关于在医疗过程中的风险,必须由病人和他们的医生决定,毕竟这对病人的健康和生命利害攸关。但如果不能给病人一些关于治疗的风险和益处,他们就不会被安排在这个决策过程中。这种风险一般由专科医师的共识面板使用配套的医学文献来评估。不幸的是,这种文学并不总是提供一个良好的风险估计,特别是在极少数情况下。本书展示了统计方法,可以用来研究问题的风险。这些措施包括核密度估计,预测建模,关联规则和文本分析。它还表明,通过例如,这些技术如何提供有意义的结果,探讨目前的方法,并讨论一些模型中的缺陷,这可能会导致错误的结果。一般医疗风险的概念引入后,课题包括药物和治疗方法中很少发生的调查过程,权衡风险和收益之间,临床试验结果的推断和风险所致的医疗费用。还检视了竞争风险,错误,和使用群体特征,以及看起来徒劳的问题。本书的最后一章提供了一般性讨论和总结,本书的最后一章提供了一般性讨论和总结,和一个附录显示了使用SAS Enterprise Miner的执行在文本中使用的模型的过程。Decisions regarding the risks involved in medical treatments must belong to patients and their physicians – after all, it is the patient''s health and life which is at stake. But patients will not be equipped for this decision-making process if they cannot be given some idea as to the risks and benefits of treatment. Such risks are generally estimated by a consensus panel of specialist physicians using supporting medical literature. Unfortunately, this literature does not always provide a good estimate of risk, particularly in the case of rare occurrences. This book demonstrates statistical techniques that can be used to investigate matters of risk. These include kernel density estimation, predictive modeling, association rules and text analysis. It also shows, through example, how these techniques can provide meaningful results, and examines current methods, discussing some of the flaws in models which may lead to misleading results. After a general introduction to the concept of medical risk, the subjects covered include the process by which rare occurrences are investigated in drugs or treatments, the trade-offs between risks and benefits, extrapolation of clinical trial results and the cost of healthcare in relation to risks. It also examines problems such as competing risks, error, and the use of group identities, as well as looking at the issue of futility. The book concludes with a chapter providing a general discussion and summary, and an appendix shows some of the processes for using SAS Enterprise Miner to perform some of the models used in the text.
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