Cost analysis of radical resection of malignant breast tumors under the China Healthcare Security Diagnosis Related Groups payment system

BACKGROUND Breast cancer is one of the most common malignant tumors in women worldwide and poses a severe threat to their health.Therefore,this study examined patients who underwent breast cancer surgery,analyzed hospitalization costs and structure,and explored the impact of China Healthcare Security Diagnosis Related Groups(CHS-DRG)management on patient costs.It aimed to provide medical institutions with ways to reduce costs,optimize cost structures,reduce patient burden,and improve service efficiency.AIM To study the CHS-DRG payment system’s impact on breast cancer surgery costs.METHODS Using the CHS-DRG(version 1.1)grouping criteria,4073 patients,who underwent the radical resection of breast malignant tumors from January to December 2023,were included in the JA29 group;1028 patients were part of the CHS-DRG payment system,unlike the rest.Through an independent sample t-test,the length of hospital stay as well as total hospitalization,medicine and consumables,medical,nursing,medical technology,and management expenses were compared.Pearson’s correlation coefficient was used to test the cost correlation.RESULTS In terms of hospitalization expenses,patients in the CHS-DRG payment group had lower medical,nursing,and management expenses than those in the diagnosis-related group(DRG)non-payment group.For patients in the DRG payment group,the factors affecting the total hospitalization cost,in descending order of relevance,were medicine and consumable costs,consumable costs,medicine costs,medical costs,medical technology costs,management costs,nursing costs,and length of hospital stay.For patients in the DRG nonpayment group,the factors affecting the total hospitalization expenses in descending order of relevance were medicines and consumable expenses,consumable expenses,medical technology expenses,the cost of medicines,medical expenses,nursing expenses,length of hospital stay,and management expenses.CONCLUSION The CHS-DRG system can help control and reduce unnecessary medical expenses by controlling medicine costs,medical consumable costs,and the length of hospital stay while ensuring medical safety.

Insulation fault diagnosis based on group grey relational grade analysis method for power transformers

Utilising dissolved gases analysis, a new insulation fault diagnosis methodfor power transformers is proposed. This method is based on the group grey relational grade analysismethod. First, according to the fault type and grey reference sequence structure, some typicalfault samples are divided into several sets of grey reference sequences. These sets are structuredas one grey reference sequence group. Secondly, according to a new calculation method of the greyrelational coefficient, the individual relational coefficient and grade are computed. Then accordingto the given calculation method for the group grey relation grade, the group grey relational gradeis computed and the group grey relational grade matrix is structured. Finally, according to therelational sequence, the insulation fault is identified for power transformers. The results of alarge quantity of instant analyses show that the proposed method has higher diagnosis accuracy andreliability than the three-ratio method and the traditional grey relational method. It has goodclassified diagnosis ability and reliability.

CLINICAL VALUE OF SERUM TUMOR SUPPLIED GROUP OF FACTOR IN DIAGNOSIS OF EPITHELIAL OVARIAN CANCER

Objective: To evaluate the clinical value of serum tumor supplied group of factor (TSGF) in diagnosis of epithelial ovarian cancer. Methods: The serum TSGF was tested in 69 patients with epithelial ovarian cancer, 28 patients with benign ovarian lesion and 61 healthy women. The serum levels of vascular endothelial growth factor (VEGF) and CA125 were determined in patients with epithelial ovarian cancer and in those with benign ovarian lesion. The correlations of TSGF with VEGF and CA125 were investigated. Results: The serum level of TSGF in patients with epithelial ovarian cancer was obviously higher than in patients with benign ovarian lesion and in healthy women (P<0.01). The serum level of TSGF in patients with epithelial cancer was associated with stage and grade. TSGF was highest in stage III, followed by stage IV, and was lowest in stage I-II. The TSGF level was lower in well-differentiated tumors and was higher in poorly differentiated tumor. There were no significant difference among diagnostic value of TSGF, VEGF, and CA125 in differentiation between epithelial ovarian cancer and benign ovarian lesion (P>0.05). The serum level of TSGF and VEGF and CA125 in patients with epithelial ovarian cancer showed positive correlation (P<0.01, P<0.05, respectively). Conclusion: There is no marked difference in diagnostic value among TSGF, VEGF and CA125. TSGF has a certain value in diagnosis of epithelial ovarian cancer, and is helpful to distinguish epithelial ovarian cancer from benign ovarian lesion.

