associated with high BMI-related diseases. RESULTS:In 2023, high BMI-related diseases caused 118 511 deaths and 9.7 million disability-adjusted life years (DALYs), accounting for approximately 20% of all deaths and 25% of all DALYs among China's working-age population. From 1990 to 2023, the burden showed significant upward trends. Demographic decomposition identified population aging and growth as primary drivers, partially offset by epidemiological changes. APC analysis revealed an increasing disease burden with age and elevated DALY risks in recent birth cohorts. Projections indicated a substantial rise in the burden of diseases attributable to high BMI, in terms of absolute deaths and DALYs, through 2050. The B-PALY framework estimated that, in 2023 alone, these diseases imposed a macroeconomic burden of approximately 129.77 billion Intl$ (about 0.03% of China's 2023 GDP). Projected cumulative losses from 2023 to 2029 amount to Intl $1.14 trillion. CONCLUSION:High BMI-related diseases caused a substantial health and macroeconomic burden in China's working-age population, with rising trends projected to continue.

Management of thyroid nodules with atypia of undetermined significance/follicular lesion of undetermined significance (AUS/FLUS) cytology is challenging because of uncertain malignancy risk. Intraoperative frozen section pathology provides real-time diagnosis for AUS/FLUS nodules undergoing surgery, but its accuracy is limited. This study aimed to develop an integrated predictive model combining clinical, ultrasound and IOFS features to improve intraoperative malignancy risk assessment. A retrospective cohort study was conducted on patients with AUS/FLUS cytology and negative BRAFV600E mutation who underwent thyroid surgery. The cohort was randomly divided into training and validation sets. Clinical, ultrasound, and pathological features were extracted for analysis. Three models were developed: an IOFS model with IOFS results as sole predictor, a clinical model integrating clinical and ultrasound features, and an integrated model combining all features. Model performance was evaluated using comprehensive metrics in both sets. The superior model was visualized as a nomogram. Among 531 included patients, the integrated model demonstrated superior diagnostic ability, predictive performance, calibration, and clinical utility compared to other models. It exhibited AUC values of 0.92 in the training set and 0.95 in the validation set. The nomogram provides a practical tool for estimating malignancy probability intraoperatively. This study developed an innovative integrated predictive model for intraoperative malignancy risk assessment of AUS/FLUS nodules. By combining clinical, ultrasound, and IOFS features, the model enhances IOFS diagnostic sensitivity, providing a reliable decision-support tool for optimizing surgical strategies.

AIMS:This study aims to analyze the burden, trends, and health inequality associated with early-onset type 2 diabetes mellitus (T2DM) caused by high Body-Mass Index (BMI) and to projected to 2050. METHODS:This study used data from the 2021 Global Burden of Disease. Analysis of the average annual percentage change (AAPC) was conducted using Joinpoint regression. Slope index and concentration index were used to assess health inequality. Bayesian age-period-cohort models predicted the burden from 2022 to 2050. RESULTS:In 2021, the ASMR and ASDR were 0.61 (95% UI: 0.35 to 0.79) and 153.88 (95% UI: 83.85 to 222.19) per 100,000, respectively. From 1990 to 2021, the AAPC of ASMR and ASDR were 1.06 (95% CI: 1.00 to 1.13) and 2.79 (95% CI: 2.75 to 2.82), respectively. High SDI countries had smaller burdens, and the inequality trend worsened. It is expected that the global burden will continue to rise in the future. CONCLUSION:The burden is constantly rising and is expected to continue increasing in the future. The burden shows differences based on age, gender, and SDI. Therefore, targeted interventions should be developed for specific populations.

