合理用药监测系统存在的问题及对策探讨

目的:分析合理用药监测系统(PASS 1.6.1.7)在处方审核中存在的问题并探讨对策。方法:采用回顾性方法,随机抽取我院2015年第一季度处方4 942张,对PASS审核结果与药师点评结果进行比较分析,并对软件审核出现的问题提出相应对策。结果与结论:PASS与药师审核的处方合格率分别为81.20%、97.40%;PASS将合理处方审为不合理处方的有929张(18.80%),主要涉及用法用量、西药与中成药开具在同一处方上、重复用药及慎用等情况;PASS将不合理处方审为合理处方的有122张(2.47%),主要涉及用法用量、诊断与用药不符等方面。发生原因主要是医院相关管理不完善及软件智能化程度不高等。建议医院加强对信息系统的数据维护管理及PASS开发方对软件规则进行相应改进等,以提高处方审核的准确率。     

个体生物等效性检验的样本含量估计

目的:对两种设计方法、三种检验方法的个体生物等效性的检验效能进行比较,并估计样本含量。方法:采用Monte-Carlo模拟研究。结果:2×4交叉设计所需的样本含量低于2×3设计。在个体内变异小于0.2时,可以采用估计法进行样本含量的估计;在个体内变异接近0.2时,可以采用检验法进行样本含量的估计;在个体内变异大于0.3时,可以选任一方法(估计法和检验法)估计样本含量,并选择合适的方法进行样本含量的估计。结论:个体生物等效性的样本含量因不同的个体内变异和个体与药物间的交互作用、设计而不同。     

均匀分布资料总体中位数可信区间估计Bootstrap法样本含量的设置

探讨了Bootstrap样本含量n*对Bootstrap法总体中位数可信区间估计效果的影响。首先模拟从均匀分布总体中随机抽样;然后用Bootstrap法进行总体中位数可信区间估计,重复1000次,得到1000个可信区间,统计1000个可信区间包含总体中位数的正确率。结果表明,Bootstrap样本含量n*对总体中位数可信区间估计的正确率影响很大,Bootstrap样本含量n*越小,正确率越高;Bootstrap样本含量n*越大,正确率越低;Bootstrap样本含量n*不能任意设置,当Bootstrap样本含量n*=n-3时,效果最好。     

应用临床合理用药监测软件对我院医嘱审查分析

目的:调研PASS对临床医嘱审查的作用。方法:统计分析医嘱中警示级别、类型及医嘱修改率,并判定PASS审查警告与临床用药的相符性。结果:共监测医嘱10982160条,其中黑色警示条数11146条,修改2861条,修改率25.67%;红色警示条数51504条,修改10357条,修改率20.00%;黄色警示条数339449条,修改66022条,修改率19.45%。在PASS系统监测过程中,出现可行性临床医嘱与PASS警告不相符的情况。结论:PASS软件审查医嘱方便、快捷,临床用药从自律性行为转变成规范化行为,提高了临床合理用药水平。但PASS软件功能还需不断更新和优化。     

单组临床试验目标值法的精确样本含量估计及统计推断

目的:针对结局为二分类变量以率作为终点评价指标的单组临床试验,探讨基于二项分布原理进行单组目标值法样本含量估计及统计推断的精确方法。方法:系统综合和全面论述了单组临床试验目标值法所涉及到的样本含量计算、可信区间估计和假设检验的精确方法。结果:按目标值起点为75%,间隔1%增加,给出预期事件发生率起点为76%,间隔1%增加,与目标值对应的精确样本含量结果,并列表给出β在0.20条件下,α分别取单侧和双侧0.05水平下的两套结果,可供直接查用。提供了可信区间估计及假设检验的精确计算公式。结论:为单组临床试验目标值法的样本含量计算、可信区间估计及假设检验提供了系统、实用的方法学支持。     

临床随访研究中样本含量的估计

目的:介绍临床随访研究中生存分析资料的log-rank检验所需样本含量的估计法.方法:以离散性Markov链拟合生存过程,据此计算log-rank统计量的数学期望和方差,导出样本含量估计公式.结果:实例分析表明,该法能较好反映实际情况,应用灵活.结论:本法是一种有效、可行的样本含量估计法,值得推荐.     

