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Markov modeling for the neurosurgeon: a review of the literature and an introduction to cost-effectiveness research

机译：神经外科医师的马尔可夫建模：文献综述和成本效益研究导论

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OBJECTIVE Markov modeling is a clinical research technique that allows competing medical strategies to be mathematically assessed in order to identify the optimal allocation of health care resources. The authors present a review of the recently published neurosurgical literature that employs Markov modeling and provide a conceptual framework with which to evaluate, critique, and apply the findings generated from health economics research. METHODS The PubMed online database was searched to identify neurosurgical literature published from January 2010 to December 2017 that had utilized Markov modeling for neurosurgical cost-effectiveness studies. Included articles were then assessed with regard to year of publication, subspecialty of neurosurgery, decision analytical techniques utilized, and source information for model inputs. RESULTS A total of 55 articles utilizing Markov models were identified across a broad range of neurosurgical subspecialties. Sixty-five percent of the papers were published within the past 3 years alone. The majority of models derived health transition probabilities, health utilities, and cost information from previously published studies or publicly available information. Only 62% of the studies incorporated indirect costs. Ninety-three percent of the studies performed a 1-way or 2-way sensitivity analysis, and 67% performed a probabilistic sensitivity analysis. A review of the conceptual framework of Markov modeling and an explanation of the different terminology and methodology are provided. CONCLUSIONS As neurosurgeons continue to innovate and identify novel treatment strategies for patients, Markov modeling will allow for better characterization of the impact of these interventions on a patient and societal level. The aim of this work is to equip the neurosurgical readership with the tools to better understand, critique, and apply findings produced from cost-effectiveness research.
机译：目标马尔可夫建模是一种临床研究技术，可以对竞争性医疗策略进行数学评估，以识别医疗保健资源的最佳配置。作者介绍了最近发表的神经外科文献的综述，该文献采用了马尔可夫模型，并提供了一个概念框架来评估，批判和应用从卫生经济学研究中得出的发现。方法检索PubMed在线数据库以识别2010年1月至2017年12月发表的神经外科文献，这些文献已利用马尔可夫模型进行了神经外科成本效益研究。然后根据发表年份，神经外科亚专业，所使用的决策分析技术以及模型输入的来源信息对纳入的文章进行评估。结果在广泛的神经外科亚专业领域共鉴定了55篇利用马尔可夫模型的文章。仅在过去的3年中，就有65％的论文发表了。大多数模型从先前发布的研究或可公开获得的信息中得出健康过渡概率，健康效用和成本信息。只有62％的研究包含间接费用。百分之九十三的研究进行了1向或2向敏感性分析，而67％的研究进行了概率敏感性分析。提供了对马尔可夫建模的概念框架的回顾，并解释了不同的术语和方法。结论随着神经外科医生的不断创新和为患者确定新的治疗策略，马尔可夫模型将有助于更好地表征这些干预措施对患者和社会的影响。这项工作的目的是为神经外科读者提供工具，以更好地理解，批判和应用从成本效益研究中获得的发现。

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