A scalable service to improve health care quality through precision audit and feedback

所有医疗保健提供组织都越来越多地通过电子临床 质量测量1和仪表板2，3。然而，这些组织缺乏以证据为基础的战略， 他们的质量和结果数据，以提高性能4，5.最常见的方法是审计， 反馈（A&F），向提供者提供临床性能总结，这表明了 对临床实践的巨大影响6-8.但A&F往往产生微不足道的影响5，9， 分散供应商谁是疲惫的信息混乱9-11.正如目前实施的，A&F是一个生硬的， “一刀切”的干预措施。护理环境中的每个提供者通常在一个或多个医疗保健服务中接收相同的度量。 通用格式，尽管人们越来越认识到“精确化”干预措施对 提高其影响12-15。A&F的精确方法将优先显示单个 对于每个接收者，具有最高值以提高性能的度量，例如当度量 水平首次低于同行基准或最低标准， 业绩差距16-19.此外，精确A&F将采用最佳消息格式（包括成帧 和视觉显示20-24），基于对接收者的了解和所期望的主旨含义， 沟通，以改善信息解释，同时减少认知处理负担25-28。好吧- 既定的心理学原则、框架和理论机制提供了知识基础， 达到精度A&F 16- 19，29 -33。从信息学的角度来看，精确的A&F需要基于知识的 以心理学理论为核心的系统，但通过优先考虑 到有关组和个人级别的收件人的可配置知识。一个精确的A&F服务雇用 这种知识作为要求（消息可接受性的必要特征）和偏好（ 消息特征的相对重要性）来生成比“一刀切”更有可能的消息 大多数”报告积极影响临床决策和实践。同样重要的信息学 挑战是通过大规模的精密A&F服务实现广泛的改进。一个可扩展 精确的A&F服务必须作为与各种计算环境兼容的基础设施 并支持广泛的临床领域。在他之前的NLM K奖中，首席研究员 开发并测试了一个基于知识的原型系统，用于麻醉电子邮件中的精确A&F 在乎初步数据显示，提供商的偏好并不统一，这表明， 可计算知识是支持可扩展精度A&F所必需的。知识网格平台， 密歇根大学开发的，已被证明支持临床决策的“精确化” 支助系统34-36.根据我们以前的工作，拟议的项目将促进创造更普遍的 为精确的A&F服务，将该服务应用于麻醉护理作为示范领域。

All health care delivery organizations measure care quality and outcomes, increasingly via electronic clinical quality measures 1 and dashboards 2,3. However, these organizations lack evidence-based strategies for putting their quality and outcome data to work to improve performance 4,5. The most common approach is audit and feedback (A&F), the delivery of clinical performance summaries to providers, which demonstrates potential for large effects on clinical practice 6–8. But A&F too often produces negligible effects 5,9, creating little more than distraction for providers who are fatigued by information chaos 9–11. As currently implemented, A&F is a blunt, “one size fits most” intervention. Each provider in a care setting typically receives identical metrics in a common format, despite a growing recognition that “precisionizing” interventions holds significant promise to improve their impact 12–15. A precision approach to A&F would prioritize display of information in the single metric that, for each recipient, carries the highest value for improving performance, such as when the metric's level drops below a peer benchmark or minimum standard for the first time, revealing an actionable performance gap 16–19. Furthermore, precision A&F would employ an optimal message format (including framing and visual displays 20–24), based on what is known about the recipient and the intended gist meaning being communicated, to improve message interpretation while reducing cognitive processing burden 25–28. Well- established psychological principles, frameworks, and theoretical mechanisms provide a knowledge base to achieve precision A&F 16–19,29–33. From an informatics perspective, precision A&F requires a knowledge-based system that uses psychological theory at its core, but which enables mass customization by giving precedence to configurable knowledge about recipients at the group and individual levels. A precision A&F service employs this knowledge as requirements (necessary characteristics for message acceptability) and preferences (the relative importance of message characteristics) to generate messages that are more likely than a “one size fits most” report to positively influence clinical decision-making and practice. An equally important informatics challenge is to enable widespread improvement through a service for precision A&F at scale. A scalable precision A&F service must function as infrastructure compatible with a wide range of computing environments and supporting a wide range of clinical domains. In his previous NLM K-award, the principal investigator developed and tested a prototype knowledge-based system for precision A&F in email messages in anesthesia care. Preliminary data show that provider preferences are not uniform, suggesting that a platform for computable knowledge is necessary to support scalable precision A&F. The Knowledge Grid platform, developed at the University of Michigan, has been shown to support “precisionizing” for clinical decision support systems 34–36. Based on our prior work, the proposed project will advance the creation of more general services for precision A&F, applying the service in anesthesia care as a demonstration domain.