率的等效性检验方法的比较

目的 :对 10种率的等效性检验方法的Ⅰ型误差和检验效能进行比较 ,并据此选择较好的方法估计样本含量 ,以便实际工作者应用。方法 :采用MonteCarlo模拟试验。结果 :10种方法中 ,以Dun nett Gent方法为最佳 ,并按该方法估计了样本含量。模拟试验表明 ,率的等效性检验所需要的样本含量非常大 ,当试验组和参考组各只有 10 0例时 ,任何等效性检验方法的检验效能均较低。结论 :按目前国家食品药品监督管理局规定的最低样本含量 10 0对 ,相应的检验效能很低 ,建议用统计学方法进行估计。     

重复测量资料的广义估计方程分析及SPSS实现

目的:探讨医药研究中重复测量设计资料的统计分析方法。方法:结合医药科研中的实例阐述广义估计方程处理重复测量资料的原理和方法。结果:广义估计方程是处理重复测量资料的有效方法,该方法应用条件宽,可适用于多种类型的反应变量,如定量变量、二分类变量、等级变量等,同时允许资料中有缺失值,或出现个别观察单位重复测量次数不完全相同等情况,因而在重复测量设计资料统计分析中应用广泛。     

医学研究中不等距重复测量资料的分析及在SPSS16.0中的实现

目的:以一实例介绍用SPSS16.0实现对不等距重复测量资料的方差分析和结果解释。方法:用SPSS16.0中的一般线性模型和程序编辑窗口实现不等距重复测量设计的方差分析。结果:球形检验结果P<0.05,重复测量数据之间存在相关性,采用多元方差分析(P<0.05);个体内变异计算,表明时间因素有效应且时间与处理因素之间有交互效应(P<0.05);个体间变异计算表明分组因素有效应(P<0.05)。结论:处理不等距重复测量资料时要慎重,利用SPSS软件易于实现对此类资料的方差分析。     

动脉导管未闭介入治疗中直径目测法的应用

目的:探讨动脉导管未闭(patent ductus arterisus,PDA)介入治疗中应用目测法测量PDA直径方法的可行性.方法:对21例接受PDA封堵术的患者,主动脉弓降部造影时引入已知直径的参照物,根据目测法测量PDA直径选择封堵器型号,同时用目测法测量PDA直径与软件测量值进行比较.结果:目测法测量PDA直径与软件测量值比较差异无统计学意义(P＞0.05),21例PDA患者根据目测法选择封堵器,其中20例一次性封堵成功,1例需更换更大型号封堵器成功.结论:PDA介入治疗中引入已知直径参照物目测法测量PDA直径迅速、简便,方法操作可行.     

Effect of dropouts on sample size estimates for test on trends across repeated measurements

Sample size calculation is an important component at the design stage of clinical trials. We investigate the implications of dropouts for the sample size estimates in testing differences in the rates of changes produced by two treatments in a randomized parallel-groups repeated measurement design. Statistical models for calculating sample sizes for repeated measurement designs often fail to take into account the impact of dropouts correctly. In this article, we examine the impact of dropouts on sample size estimate and compare the power with the approach of Jung and Ahn [Jung, S. H., Ahn, C. (2003). Sample size estimation for GEE method for comparing slopes in repeated measurements data. Stat. Med. 22: 1305-1315] with that suggested by Patel and Rowe [Patel, H., Rowe, E. (1999). Sample size for comparing linear growth curves. J. Biopharm. Stat. 9:339-350] through a simulation study.     

PASS系统在我院临床医嘱审查中的应用

目的:探讨临床合理用药监测软件系统(PASS)在医院临床医嘱审查中的应用。方法:统计分析我院2005年4月~2006年4月经PASS系统审查的医嘱警示级别、类型及医嘱修改率,并判定PASS系统审查警告与临床用药的相符性。结果:共监测医嘱10982160条,其中黑色警示11146条,修改2861条(25.67%);红色警示51504条,修改10357条(20.0%);黄色警示339449条,修改66022条(19.45%),在PASS系统监测过程中,出现了可行性临床医嘱与PASS系统警示不相符的情况。结论:PASS系统审查医嘱方便、快捷,提高了临床合理用药水平,但PASS系统功能还需不断更新和优化。     

Sample Size Determinations for the Wilcoxon–Mann–Whitney Test: A Comprehensive Review

The Wilcoxon–Mann–Whitney (WMW) test is the most commonly used nonparametric method to compare two treatments when the underlying distribution of the outcome variable is not normally distributed. The sample size calculation methods for the WMW test have been extensively discussed in the literature. In this article we give a comprehensive review of sample size calculation methods for the WMW test on data with or without ties. We also provide detailed implementation of these sample size calculation methods for the WMW test depending on the characteristics of the data and the amount of available information. In addition, the implementation of these methods in popular sample size calculation software packages is also discussed. This article will be very helpful for researchers to determine sample sizes for the WMW test in the design phase of a study.     