Diagnosis related group grouping study of senile cataract patients based on E-CHAID algorithm

AIM： To figure out the contributed factors of the hospitalization expenses of senile cataract patients（HECP） and build up an area-specified senile cataract diagnosis related group（DRG） of Shanghai thereby formulating the reference range of HECP and providing scientific basis for the fair use and supervision of the health care insurance fund.METHODS： The data was collected from the first page of the medical records of 22 097 hospitalized patients from tertiary hospitals in Shanghai from 2010 to 2012 whose major diagnosis were senile cataract. Firstly, we analyzed the influence factors of HECP using univariate and multivariate analysis. DRG grouping was conducted according to the exhaustive Chi-squared automatic interaction detector（E-CHAID） model, using HECP as target variable. Finally we evaluated the grouping results using non-parametric test such as Kruskal-Wallis H test, RIV, CV, etc.RESULTS： The 6 DRGs were established as well as criterion of HECP, using age, sex, type of surgery and whether complications/comorbidities occurred as the key variables of classification node of senile cataract cases.CONCLUSION： The grouping of senile cataract cases based on E-CHAID algorithm is reasonable. And the criterion of HECP based on DRG can provide a feasible way of management in the fair use and supervision of medical insurance fund.

Fault Diagnosis of Wind Turbine Generator with Stacked Noise Reduction Autoencoder Based on Group Normalization

In order to improve the condition monitoring and fault diagnosis of wind turbines,a stacked noise reduction autoencoding network based on group normalization is proposed in this paper.The network is based on SCADA data of wind turbine operation,firstly,the group normalization(GN)algorithm is added to solve the problems of stack noise reduction autoencoding network training and slow convergence speed,and the RMSProp algorithm is used to update the weight and the bias of the autoenccoder,which further optimizes the problem that the loss function swings too much during the update process.Finally,in the last layer of the network,the softmax activation function is used to classify the results,and the output of the network is transformed into a probability distribution.The selected wind turbine SCADA data was substituted into the pre-improved and improved stacked denoising autoencoding(SDA)networks for comparative training and verification.The results show that the stacked denoising autoencoding network based on group normalization is more accurate and effective for wind turbine condition monitoring and fault diagnosis,and also provides a reference for wind turbine fault identification.

Research on Key Techniques of Condition Monitoring and Fault Diagnosing Systems of Machine Groups

This paper describes the development of the condition monitoring and faultdiagnosing system of a group of rotating machinery. The data management is performed by means ofdouble redundant data bases stored simultaneously in both the analyzing server and monitoringclient. In this way, high reliability of the storage of data is guaranteed. Condensation of trenddata releases much space resource of the hard disk. Diagnosing strategies orientated to differenttypical faults of rotating machinery are developed and incorporated into the system. Experimentalverification shows that the system is suitable and effective for condition monitoring and faultdiagnosing for a rotating machine group.

Current Situation and Suggestions on the Development of Diagnosis Related Group(DRG)Policy in China

Objective To implement the national diagnosis related group(DRG)policy smoothly,and gradually move towards value medicine and fine management,some suggestions are put forward for improving medical service efficiency,saving medical insurance fund,and reducing the burden of patients,so as to realize the win-win situation of medical insurance and patients.Methods Based on the experience of the United States,Australia,and Germany,the policy implementation background and development process in China were summarized.The advantages and disadvantages of single disease payment method,disease score payment method,and diagnosis related groups-prospective payment system(DRG-PPS)method were compared,and then the problems were found out.Results and Conclusion In view of the imperfect information system,lack of professional talents,and uneven progress of each pilot,it is proposed that relevant departments should pay more attention to the construction and improvement of coding and other information systems,cultivate professional talents,promote the reform of DRG payment technology specification and grouping technology combined with national pilot project,thus enhancing the application and in-depth development of DRG policy in China.

