Developing Information Technology to Support Clinical Thinking During Safety-Critical Tasks

每年约有700名加拿大人死于可预防的药物不良反应。这些药物不良事件在很大程度上可以通过技术解决方案来预防。然而，现有的技术解决方案在支持临床推理和解决问题的能力方面存在不足。因此，这项研究计划的总体目标是识别和建模参与批判性思维的认知过程，并在临床信息技术（IT）支持系统的设计中使用这些知识，以最终降低用药错误率。 我们独特的科学方法是开发一个通用的认知辅助平台，以解决不同的任务类型和错误类型，可应用于不同的临床技术。这项工作的很大一部分将是针对确定如何任务变量，如复杂性（例如，简单的程序性任务对复杂的适应性问题解决任务）和熟悉度（例如，常规任务与意外任务）影响人们如何推理和解决问题。这个研究领域不是很发达，但它是根本通知临床IT支持系统的设计，更容易使用，不太可能导致错误的委员会，并提高整体能力，提供援助时，面对意外情况。这项工作预计将有助于自然科学和工程领域在几个方面，包括新的IT系统设计，理论和经验模型，解释人们如何结构他们的知识，原因，并解决问题时，执行安全关键任务的发展。此外，这项研究计划提供了一个独特的机会，在跨健康和工程领域的多学科环境中培养研究生。

Every year, some 700 Canadians die from preventable adverse drug events. These adverse drug events can in large part be prevented using technological solutions. However, existing technological solutions are deficient in their ability to support clinical reasoning and problem solving. As such, the overarching goal of this research program is to identify and model the cognitive processes involved in critical thought and use this knowledge in the design of clinical Information Technology (IT) support systems to ultimately decrease medication error rates. Our unique scientific approach is to develop a universal platform of cognitive aids that address different task types and error types that could be applied to different clinical technologies. A significant portion of this work will be targeted at determining how task variables such as complexity (e.g., simple procedural tasks vs. complex adaptive problem solving tasks) and familiarity (e.g., routine tasks vs. unexpected tasks) influence how people reason and problem solve. This research area is not very well developed yet it is fundamental to informing the design of clinical IT support systems that are easier to use, less likely to lead to commission of an error, and improve overall ability to provide assistance when face with unexpected situations. This work is expected to contribute to the field of natural science and engineering in several ways, including the development of new IT system designs, theoretical and empirical models that explain how people structure their knowledge, reason, and problem-solve when performing safety-critical tasks. Moreover, this research program offers a unique opportunity for the training of graduate students in a multidisciplinary setting spanning the health and engineering fields.