Sample Size Calculations for Population Pharmacodynamic Experiments Involving Repeated Dichotomous Observations

Analysis of repeated binary measurements presents a challenge in terms of the correlation between measurements within an individual and a mixed-effects modelling approach has been used for the analysis of such data. Sample size calculation is an important part of clinical trial design and it is often based on the method of analysis. We present a method for calculating the sample size for repeated binary pharmacodynamic measurements based on analysis by mixed-effects modelling and using a logit transformation. Wald test is used for hypothesis testing. The method can be used to calculate the sample size required for detecting parameter differences between subpopulations. Extensions to account for unequal allocation of subjects across groups and unbalanced sampling designs between and within groups were also derived. The proposed method has been assessed via simulation of a linear model and estimation using NONMEM. The results showed good agreement between nominal power and power estimated from the NONMEM simulations. The results also showed that sample size increases with increased variability at a rate that depends on the difference in parameter estimates between groups, and designs that involve sampling based on an optimal design can help to reduce cost.     

Sample size calculations for population pharmacodynamic experiments involving repeated dichotomous observations

Analysis of repeated binary measurements presents a challenge in terms of the correlation between measurements within an individual and a mixed-effects modelling approach has been used for the analysis of such data. Sample size calculation is an important part of clinical trial design and it is often based on the method of analysis. We present a method for calculating the sample size for repeated binary pharmacodynamic measurements based on analysis by mixed-effects modelling and using a logit transformation. Wald test is used for hypothesis testing. The method can be used to calculate the sample size required for detecting parameter differences between subpopulations. Extensions to account for unequal allocation of subjects across groups and unbalanced sampling designs between and within groups were also derived. The proposed method has been assessed via simulation of a linear model and estimation using NONMEM. The results showed good agreement between nominal power and power estimated from the NONMEM simulations. The results also showed that sample size increases with increased variability at a rate that depends on the difference in parameter estimates between groups, and designs that involve sampling based on an optimal design can help to reduce cost.     

基于HIS并结合PASS的电子药历软件的研制

目的：开发基于HIS并结合PASS的电子药历。方法：在Win2003／XP平台，用PowerBuilder软件，按照SOAP的模式设计电子药历格式。结果：成功开发各项功能符合要求的电子药历软件，通过自动或半自动的方式收集HIS系统内药历所需基本数据等情况，配合PASS审查结果，并记录药师参与临床治疗分析，形成完整药历。结论：电子药历软件方便药师工作，记载信息全面、准确、标准化，是药师工作的得力工具。     

临床试验Williams设计中样本含量的估算方法

在临床试验中,2组交叉设计应用已相当广泛,其样本含量估算方法也被研究者所熟悉。多组交叉试验由Williams首先提出,因此被称为Wil-liams设计。本文介绍基于Williams设计的样本含量估算方法,并提供示例分析,供研究者参考使用。     

PASS系统对我院临床合理用药情况的监测与分析

目的:探讨临床合理用药监测系统(PASS)对我院合理用药的监测情况。方法:利用PASS系统对我院2006年8月7日～11月6日的44万多条用药医嘱进行监测,并通过Excel进行分类统计总结。结果:其中黑灯628次,修改494次;红灯16134次,修改7740次;橙灯122926次,修改57867次。本次调查中有数种药物反复出现不合理应用现象,如维生素C、苯巴比妥、阿托品等。结论:PASS系统运行以来,不合理用药的现象大幅度减少,但部分软件问题还需进一步完善。     

Power and sample size for the S:T repeated measures design combined with a linear mixed-effects model allowing for missing data

Tango (Biostatistics 2016) proposed a new repeated measures design called the S:T repeated measures design, combined with generalized linear mixed-effects models and sample size calculations for a test of the average treatment effect that depend not only on the number of subjects but on the number of repeated measures before and after randomization per subject used for analysis. The main advantages of the proposed design combined with the generalized linear mixed-effects models are (1) it can easily handle missing data by applying the likelihood-based ignorable analyses under the missing at random assumption and (2) it may lead to a reduction in sample size compared with the simple pre-post design. In this article, we present formulas for calculating power and sample sizes for a test of the average treatment effect allowing for missing data within the framework of the S:T repeated measures design with a continuous response variable combined with a linear mixed-effects model. Examples are provided to illustrate the use of these formulas.