Clinical Intelligent Diagnosis Path Based on the Chief Complaint

Goals of traditional Chinese medicine(TCM)include precision,accuracy,and recognition by clinical practice.Establishment of a diagnosis and treatment system that closely conforms to the principle-method-recipe-medicines system and derivation of an accurate diagnosis and treatment plan should be considerations of TCM.Artificial intelligence research based on computer technology is one of the effective ways to solve this problem.In the research of intelligent diagnosis path,reflecting the characteristics of the overall view and dialectical treatment of TCM such as"Combination of four diagnostic methods""overall examination""combination of disease and syndrome"and"treatment individualized to patient,season and locality"are key for successful research of artificial intelligence in TCM diagnosis or recognition by clinical practice.

Fuzzy Integral Theory and Its Application in Fault Intelligent Integrated Diagnosis

In this paper, by employing the idea of 'dispersion first, then concentration'' adhering to the biological perceptual system, an idea of the multi-symptom-domain based fault consensus diagnosis is developed. From the point of group decision-making, the method based on neural networks to realize this diagnosis idea is studied, and a particular multi-symptom-domain based diagnosis strategy is proposed, which is based on fuzzy integral theory. Finally, a case study is given. The research results show that the proposed diagnosis strategy is available and more efficient than conventional methods.

The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure

Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is also beneficial for three parametric data.By Pythagorean fuzzy sets,the difference is calculated only between two parameters(membership and non-membership).According to human thoughts,fuzzy data can be found in three parameters(membership uncertainty,and non-membership).So,to make a compromise decision,comparing Sq-LDFSs is essential.Existing measures of different fuzzy sets do,however,can have several flaws that can lead to counterintuitive results.For instance,they treat any increase or decrease in the membership degree as the same as the non-membership degree because the uncertainty does not change,even though each parameter has a different implication.In the Sq-LDFSs comparison,this research develops the differentialmeasure(DFM).Themain goal of the DFM is to cover the unfair arguments that come from treating different types of FSs opposing criteria equally.Due to their relative positions in the attribute space and the similarity of their membership and non-membership degrees,two Sq-LDFSs formthis preference connectionwhen the uncertainty remains same in both sets.According to the degree of superiority or inferiority,two Sq-LDFSs are shown as identical,equivalent,superior,or inferior over one another.The suggested DFM’s fundamental characteristics are provided.Based on the newly developed DFM,a unique approach tomultiple criterion group decision-making is offered.Our suggestedmethod verifies the novel way of calculating the expert weights for Sq-LDFSS as in PFSs.Our proposed technique in three parameters is applied to evaluate solid-state drives and choose the optimum photovoltaic cell in two applications by taking uncertainty parameter zero.The method’s applicability and validity shown by the findings are contrasted with those obtained using various other existing approaches.To assess its stability and usefulness,a sensitivity analysis is done.

