Bayesian analysis: an objective, scientific approach to better decisions.

H Jones
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Abstract

An important responsibility for managers is to see that good decisions are made, which includes training other decision makers in how to make them. In our rapidly changing health-care environment, it is important that the best decisions be made based on cost-effectiveness (tests we perform or outsource), productivity (employees we hire), service quality (how we organize services), technology (equipment and methods we purchase), and outcomes (what we accomplish for patients). A decision analysis method is described that uses an objective, scientific approach to decision making. Bayesian analysis is a statistical method that allows researchers (decision makers) to take into account data as well as prior beliefs to calculate the probability that an alternative (decision, treatment) is superior. Developing criteria, prior rating, of options, and calculating assessments and final assessment are included in the analysis. An example is provided to show how our laboratory compared routine hematology automation alternatives (automated cell counter, automated microscope, and automated flow cytometry cell counter) using the Bayesian analytical technique. Discussion follows related to how the technique is effective in managing team decisions by allowing different opinions, past experiences, and beliefs to be expressed and evaluated.

贝叶斯分析:一种做出更好决策的客观、科学的方法。
管理者的一项重要责任是确保做出正确的决策,这包括培训其他决策者如何做出正确的决策。在我们快速变化的医疗保健环境中,重要的是要根据成本效益(我们执行或外包的测试)、生产力(我们雇用的员工)、服务质量(我们如何组织服务)、技术(我们购买的设备和方法)和结果(我们为患者完成的工作)做出最佳决策。本文描述了一种采用客观、科学的方法进行决策的决策分析方法。贝叶斯分析是一种统计方法,它允许研究人员(决策者)考虑数据以及先验信念来计算替代方案(决策,治疗)更优的概率。制定标准、预先评级、选择、计算评估和最终评估都包括在分析中。提供了一个例子来展示我们的实验室如何使用贝叶斯分析技术比较常规血液学自动化替代方案(自动细胞计数器,自动显微镜和自动流式细胞仪细胞计数器)。接下来的讨论涉及到该技术如何通过允许不同的意见、过去的经验和信念被表达和评估来有效地管理团队决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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