用于决策支持的框架,以帮助在发生模糊故障时分配资源

M. Hertz, M. Hertz
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引用次数: 0

摘要

这个决策工具是通过因果哲学、认知工程、认知心理学和人为因素的框架开发出来的,它在总体上显示出能够降低系统复杂性的希望。虽然研究结果没有他们希望的那么高,但作者在如何展示该工具以及应该在何处进行更改方面吸取了许多教训。从基于案例研究的试点研究开始,下一步将朝着医疗差错领域发展。医学界正在为如何降低错误率而苦苦挣扎。该字段的错误率和复杂性是系统属性。如果不改变系统的运作方式,就很难降低医院和整个行业的总体错误率。希望通过使用类似于这里所展示的工具,每个参与者将能够看到他们如何适应更大的系统。通过降低系统表示复杂性和单个任务(如手术或药物分配)的复杂性,可以在降低错误率方面取得真正的进展。
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Framework for a decision support to aid in the allocation of resources in the event of an ambiguous failure
The decision tool that was developed via a framework of philosophy of causation, cognitive engineering, cognitive psychology and human factors, shows promise in being able to reduce the complexity of systems in general. While the findings are not as high as they hoped, the authors learned many lessons about how the tool should be presented and where changes should be made. From the pilot study based that is based on a case study, the next move will be towards the field of medical error. The field of medicine is struggling with how to lower its error rates. The error rates and complexity of the field are system properties. Without changing how the system functions, little can be done to reduce the overall error rates of hospitals and the profession in general. It is hoped that through the use of a tool similar to the one presented here, each actor will be able to see how they fit into the larger system. Through a reduction of system representational complexity and through a reduction in the complexity of individual tasks, such as surgery or medication distribution, real progress towards lowering error rates can occur.
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