Brain abscess caused by Streptococcus anginosus group:Three case reports

BACKGROUND This case series investigated the clinical manifestations,diagnoses,and treatment of cerebral abscesses caused by Streptococcus anginosus.We retrospectively analyzed the clinical characteristics and outcomes of three cases of cerebral abscesses caused by Streptococcus anginosus and conducted a comprehensive review of relevant literature.CASE SUMMARY Case 1 presented with a history of left otitis media and exhibited high fever,confusion,and vomiting as primary symptoms.Postoperative pus culture indicated a brain abscess caused by Streptococcus constellatus infection.Case 2 experienced dizziness for two days as the primary symptom.Postoperative pus culture suggested an intermediate streptococcal brain abscess.Case 3:Enhanced head magnetic resonance imaging(MRI)and diffusion-weighted imaging revealed occupancy of the left temporal lobe,initially suspected to be a metastatic tumor.However,a postoperative pus culture confirmed the presence of a brain abscess caused by Streptococcus anginosus infection.The three cases presented in this case series were all patients with community-acquired brain abscesses resulting from angina caused by Streptococcus group infection.All three patients demonstrated sensitivity to penicillin,ceftriaxone,vancomycin,linezolid,chloramphenicol,and levofloxacin.Successful treatment was achieved through stereotaxic puncture,drainage,and ceftriaxone administration with a six-week course of antibiotics.CONCLUSION Preoperative enhanced head MRI plays a critical role in distinguishing brain tumors from abscesses.Selecting the correct early diagnostic methods for brain abscesses and providing timely intervention are very important.This case series was in accordance with the CARE guidelines.

Medical Diagnosis Based on Multi-Attribute Group Decision-Making Using Extension Fuzzy Sets,Aggregation Operators and Basic Uncertainty Information Granule

Accurate medical diagnosis,which involves identifying diseases based on patient symptoms,is often hindered by uncertainties in data interpretation and retrieval.Advanced fuzzy set theories have emerged as effective tools to address these challenges.In this paper,new mathematical approaches for handling uncertainty in medical diagnosis are introduced using q-rung orthopair fuzzy sets(q-ROFS)and interval-valued q-rung orthopair fuzzy sets(IVq-ROFS).Three aggregation operators are proposed in our methodologies:the q-ROF weighted averaging(q-ROFWA),the q-ROF weighted geometric(q-ROFWG),and the q-ROF weighted neutrality averaging(qROFWNA),which enhance decision-making under uncertainty.These operators are paired with ranking methods such as the similarity measure,score function,and inverse score function to improve the accuracy of disease identification.Additionally,the impact of varying q-rung values is explored through a sensitivity analysis,extending the analysis beyond the typical maximum value of 3.The Basic Uncertain Information(BUI)method is employed to simulate expert opinions,and aggregation operators are used to combine these opinions in a group decisionmaking context.Our results provide a comprehensive comparison of methodologies,highlighting their strengths and limitations in diagnosing diseases based on uncertain patient data.

Analysis of a Group of Weak Small-Scale Vortexes in the Planetary Boundary Layer in the Mei-yu Front

A mei-yu front process in the lower reaches of the Yangtze River on 23 June 1999 was simulated by using the fifth-generation Pennsylvania State University-NCAR （PSU/NCAR） Mesoscale Model （MM5） with FDDA （Four Dimension Data Assimilation）. The analysis shows that seven weak small mesoscale vortexes of tens of kilometers, correspondent to surface low trough or mesoscale centers, in the planetary boundary layer （PBL） in the mei-yu front were heavily responsible for the heavy rainfall. Sometimes, several weak small-scale vortexes in the PBL could form a vortex group, some of which would weaken locally, and some would develop to be a meso-α-scale low vortex through combination. The initial dynamical triggering mechanism was related to two strong currents： one was the northeast flow in the PBL at the rear of the mei-yu front, the vortexes occurred exactly at the side of the northeast flow; and the other was the strong southwest low-level jet （LLJ） in front of the Mei-yu front, which moved to the upper of the vortexes. Consequently, there were notable horizontal and vertical wind shears to form positive vorticity in the center of the southwest LLJ. The development of mesoscale convergence in the PBL and divergence above, as well as the vertical positive vorticity column, were related to the small wind column above the nose-shaped velocity contours of the northeast flow embedding southwestward in the PBL, which intensified the horizontal wind shear and the positive vorticity column above the vortexes, baroclinicity and instability.

