基于门诊多类型就诊卡模式的数字化医院建设探讨

提出并实现了基于“三卡通”(医保卡、就诊卡、银行借记卡)支付的医院门诊就医新模式,从而进一步改善门诊就医环境,便捷就医流程,缓解群众“就医难”的问题,提升医院的财务管理水平和医疗服务质量,推进数字化医院建设。     

湖北省医院门诊药事服务项目界定及服务成本测算研究

????? 界定门诊药事服务的项目,测算门诊药事服务成本,推进医院门诊药事服务的开展。通过文献法获得与药事服务的概念及门诊药事服务项目有关的内容,通过专家咨询法和现场调查法,获取开展门诊药事服务的成本资料,运用标准成本测算方法测算湖北省医院门诊基本药事服务成本。 界定了药事服务的概念及门诊药事服务项目,测得湖北省三甲医院门诊药事服务成本为30.02元,二甲医院的门诊药事服务成本为10.44元。建议各级医院按此类标准进行探索性补偿。

     

肿瘤专科医院志愿者服务的实践与探索

????? 为改善医疗环境和提高医疗服务质量,满足患者多层次的医院服务需求,建立医院志愿者服务体系,开展志愿服务已成为医务社会工作的一条创新之路。志愿者作为促进现代医学技术与社会人文精神紧密结合的良好媒介与助推器,切实将“全心全意为患者服务”的宗旨落实到实处,为医院发展提供有力支持。

     

医学院校附属医院护理人员科研能力影响因素分析

目的 分析筛选医学院校附属医院护理人员科研现状及影响因素,为提高护理人员的科研能力提供依据。方法 选取38位资深专家采用德尔菲法确定科研能力评价指标。采用随机抽样的方法对某医学院校4所附属医院200名护理人员进行问卷调查,采用多因素Logistic回归法分析护理人员科研能力影响因素。结果 分析表明,学历、团队情况、科研经费、科研管理规范性4个因素对护理人员的科研绩效影响作用显著。结论 为进一步提高医学院校附属医院护理人员的科研能力,应该加强护理人员学历教育、培养护理科研团队、增加护理科研经费的投入以及加强护理科研管理的规范性。

     

上海市某区社区卫生服务中心门诊用药合理性评价

利用6个合理用药国际指标以及TOPSIS法,综合分析和评价了2009年上海市某区12所社区卫生服务中心门诊用药状况。12种社区卫生服务中心门诊处方分析显示：平均药费为77.11元/张,平均药物数为2.30种,抗菌药物费用比例为12.02%,针剂费用比例为12.95%,抗菌药物处方比例为26.27%,国家基本药物使用比例为56.45%。根据C _i值分析,社区卫生服务中心的门诊用药基本合理,部分医疗机构门诊用药合理性有待提高。     

医院床位利用效率评价比较及影响因素分析

通过对国内外床位利用效率评价方法、评价结果的现状分析,总结归纳床位利用效率的影响因素,发现影响床位利用效率的因素主要有国家相关政策、医院自身管理和医护人员行为、病人病种结构及其他不可控因素,国内对床位利用效率的评价研究存在方法单一、影响因素分析不够透彻以及政策建议缺乏针对性和可操作性等几个方面的问题。      

我国医院床位配置与利用现状及对策分析

医院医疗资源的配置与利用是完善卫生服务体系、提高现有的医疗资源利用效率的关键因素,通过我国医院床位配置与利用现状分析,对其中存在的问题及原因进行剖析,并提出相应的对策建议,对合理分配有限的医疗资源并有效利用具有重要意义。     