China has entered an aging society, and the mental health of the aged has gradually attracted social attention. This study aimed to model the mediating effect of social activities on the relationship between incapacitation and depression in the aged and to explore the moderating effect of community support on the mediating role. This paper used the latest data from The Chinese Longitudinal Healthy Longevity Survey (CLHLS). A moderated mediation effect model was constructed with the degree of incapacity as the independent variable, depressive symptoms as the dependent variable, socialization as the mediator, and community support as the moderator. Socialization was a partial mediating variable in the relationship between incapacitation and depression in the aged, and its mediating effect accounted for 13.29

To assess whether the comprehensive reforms in 2017 (Reform 1) and 2019 (Reform 2) in Beijing have achieved the anticipated targets by analyzing the changes in curative care expenditure (CCE) and related indicators before and after the reforms. Due to the Covid-19 pandemic, data are not comparable for the period after 2019, we obtained records of patients from the Hospital Information System (HIS) between January 1, 2016 and December 31, 2019. The multistage stratified cluster random sampling was used to obtain sample data, and the System of Health Accounts 2011 was applied to account for the CCE of all hospitals in Beijing. We used an interrupted time series analysis (ITSA) to compare the changes in levels and trends before and after the reforms. Overall, the reforms failed to impact the rising trend in CCE, but successfully lowered the level of drug and consumable prices in all hospitals and optimized the hospital revenue structure. The reforms’ impact on patient burden was also mixed. For Reform 1, outpatient costs rose in tertiary hospitals, fell for inpatients in tertiary and secondary hospitals, and exhibited no change in all other hospitals. In terms of the trend, Reform 1 saw a fall in patient burden except for a rise inpatients in tertiary and primary hospitals. For Reform 2, the level of total expenditures per outpatient visit fell in primary hospitals, rose per inpatient bed day in secondary hospitals and had no change in all other hospitals. The impact of reforms on Beijing’s hierarchical medical system (HMS) was not significant. The reform outcomes were only partially in line with the reforms’ aims. While echoing the call for more resources for primary hospitals, only major patient medical service pricing changes would shift patients away from tertiary and secondary hospitals towards primary hospitals. We suggest that several measures be taken to enhance the service capacity of primary hospitals and that an advertising campaign be launched to inform and encourage patients to use primary hospitals as gatekeepers.

BackgroundBreast conserving surgery (BCS) is a standard treatment for breast cancer. Intraoperative frozen section analysis (FSA) is widely used for margin assessment in BCS. In addition, FSA-assisted excisional biopsy is still commonly practiced in many developing countries. The aim of this study is to develop a predictive model applicable to BCS with FSA-assisted excisional biopsy and margin assessment, with a focus on predicting the risk of secondary margin positivity in re-excision procedures following positive initial margins. This may reduce surgical complications and healthcare costs associated with multiple re-excisions and FSAs for recurrent positive margins.MethodsPatients were selected, divided into training and testing sets, and their data were collected. The Least Absolute Shrinkage and Selection Operator (LASSO) was used to identify significant variables from the training set for model building. Model performance was evaluated using Receiver Operating Characteristic (ROC) curves, calibration curves, and Decision Curve Analyses (DCAs). An optimal threshold identified by the Youden index was validated using sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).ResultsThe study included 348 patients (256 in the training set, 92 in the testing set). No significant statistical differences were found between the sets. LASSO identified six variables to construct the model and corresponding nomogram. The model showed good discrimination (mean area under the curve (AUC) values of 0.79 in the training set and 0.83 in the testing set), calibration (Hosmer-Lemeshow test results (p-values 0.214 in the training set, 0.167 in testing set)) and clinical utility. The optimal threshold was set at 97 points in the nomogram, yielding a sensitivity of 0.66 (0.54-0.77), specificity of 0.80 (0.74-0.85), PPV of 0.56 (0.47-0.64) and NPV of 0.86 (0.82-0. 90) for the training set, and a sensitivity of 0.65 (0.46-0.84), specificity of 0.88 (0.79-0.95), PPV of 0.68 (0.53-0.85) and NPV of 0.87 (0.81-0.93) for the testing set, demonstrating the model’s effectiveness in both sets.ConclusionsThis study successfully developed a novel predictive model for secondary margin positivity applicable to BCS with FSA-assisted excisional biopsy and margin assessment. It demonstrates good discriminative ability, calibration, and clinical utility.