DRG支付背景下某公立医院专科建设思考及实施效果分析

近年来,随着医改的持续深化,按疾病诊断相关分组(DRG)支付逐渐成为新医改的焦点。DRG支付制度不仅是医保结付的方式,同时也是公立医院规范医生诊疗行为、衡量医疗服务质量的管理工具,促使医院由粗放管理转向精细管理转型,对公立医院的运营管理理念提出一系列挑战。因此,分析DRG支付方式改革给公立医院带来的影响以及相关运营情况意义重大。笔者选取某公立医院推进DRG支付方式改革以来的22 791例病案资料进行分析,探讨在DRG支付背景下医院运营的应对策略及主要问题,为公立医院更好地落实DRG支付政策及高质量发展转型提供建议。

基于合成控制法的DRG改革对住院费用的影响——以北京市三级公立医院为例

目的:分析DRG改革对北京市三级公立医院例均住院总费用及其增速、内部结构的短期效应与长期影响。方法:基于2009—2018年北京市三级公立医院住院费用的年度报表数据,采用合成控制法分析2011年的DRG改革对例均住院总费用及各项费用占比的影响。结果:与未试点的医院相比,短期内试点医院的例均住院总费用有所降低,药占比下降显著,耗材费用占比增速下降明显,手术、治疗、护理费用占比有所下降,检查、化验费用占比略有上升。长期看,试点医院例均住院总费用与增速超过非试点医院,药占比、手术、治疗、护理费用占比低于非试点医院,耗材费用占比大幅提高,检查、化验费用占比呈现较强的个体差异性。结论:DRG改革短期内对控制费用增长具有积极作用,长期效果有待改善,费用结构有待优化;未来应从发挥“双中心”的多元作用、与三级公立医院绩效考核结合、提高体现医生技术劳动价值的收入等方面完善DRG改革。

公立医院DRG绩效考核指标体系构建研究

目的:构建基于DRG支付制度的公立医院绩效考核指标体系,以期提高公立医院绩效评价的科学性,为公立医院深化DRG支付方式改革提供参考。方法:基于平衡计分卡的基础框架,通过文献研究法初步构建指标库;遴选21位相关领域专家进行两轮德尔菲法专家咨询确定指标体系,利用层次分析法确定指标权重。结果:构建了基于DRG的公立医院绩效考核指标体系,包括4个维度、7个一级指标和17个二级指标,专家积极系数、权威程度及两轮咨询协调程度较好。指标体系重视患者体验、医疗服务能力和质量安全,指标维度权重值为0.15~0.47,一级指标权重值为0.05~0.23,二级指标权重值为0.01~0.22。结论:初步形成基于DRG的公立医院绩效考核指标体系,指标体系科学可靠,可应用于公立医院DRG绩效考核评价工作,明确指标来源和获取途径,为指标体系的推广奠定基础。

安徽省某三甲医院DRG付费改革效果评价

[目的]评价安徽省某三甲医院DRG付费改革的实施效果。[方法]收集2020-2022年某三甲医院DRG病例资料,比较住院费用、住院天数、内外科病例构成、正常倍率组占比及各项住院费用指标在3个年度之间的差异。[结果]与2020年相比,该院2021年、2022年的总费用、材料费、检查费、药品费、住院天数的中位数明显下降,差异均有统计学意义(P<0.05);与2021年相比,2022年内科病例占比及正常倍率组占比提高,差异均有统计学意义(P<0.05)。[结论] DRG付费改革倒逼医疗机构控制医疗费用不合理增长,优化费用结构,提升医疗服务效率,有利于推进分级诊疗。