2015-2017年某综合医院医院感染现患率调查分析

摘要 目的：了解与掌握医院感染现状及抗菌药物的使用,为有效预防与控制医院感染提供科学依据。方法：采用横断面调查方法,对医院2015年9月12日、2016年9月7日、2017年8月23日住院患者医院感染横断面调查,并对调查的所有资料进行分析。结果：应调查4160例,实查4125例,实查率99.16%,实查率符合现患率调查要求。2015-2017年医院感染现患率分别为6.12%、4.58%、4.12%,三年调查现患率比较,差异有统计学意义（x²=6.537,P=0.038）。调查科室中综合ICU医院感染现患率最高,为30.30%,例次感染率为36.36%。2015-2017年医院感染部位均以下呼吸道最高,其次为泌尿道,血管相关最低。2015-2017年现患率调查统计病原菌共172株,以革兰阴性菌为主。2015-2017年调查抗菌药物使用率分别为27.54%、24.09%、23.32%,合计为24.99%,三年调查日的使用率比较,差异有统计学意义（x²=7.452,P=0.024）。病原学送检673例,送检率79.83%。结论：医院感染现患率调查有助于掌握医院感染现状,根据调查存在的问题,采取相应干预措施,可有效预防与控制医院感染。     

医院设备利用率管理的探究

分析了医院医疗设备利用率管理的现状,提出了医疗设备利用率管理的前期工作与实施方法。建立设备的性能价值评定标准以及加强设备的维护保养工作都是提高设备利用率的有效途径。     

Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis

Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies.     

基于医院核心财务的医院资源规划业务管理分析

以核心财务系统为落脚点,依次展开医院资源规划系统对应的业务设计,为医院资源规划系统的实施提供有力的参考方案。基于核心财务系统,医院资源规划业务主要包括预算业务、科研教学业务、费用管理业务、固定资产及物资业务、药品材料试剂业务。业务数据与核心财务系统实现对接,数据最终汇集至核心财务系统完成成本核算和绩效考核,形成完整的以“财务一体化”为主线的运营管理平台。     

Multivariate Analysis of Genetic Variation

Multiple factor analysis was used to interpret geographical variation of gene frequencies. Allelic frequencies at three loci (two esterase loci, Esr and Esh, and a malic dehydrogenase locus) from ants (Pogonomyrmex barbatus) collected throughout Texas and reported by Johnsonet al. (1969) were reexamined for patterns of correlation with five environmental measurements: mean January temperature, mean July temperature, mean annual precipitation, elevation, and annual growing season. These measurements and the associated gene frequencies at each sampling location were subjected to factor analysis. Variables highly correlated with the same factor were hypothesized to be causally related.Both orthogonal and oblique rotations of the factor solution provided four factors with essentially the same interpretation. Variation at the Esh locus was associated with a continuum from cold-wet to hot-dry. Variation at the Mdh locus and some of that at the Esr locus was related to the severity of winter months. Other allelic frequencies at the Esr locus had high correlations with a third factor which seemed to be independent of the environmental measurements. None of the allelic frequencies had high correlations with the fourth factor which was interpretable as an altitudinal gradient.     

Basics of Multivariate Analysis in Neuroimaging Data

Multivariate analysis techniques for neuroimaging data have recently received increasing attention as they have many attractive features that cannot be easily realized by the more commonly used univariate, voxel-wise, techniques^1,5,6,7,8,9. Multivariate approaches evaluate correlation/covariance of activation across brain regions, rather than proceeding on a voxel-by-voxel basis. Thus, their results can be more easily interpreted as a signature of neural networks. Univariate approaches, on the other hand, cannot directly address interregional correlation in the brain. Multivariate approaches can also result in greater statistical power when compared with univariate techniques, which are forced to employ very stringent corrections for voxel-wise multiple comparisons. Further, multivariate techniques also lend themselves much better to prospective application of results from the analysis of one dataset to entirely new datasets. Multivariate techniques are thus well placed to provide information about mean differences and correlations with behavior, similarly to univariate approaches, with potentially greater statistical power and better reproducibility checks. In contrast to these advantages is the high barrier of entry to the use of multivariate approaches, preventing more widespread application in the community. To the neuroscientist becoming familiar with multivariate analysis techniques, an initial survey of the field might present a bewildering variety of approaches that, although algorithmically similar, are presented with different emphases, typically by people with mathematics backgrounds. We believe that multivariate analysis techniques have sufficient potential to warrant better dissemination. Researchers should be able to employ them in an informed and accessible manner. The current article is an attempt at a didactic introduction of multivariate techniques for the novice. A conceptual introduction is followed with a very simple application to a diagnostic data set from the Alzheimer s Disease Neuroimaging Initiative (ADNI), clearly demonstrating the superior performance of the multivariate approach.