A knowledge-based message tailoring system

摘要 医疗保健组织拥有丰富的关于护理质量和结果的数据，但缺乏可推广的战略 将他们的数据用于工作以提高性能。向医疗保健部门提供临床表现反馈 专业人士是一种广泛使用的绩效改进策略，但有关其使用的证据显示了一种模式 在几十年的试验中产生了复杂的效果。心理学理论在临床设计中的应用不足 性能反馈，但它提供了强大的解释机制，以改善认知加工和 反馈消息的影响。基于知识的消息定制系统可以用理论上的推理 知识和临床表现数据，以预测最佳反馈消息格式和内容，同时 提供报文设计基本原理的解释。这项建议的研究目标是开发和 评估用于临床表现反馈的基于知识的消息定制系统。拟议中的工作 将在抗菌素管理的健康领域进行，这是全球 对临床医生的反馈通常被用来促进行为改变的重要性。的具体目标 建议项目是1)开发基于理论的绩效消息剪裁的知识库 反馈，2)创建抗菌管理的消息定制系统，3)评估 与医疗保健专业人员一起定制的原型消息系统。通过实现这些目标，候选人 将获得研究经验并增强对开发和评估 临床环境中的基于知识的系统。NLMK01奖项创造的培训机会将 使应聘者在本体开发、知识工程和 认知研究，并在密歇根大学的研究社区中开展合作。这个 该奖项最终将帮助候选人实现其转变现有知识的长期目标 将报文剪裁成可计算的形式，以进行关于 临床表现反馈和其他形式的临床建议。

Abstract Healthcare organizations are rich in data about care quality and outcomes, but lack generalizable strategies for putting their data to work to improve performance. Giving clinical performance feedback to healthcare professionals is a widely used performance improvement strategy, but evidence about its use shows a pattern of mixed effects over decades of trials. Psychological theory is underutilized in the design of clinical performance feedback, yet it offers robust explanatory mechanisms to improve the cognitive processing and impact of feedback messages. A knowledge-based message tailoring system could reason with theoretical knowledge and clinical performance data to predict optimal feedback message formats and content, while offering explanations of the message design rationale. The research goal of this proposal is to develop and evaluate a knowledge-based message tailoring system for clinical performance feedback. The proposed work will be carried out in the health domain of antimicrobial stewardship, a well-defined domain of global importance in which feedback to clinicians is routinely used to promote behavior change. The specific aims of the proposed project are 1) Develop a knowledge base for theory-based message tailoring of performance feedback, 2) Create a message tailoring system for antimicrobial stewardship, and 3) Evaluate the function of the prototype message tailoring system with healthcare professionals. By achieving these aims, the candidate will gain research experience and enhance his knowledge about the development and evaluation of knowledge-based systems in clinical settings. The training opportunities created by the NLM K01 award will enable the candidate to enhance his knowledge in ontology development, knowledge engineering, and cognitive studies, and to develop collaborations in the research community at the University of Michigan. The award will ultimately help the candidate to achieve his long-term goal of transforming existing knowledge about message tailoring into computable forms for the purpose of conducting research about the effectiveness of clinical performance feedback and other forms of clinical advice.