PDF(Pubmed)
Abstract：
UNASSIGNED: When performance data are provided as feedback to healthcare professionals, they may use it to significantly improve care quality. However, the question of how to provide effective feedback remains unanswered, as decades of evidence have produced a consistent pattern of effects-with wide variation. From a coaching perspective, feedback is often based on a learner\'s objectives and goals. Furthermore, when coaches provide feedback, it is ideally informed by their understanding of the learner\'s needs and motivation. We anticipate that a \"coaching\"-informed approach to feedback may improve its effectiveness in two ways. First, by aligning feedback with healthcare professionals\' chosen goals and objectives, and second, by enabling large-scale feedback systems to use new types of data to learn what kind of performance information is motivating in general. Our objective is to propose a conceptual model of precision feedback to support these anticipated enhancements to feedback interventions.
UNASSIGNED: We iteratively represented models of feedback\'s influence from theories of motivation and behavior change, visualization, and human-computer interaction. Through cycles of discussion and reflection, application to clinical examples, and software development, we implemented and refined the models in a software application to generate precision feedback messages from performance data for anesthesia providers.
UNASSIGNED: We propose that precision feedback is feedback that is prioritized according to its motivational potential for a specific recipient. We identified three factors that influence motivational potential: (1) the motivating information in a recipient\'s performance data, (2) the surprisingness of the motivating information, and (3) a recipient\'s preferences for motivating information and its visual display.
UNASSIGNED: We propose a model of precision feedback that is aligned with leading theories of feedback interventions to support learning about the success of feedback interventions. We plan to evaluate this model in a randomized controlled trial of a precision feedback system that enhances feedback emails to anesthesia providers.
UNASSIGNED: We iteratively represented models of feedback\'s influence from theories of motivation and behavior change, visualization, and human-computer interaction. Through cycles of discussion and reflection, application to clinical examples, and software development, we implemented and refined the models in a software application to generate precision feedback messages from performance data for anesthesia providers.
UNASSIGNED: We propose that precision feedback is feedback that is prioritized according to its motivational potential for a specific recipient. We identified three factors that influence motivational potential: (1) the motivating information in a recipient\'s performance data, (2) the surprisingness of the motivating information, and (3) a recipient\'s preferences for motivating information and its visual display.
UNASSIGNED: We propose a model of precision feedback that is aligned with leading theories of feedback interventions to support learning about the success of feedback interventions. We plan to evaluate this model in a randomized controlled trial of a precision feedback system that enhances feedback emails to anesthesia providers.
摘要：
■当绩效数据作为反馈提供给医疗保健专业人员时，他们可能会使用它来显著提高护理质量。然而,如何提供有效反馈的问题仍然没有答案，几十年来的证据产生了一致的效应模式--差异很大。从教练的角度来看，反馈通常基于学习者的目标和目标。此外，当教练提供反馈时，这是由他们的理解学习者的需求和动机的理想信息。我们预计，“教练”知情的反馈方法可能会在两个方面提高其有效性。首先,通过将反馈与医疗保健专业人员选择的目标和目标保持一致，第二,通过使大规模反馈系统能够使用新类型的数据来了解什么样的性能信息通常是激励。我们的目标是提出精确反馈的概念模型，以支持对反馈干预措施的这些预期增强。
■我们从动机和行为改变的理论中迭代地表示反馈的影响模型，可视化,和人机交互。通过讨论和反思的循环，应用于临床实例，和软件开发，我们在一个软件应用程序中实现并改进了模型,以便从麻醉提供者的表现数据中生成精确反馈信息.
■我们提出，精确反馈是根据其对特定接受者的动机潜力而优先考虑的反馈。我们确定了影响动机潜力的三个因素：(1)接受者表现数据中的动机信息，(2)激励信息的惊奇，和(3)接收者对激励信息及其视觉显示的偏好。
■我们提出了一种精确反馈模型，该模型与反馈干预的主要理论保持一致，以支持学习反馈干预的成功。我们计划在一项精确反馈系统的随机对照试验中评估该模型，该系统可增强对麻醉提供者的反馈电子邮件。
■我们从动机和行为改变的理论中迭代地表示反馈的影响模型，可视化,和人机交互。通过讨论和反思的循环，应用于临床实例，和软件开发，我们在一个软件应用程序中实现并改进了模型,以便从麻醉提供者的表现数据中生成精确反馈信息.
■我们提出，精确反馈是根据其对特定接受者的动机潜力而优先考虑的反馈。我们确定了影响动机潜力的三个因素：(1)接受者表现数据中的动机信息，(2)激励信息的惊奇，和(3)接收者对激励信息及其视觉显示的偏好。
■我们提出了一种精确反馈模型，该模型与反馈干预的主要理论保持一致，以支持学习反馈干预的成功。我们计划在一项精确反馈系统的随机对照试验中评估该模型，该系统可增强对麻醉提供者的反馈电子邮件。