The effectiveness of mammography in women with dense breasts is compromised by a high rate of false-negative results. While supplemental ultrasound increases sensitivity, its low positive predictive value (PPV) leads to more unnecessary biopsies. This study aims to develop a nomogram model to predict the malignancy of breast masses that are additionally identified as suspicious by supplemental ultrasound after an initial negative screening mammography. The goal is to improve the PPV of supplemental ultrasound and potentially reduce unnecessary biopsies. In this study, eligible data were collected retrospectively and then randomized into training and validation sets. The Least Absolute Shrinkage and Selection Operator was used to identify the most important predictive variables in the training set. The maximum Youden index determined the optimal model threshold, and model performance was evaluated using receiver operating characteristic curves, calibration curves, decision curve analyses, and metrics such as sensitivity, specificity, PPV, and negative predictive value. The study included 425 breast masses, 345 benign and 80 malignant. These were divided into 298 for the training set and 127 for the validation set. Least Absolute Shrinkage and Selection Operator identified the 5 most important predictive variables for the construction of the model. The model showed strong discrimination with area under the curve values of 0.91 (0.87-0.95) for the training set and 0.88 (0.81-0.96) for the validation set. Hosmer-Lemeshow tests indicated a good model fit, with P-values of 0.78 and 0.12 for the training and validation sets, respectively. In addition, decision curve analyses highlighted the clinical utility of the model. The model also showed commendable diagnostic performance in terms of sensitivity, specificity, PPV, and negative predictive value. The nomogram model significantly increased the PPV of supplemental ultrasound from 0.18 to 0.56 in the training set and from 0.21 to 0.56 in the validation set. This study successfully developed a nomogram model to predict the malignancy of suspicious breast masses additionally identified by supplemental ultrasound. The model shows robust performance and significantly improves the PPV of supplemental ultrasound, suggesting a promising way to reduce unnecessary biopsies in such cases.

目的:以脑梗死住院患者为例,对中医类医院中医优势病种的病例组合方案进行探索,为未来中医优势病种更好地参与按病种付费提供数据参考.方法:提取2019年北京市若干家中医类医院9055例脑梗死住院患者病案首页数据.通过多元线性回归确定分节点变量,纳入决策树模型进行病例组合并测算分组后的标准费用、病种权重等.结果:以性别、年龄、住院天数、耗材费、医院类型和医院级别等关键因素作为住院费用分节点变量纳入决策树模型,形成19个病例组合,总体分组较为合理.结论:采取措施控制影响脑梗死患者住院费用的关键因素,重点关注超标费用,制定标准费用、费用上限、超标费用、病种权重,积极探讨中医优势病种病例组合方案,为其参与按病种付费提供数据参考.

目的:旨在探讨影响中医优势病种中药参与率及费用的相关因素,以期为更好发挥中医药优势提供参考.方法:数据选取自2019年1 月1 日—12月31 日北京市55家医院优势病种住院患者的信息.采用倾向性得分匹配法对提取的住院患者基本数据进行混杂消除,并运用χ2检验、logistic回归及贝叶斯网络模型统计方法分析中药参与率差异、影响因素以及影响程度.结果:共收集219 375例优势病种住院患者数据,其中有效例数193 810例.男性占比(54.10%)优于女性,41～80岁占比(61.27%)最高,患者以城镇职工基本医疗保险支付为主(45.22%),三级医院相较二级医院占比更高,住院0～7天患者占比(43.17%)最高;与不参与时相比,优势病种患者在有中成药参与时费用更高,有中药饮片参与时二级医院费用更低,三级医院更高;医院级别、类别、居住地、年龄、支付方式及住院日在4种中药参与率情况相比,差异具有统计学意义(P＜0.05);其中,医院类别、年龄和住院日是中药参与率的共同影响因素(P＜0.05).结论:优势病种中成药参与率及价格均高于饮片,两者占比不均衡,建议健全中医定价和补偿激励机制,并积极探索中医药特色诊疗技术,以提高中药使用率,并发挥其在中医优势病种治疗中的优势作用.

