第六讲 临床诊治中的Markov模型

1Markov模型进行决策分析的步骤Markov模型是模拟随时间发生的随机事件的过程。利用Markov模型进行决策分析的步骤如下:[1](1)根据研究目的和疾病的自然病程设立Markov状态,确定各状态间可能存在的相互转换;(2)确定循环周期和每个周期中各状态间的转换概率;(3)确定各状态的效用     

第六讲临床诊治中的Markov模型

Markov模型进行决策分析的步骤 Markov模型是模拟随时间发生的随机事件的过程.利用Markov模型进行决策分析的步骤如下:[1]     

第一讲 临床决策分析概述

为了使大家对临床决策有更加深入的理解,本刊编辑部特约请上海交通大学上海市第六人民医院曹建文副教授就临床决策的相关问题撰写了系列讲座,讲座的内容为：第一讲：临床决策分析概述;第二讲：如何构建不确定条件下的临床决策;第三讲：临床决策分析中如何应用决策树;第四讲：临床决策分析中的效用分析;第五讲：灵敏度分析在临床决策中的应用;第六讲：临床诊治中的Markov模型;第七讲：成本一效果分析在临床决策中的作用;第八讲：决策分析在药物经济学中的应用。我们希望读者看过这些讲座后,踊跃提出问题,发表意见,以促进医疗决策的深入研究。     

第一讲 临床决策分析概述

为了使大家对临床决策有更加深入的理解,本刊编辑部特约请上海交通大学上海市第六人民医院曹建文副教授就临床决策的相关问题撰写了系列讲座,讲座的内容为:第一讲:临床决策分析概述;第二讲:如何构建不确定条件下的临床决策;第三讲:临床决策分析中如何应用决策树;第四讲:临床决策分析中的效用分析;第五讲:灵敏度分析在临床决策中的应用;第六讲:临床诊治中的Markov模型;第七讲:成本-效果分析在临床决策中的作用;第八讲:决策分析在药物经济学中的应用。我们希望读者看过这些讲座后,踊跃提出问题,发表意见,以促进医疗决策的深入研究。     

数据仓库在针灸临床循证决策分析中的应用研究

数据仓库为海量数据存储和高层决策分析提供了一种综合解决方案.在介绍数据仓库概念基础上,分析了针灸临床循证决策研究采用数据仓库技术的必要性,并通过针灸数据仓库的数据需求分析,数据仓库的模型设计和功能设计,初步构建了应用于针灸临床循证决策分析的针灸数据仓库.     

第一讲临床决策分析概述

决策分析在临床实践中的应用形成了临床决策分析.在国外,临床决策分析已经有数十年的发展历史,而且被广泛应用于临床科研和实践中.近年来随着循证医学的发展,临床决策分析逐渐被引入到我国医院的临床实践中,通过决策分析方法,分析和评价临床诊断、治疗的各种方案的效果,为临床医生进行合理诊疗提供依据.为了普及和推广临床决策分析的基本概念和方法,我们将通过讲座的形式给读者介绍临床决策分析的有关内容,并通过临床案例分析加深有关临床决策分析方法的讲解,目的是使读者能够掌握其基本内容和方法,以便在今后的临床实践中能够正确使用该方法.     

第八讲决策分析在药物经济学中的应用

在药物经济学的评价中,同样也可以采用我们前面介绍的决策树分析的方法,灵敏度分析的方法,成本-效果分析的方法等等,这些都是在进行决策分析时最常用的方法.通过这些方法的应用,为临床医生、决策者作出明确的判断提供了有价值的信息.下面通过一个案例来充分说明决策分析在药物经济学中的应用.     

关注健康的公平性

经济学的分析方法可以分为实证分析和规范分析.实证分析研究经济现象的实际情况,回答客观事物是什么的问题;规范分析研究如何处理和解决经济问题,回答应该怎么办的问题.所以,规范分析就是决策分析,宏观的决策分析就是政策分析.政策分析的基本规范原则是效率、公平和稳定.效率和公平似乎是一对矛盾,稳定的原则似乎可以协调效率和公平的关系.但是,从根本上说,上述三个原则是统一的,从人类发展目标出发可以把他们统一起来.     