DRG支付方式下公立医院特殊病例住院费用影响因素分析

目的:分析DRG支付方式下,包括高倍率病例和低倍率病例在内的特殊病例费用特征及其影响因素,为降低医疗费用、减轻患者负担和完善DRG支付方式改革提供参考。方法:选取某三甲综合医院2022年全年所有特殊病例的病案首页数据,采用描述性分析和单因素分析对特殊病例的影响因素进行分析,并通过结构方程模型分析各影响因素间的作用路径和影响程度。结果:纳入高倍率病例1281例(占总病例2.78%),其中治疗费用花费最多(占16.29%),费用最少的是诊察费(占0.79%);低倍率病例3266例(占7.09%),其中手术费用花费最多(占31.51%),费用最少的是诊疗费(占1.61%)。性别、年龄、住院天数、科室类别、医保付费方式、并发症均是特殊病例住院费用的影响因素(P<0.05)。结构方程模型结果显示,科室类别对费用的影响最大,性别对费用的影响最小。结论:调整医疗费用结构,缩短患者的住院天数,合理使用DRG支付方式,从而降低医疗费用、提高诊疗效率,实现总体控费目标。

从药师角度分析某院肿瘤内科DRG病组亏损的影响因素及应对策略:以RE16病组为例

目的减少医院肿瘤内科疾病诊断相关分组(DRG)RE16病组的亏损。方法检索医院DRG分析系统出院结算日期为2022年3月15日至2023年4月30日的1179例次肿瘤内科患者的DRG数据,按DRG盈利与亏损分为盈利组(824例次)和亏损组(355例次),比较两组患者的性别、年龄、住院天数、药费、药占比、材料费、材料费占比、检查费、检查费占比、化验费、化验费占比、治疗费、治疗费占比,分析亏损的影响因素,并从药师角度分析可能对RE16病组亏损有显著影响的药品。结果亏损组和盈利组的住院天数、药费、材料费、材料费占比、检查费、检查费占比、化验费、化验费占比、治疗费、治疗费占比均有显著差异(P<0.05)。药费在RE16病组的占比最高(75.60%),其次为化验费(13.08%)和材料费(4.04%)。亏损组聚乙二醇化重组人粒细胞刺激因子(长效)、因卡膦酸二钠及其他辅助用药如肌苷注射液、参麦注射液、斑蝥维生素B6注射液、金复康口服液的使用率均显著高于盈利组(51.27%比27.66%,19.15%比5.83%,21.41%比7.16%,12.68%比4.85%,8.45%比2.91%,2.54%比1.33%,P<0.05)。结论药费对RE16病组亏损有影响,可通过开展重点药物专项点评和实行药品分级管理减少RE16病组的亏损。

基于决策树模型HC25病组DRGs细分组及住院费用的影响因素研究

目的构建基于决策树模型HC25病组患者DRGs细分组的研究及住院费用的影响因素。方法收集西安交通大学第一附属医院2020年1月至2022年6月依据CHS-DRG分组方案进入HC25(胆囊切除术,不伴并发症或合并症)病组患者的病案首页数据(n=3844),通过单因素和多因素分析了解影响住院费用的主要因素,通过建立决策树模型进行病例组合,分析分组效果及不同分组的费用标准。结果正态性检验结果显示:住院费用呈偏态分布(χ2=0.197,P<0.001);单因素方差分析结果显示:住院费用在不同年龄、性别、手术方式、患者来源、医疗付费方式、入院病情危重情况、术前时间、住院时间、是否有再住院计划之间,差异有统计学意义(P均<0.05);多重线性逐步回归分析结果显示,影响住院费用显著性差异的因素从大到小依次为:住院时间、手术方式、入院病情危重情况、性别、术前时间、患者来源、再住院计划(P均<0.05);采用CHAID共生成了7个DRGs分组,第一层分类节点变量是手术方式,第二层是术前时间、住院时间,第三层是入院时病情危重情况;不同DRGs组合的住院费用比较,差异有统计学意义(χ2=2474.595,P<0.001),组合DRGs(1)的住院费用最高,权重最高;DRGs(7)的住院费用最低,权重最小;所有DRGs病组中超标费用患者共170例(4.42%),各组超标费用比例均<10%。结论基于决策树模型对HC25病组的细分组效果合理有效,能较客观反映医疗资源消耗水平。