目的:通过研究北京市不同来源老年人口治疗费用受益人群现状,为提高首都老年人口卫生政策的精准性和科学性提供数据支持.方法:采用卫生费用核算体系2011,通过多阶段分层整群抽样调查,选择52家医院、29家社区为样本,核算北京市地域范围内医疗机构老年患者治疗费用情况.结果:2019年北京市医疗机构老年患者的治疗费用为982.32亿元,占比为39.78%,其中本地居民消耗为81.19%.本地患者以利用门诊服务为主,外来就医患者则主要利用三级医院的住院服务.来北京市就医的老年患者以低龄老年患者为主,60～70岁的患者治疗费用占比在60%以上.老年患者以慢性非传染性疾病为主,疾病分布相对集中,不同来源患者疾病分布呈现明显差异.结论:老年患者对医疗资源需求高,以慢性非传染性疾病为主,不同来源老年患者治疗费用在年龄别、疾病别、机构流向等方面的构成差异明显,卫生政策制定应该精准考虑不同来源老年患者的需求.

目的 建立可推广的公立医院财政分类精准补偿新机制,进而提高公立医院财政补偿的合理性、科学性.方法 假定拨款给公立医院的总财政资金一定,通过医院的规模、运营特点、盈亏情况、绩效考核计算医院财政拨款系数.综合规模值通过主成分降维得到,运营系数通过熵权TOPSIS综合评价得到,盈亏系数和绩效系数通过比例系数法得到.结果 运营系数大于 1 的医院类别有5类,分别为精神病医院(1.62)、老年医院(1.35)、传染病医院(1.15)、结核病医院(1.08)、妇产医院(1.03);盈亏系数大于 1 的医院类别有4类,分别为传染病医院(1.21)、妇产医院(1.03)、结核病医院(1.13)、精神病医院(1.02).结论 综合多方面因素,以系数化方法提出财政补偿新方案,符合高质量发展的政策需求.建议形成专门的财政补偿相关指标体系和财政补偿评估制度,实现科学、合理的财政精准补偿和动态调整机制.

目的:旨在比较中医优势病种在中医类医院和综合医院治疗的次均住院总费用的差异,探讨不同类型医疗机构住院治疗中医优势病种的费用特点.方法:数据选自北京市58家医院中出院时间在2016-01-01—2019-12-31 的优势病种住院患者信息,采用倾向性得分匹配法对提取的住院患者基本数据进行混杂消除.结果:共收集605 688例优势病种住院患者数据,结果发现中医优势病种整体上在综合医院的次均住院总费用高于中医类医院,中医优势病种在中医类医院的费用结构体现了中医诊疗的特点.结论:未来要积极推动中医优势病种按病种付费,充分考虑各病种特点,将费用结构调整重点放在医疗行为的调整和中医药优势的发挥上.

公立医院的公益性属性使其在控制医疗服务价格的同时还需保障医院的正常运营,因此,政府需要以多种形式对公立医院提供补偿.从我国公立医院补偿机制的现状出发,重点梳理了财政补偿、医疗保险基金、医疗服务价格之间的关系,并对比国外公立医院补偿机制,在总结我国公立医院补偿机制现存问题的基础上,对各项补偿之间的联动提出思考与建议.

This paper sorts out and analyzes the relevant policies of medical insurance payment in the field of traditional Chinese medicine issued by the national and regional health administrative departments, as well as the typical practices in various regions reported in newspapers, so as to provide a reference for deepening the reform of medical insurance payment methods in the field of traditional Chinese medicine. Retrieve documents on “reform of traditional Chinese medicine medical insurance payment”issued by various health administrative departments and news on “medical insurance payment of traditional Chinese medicine”and“payment of traditional Chinese medicine by disease type”published on the government website through the government website before January 15, 2022, and extract the key information from it. A total of 30provinces and cities have collected policy documents on traditional Chinese medicine medical insurance payment reform and typical practices in some regions. At present, the payment methods for traditional Chinese medicine diseases mainly include payment by disease, payment by diagnosis related groups, payment by diagnosis-intervention packet, and payment by curative effect value. There are differences in payment methods for different types of traditional Chinese medicine diseases. There are also some problems with different payment methods. It is recommended to strengthen research on price adjustment of traditional Chinese medicine, improve the disease database and surgical operation coding system with traditional Chinese medicine characteristics, and improve the positive incentive mechanism for medical institutions to provide traditional Chinese medicine services and medical insurance payments.