心身疾病新的评估策略:心身医学研究诊断标准

心身研究的诊断标准(DCPR)是由国际调研组提出的心身医学研究临床诊断概念和结构框架.人们对影响躯体疾病的易损性,病程,预后,康复的心理因素的评估受到日益关注.DCPR的研发理论基础是将来源于心身研究的心理变量转变成用以鉴别诊断的可操作性诊断标准.ICPR是一个简单、有效和可靠的定式访谈工具,可用于筛查、诊断心身疾病和心理生理障碍.补充ICD- 10、DSM、CCMD的临床诊断应用的不足.包含了十二组心身综合征,其目的是将影响躯体状况预后和治疗价值中的心理变量转化为客观的心身医学研究用诊断标准用工具.这十二组症状包括健康焦虑,死亡恐惧症,疾病恐惧症,疾病否认,持续的躯体化症状,转换性障碍,继发于精神障碍的功能性躯体症状,周年反应,精神消沉,易激惹心境,A型行为和述情障碍.提出心身疾病临床多轴诊断系统.     

妊娠期高血压疾病高凝状态的研究

有关研究表明高凝状态在妊娠期高血压疾病的发病中起重要作用,运用哲学观点辩证地研究妊娠期高血压疾病的高凝状态,是我们研究妊娠期高血压疾病切实可行的出路,并且已在长期的研究中得到了体现.     

Formal Requirements of Markov State Models for Paired Associate Learning

Discrete state learning models that make Markov assumptions are a powerful tool for the analysis and optimization of performance in paired associate tasks. We seek here to derive bounds on the complexity needed by such models in order to account for the critical effects of lag and retention intervals on paired associate learning. More specifically, after establishing that two different Markov chains are needed (one for describing the effects of trials where a paired associate is presented and one for describing the effects of trials where the paired associate is not presented), we determine the minimum number of states required in a Markov model with two chains. It is shown formally that, under certain psychologically plausible assumptions, more than three states are required. A model with two chains and four states is presented and it is shown empirically that it can account for the lag and retention effects in paired associate learning. Copyright 2001 Academic Press.     

Quantum dynamics of human decision-making

A quantum dynamic model of decision-making is presented, and it is compared with a previously established Markov model. Both the quantum and the Markov models are formulated as random walk decision processes, but the probabilistic principles differ between the two approaches. Quantum dynamics describe the evolution of complex valued probability amplitudes over time, whereas Markov models describe the evolution of real valued probabilities over time. Quantum dynamics generate interference effects, which are not possible with Markov models. An interference effect occurs when the probability of the union of two possible paths is smaller than each individual path alone. The choice probabilities and distribution of choice response time for the quantum model are derived, and the predictions are contrasted with the Markov model.     

An overview of Markov chain methods for the study of stage-sequential developmental processes

This article presents an overview of quantitative methodologies for the study of stage-sequential development based on extensions of Markov chain modeling. Four methods are presented that exemplify the flexibility of this approach: the manifest Markov model, the latent Markov model, latent transition analysis, and the mixture latent Markov model. A special case of the mixture latent Markov model, the so-called mover-stayer model, is used in this study. Unconditional and conditional models are estimated for the manifest Markov model and the latent Markov model, where the conditional models include a measure of poverty status. Issues of model specification, estimation, and testing using the Mplus software environment are briefly discussed, and the Mplus input syntax is provided. The author applies these 4 methods to a single example of stage-sequential development in reading competency in the early school years, using data from the Early Childhood Longitudinal Study--Kindergarten Cohort.     

Comparison of decision learning models using the generalization criterion method

It is a hallmark of a good model to make accurate a priori predictions to new conditions ( Busemeyer & Wang, 2000 ). This study compared 8 decision learning models with respect to their generalizability. Participants performed 2 tasks (the Iowa Gambling Task and the Soochow Gambling Task), and each model made a priori predictions by estimating the parameters for each participant from 1 task and using those same parameters to predict on the other task. Three methods were used to evaluate the models at the individual level of analysis. The first method used a post hoc fit criterion, the second method used a generalization criterion for short-term predictions, and the third method again used a generalization criterion for long-term predictions. The results suggest that the models with the prospect utility function can make generalizable predictions to new conditions, and different learning models are needed for making short-versus long-term predictions on simple gambling tasks.     