目的 对北京市16个区2020年卫生资源配置情况进行分析,为优化卫生资源配置提供参考建议.方法 通过对2020年1月至12月北京市16个区(东城区、西城区、朝阳区、丰台区、石景山区、海淀区、门头沟区、房山区、通州区、顺义区、昌平区、大兴区、怀柔区、平谷区、密云区和延庆区)卫生资源配置产生重要影响的9项主要指标进行主成分分析、因子分析和聚类分析,比较各区的卫生资源配置现状及差异.结果 2项主成分对医疗卫生机构资源配置具有较大影响.通过因子分析得到的卫生资源因子和机构配置因子,与主成分分析的结果一致.通过聚类进一步将16个区分为4种类型,即核心区、经济区、发展区和远郊区.结论 16个区需合理规划卫生资源配置,加强卫生人力资源投入及医联体建设,更好地改善资源配置和医疗质量,以促进北京市整体卫生资源质量的提高.

目的:通过比较分析北京市中医优势病种本地居民和外来就医患者治疗费用的分布情况,为优化协调区域内与区域间的卫生资源配置、发现重点人群提供参考.方法:运用分层整群抽样方法,获得205家不同类别医疗机构,以卫生费用核算体系2011 为基础,核算2019年北京市医疗机构不同来源中医优势病种患者的治疗费用情况.结果:2019年北京市中医优势病种治疗费用占全市整体疾病治疗费用的13.74%,以本地居民治疗费用为主,本地居民与外来就医患者治疗费用的诊疗范式、机构、性别、年龄分布存在差异.结论:中医优势病种治疗费用规模较大,主要流向三级医院,中医治疗病种、优质住院服务对外来就医患者更具吸引力,建议优化医疗资源布局,在制定政策前充分考虑不同人群的就医需求.

目的 在医疗服务项目成本数据的基础上,探讨公立医院政策性亏损补偿方案,提高补偿的科学性和精准性.方法 通过CRITIC权重和秩和比综合评价法对医疗服务项目展开综合评价,建立差异化补偿方案.结果 基于2017-2019年A市39家医院206 864个医疗服务项目的成本数据,分类后可见不同类别的医疗服务项目盈亏特点各异,护理类亏损项目占92.47%,而实验室诊断项目每服务量项均盈利4.56元.根据保本点、盈亏情况、成本价格偏离度、成本结构相关6项指标,各类项目政策性亏损补偿比例由高到低可划分为A、B1、B2、C 4个档次,据此展开分类补偿.结论 此补偿方案是对医疗服务项目成本的深化应用和政策性亏损精准补偿的有益探索,后续政策可根据补偿档次确定补偿比例,也可结合医院不同级别、类型亏损及自身管理差异继续完善.另外,建议整合医疗、医保、医药多方力量,实现财政补偿与价格政策协同联动,共同促进公立医院高质量发展.

目的 探讨结直肠癌患者住院费用构成及影响因素,为控制其医疗费用提供参考依据.方法 应用描述性分析研究北京市2019年1月1日-2019年12月31日7335例结直肠癌患者的基本情况、住院费用构成,应用单因素分析、多元线性回归和BP神经网络模型研究住院费用影响因素.结果 结直肠癌患者人均住院费用32062.62元,手术治疗患者住院费用以耗材费为主(59.51％),非手术治疗患者住院费用以药品费为主占76.42％.住院费用影响因素包括住院天数、医院类型、是否手术、支付方式、医院级别和年龄,住院天数是结直肠癌患者住院费用的首要影响因素(多元线性回归标准化系数为0.437,BP神经网络自变量重要性为0.532),其次为医院类型(多元线性回归标准化系数为0.342,BP神经网络自变量重要性为0.168),是否手术和支付方式的影响程度高于年龄和医院级别.BP神经网络模型的MAE、MSE和RMSE值分别为0.260、0.132和0.363,均小于多元线性回归模型(0.305、0.183和0.428).结论 住院天数是影响结直肠癌患者住院费用的重要因素,通过缩短住院天数可有效减轻患者经济负担.多元线性回归和BP神经网络模型均可用于分析结直肠癌患者住院费用的影响因素,但BP神经网络模型的性能和预测效果更好.