Why older adults make more immediate treatment decisions about cancer than younger adults

Literature relevant to medical decision making was reviewed, and a model was outlined for testing. Two studies examined whether older adults make more immediate decisions than younger adults about treatments for prostate or breast cancer in authentic scenarios. Findings clearly showed that older adults were more likely to make immediate decisions than younger adults. The research is important because it not only demonstrates the consistency of this age-related effect across disease domains, gender, ethnic groups, and prevalent education levels but begins to investigate a model to explain the effect. Major reasons for the effect focus on treatment knowledge, interest and engagement, and cognitive resources. Treatment knowledge, general cancer knowledge, interest, and cognitive resources relate to different ways of processing treatment information and preferences for immediate versus delayed decision making. Adults with high knowledge of treatments on a reliable test tended to make immediate treatment decisions, which supports the knowledge explanation. Adults with more cognitive resources and more interest tended to delay their treatment decisions. Little support was found for a cohort explanation for the relationship between age and preference for immediate medical decision making.     

Joint effects of semantic priming and repetition in a lexical decision task: Implications for a model of lexical access

An experiment is reported which showed that in a lexical decision task semantic priming by a related preceding word and repetition of target words produce additive effects on decision latency. Previous models of lexical access and modifications of them are discussed, and it is argued that some such models predict an interaction of priming and repetition, while others are insufficiently precise to make a prediction. It is suggested that the generality of effects across tasks requiring lexical access must be established and the components of complex effects must be separated before an adequate model can be devised to account for the data.     

Analyzing information search patterns to test the use of a two-phased decision strategy

This study compares three procedures, Payne's index, Van Raaij's index and the single Markov model, to test the hypothesis that subjects apply two decision strategies successively in making a choice. The information search patterns were gathered for 72 subjects by means of an information display board. The decision tasks varied in complexity (3, 5, 8 alternatives and 4, 6, 8 attributes). The number of tests which resulted in a significant difference (p < 0.05) were respectively, six out of eighteen t-tests for Payne's index, fourteen out of eighteen t-tests regarding Van Raaij's index, and eight out of nine Chi-square tests for the single Markov model. The theoretical considerations as well as the results suggest that Payne's index is the least sensitive, and that Van Raaij's index, compared to the Markov model, is less sensitive to detect a difference in strategies used.     

Values interpretation: A new model for hospital ministry

The importance of values in clinical settings is a topic of increasing discussion in the medical literature, but the nature of values and the process of interpreting them have received little attention. The hospital chaplain or religious professional is an underused resource in addressing values issues. This paper summarizes the current models of the hospital chaplaincy in historical context, and then develops a new model drawn from the disciplines of pastoral care and clinical medical ethics in order to address problems involving values in clinical settings. The model construes the chaplain as values interpreter who provides both consultation and liaison functions in clinical situations. We present a clinical case to illustrate the role of the values interpreter. We conclude that the religious professional can make an important contribution to both clinical decision making and medical education through such a model.The authors thank Don S. Browning, Ph.D., and Thomas H. Jobe, M.D., for their critical readings of earlier versions of this paper.     

Analysis of the decision-making process leading to appendectomy: a grounded theory study

The aim was to develop a theoretical understanding of the decision-making process leading to appendectomy. A qualitative interview study was performed in the grounded theory tradition using the constant comparative method to analyze data. The study setting was one county hospital and two local hospitals in Sweden, where 11 surgeons and 15 surgical nurses were interviewed. A model was developed which suggests that surgeons' decision making regarding appendectomy is formed by the interplay between their medical assessment of the patient's condition and a set of contextual characteristics. The latter consist of three interacting factors: (1) organizational conditions, (2) the professional actors' individual characteristics and interaction, and (3) the personal characteristics of the patient and his or her family or relatives. In case the outcome of medical assessment is ambiguous, the risk evaluation and final decision will be influenced by an interaction of the contextual characteristics. It was concluded that, compared to existing, rational models of decision making, the model presented identified potentially important contextual characteristics and an outline on when they come into play.