Understanding and Improving Decision-making in Pneumonia with Informatics

导言：本提案旨在了解和改进退伍军人肺炎救治工作 通过信息学。 背景：肺炎是美国最常见的传染病死亡原因， 估计每年有50,000人死亡，花费80-100亿美元。每年有12 2.5万名退伍军人 年在急诊科，20,000人住院。13风险调整后30天死亡率范围 在退伍军人管理局设施中，从11%到18%。用于肺炎的资源也千差万别，费用为 住院护理估计高达门诊护理的25倍。20为提高肺炎护理标准， 紧张的研究和质量改进工作的重点是建立以证据为基础的 肺炎的实践指南，代表了从我们的研究和意见中产生的共识 最好的学术医院和肺炎专家。然而，我们继续看到这两种管理方式的差异 以及退伍军人事务部和其他系统的结果，这表明指南可能很难应用于REAL 练习一下。我们的电子健康记录的最新进展使我们能够衡量这两个方面的实际做法 人口和个人层面。通过研究慢性阻塞性肺疾病患者分诊和抗生素决定的差异 肺炎，我们可以从我们自己的人口中学习产生证据，包括以前的 对患者、环境和场景的代表性不足，使其更接近实际情况。 职业目标：我的职业目标是：1)发展先进的人口分析技能，2)获得基础 在行为科学方面，以及3)在信息学方面发展更深的理解。 研究目标：我的研究目标与我的职业目标相一致：(1)检查分诊中的变异来源 以及退伍军人事务部急诊科肺炎的抗生素选择决定。(2)描述 影响急诊科提供者肺炎决策的认知过程 在决策过程中表现出多样性。(3)设计并测试支持决策的信息化工具-- 制作，与工作流程集成，并允许我们从临床经验中学习。 方法：目标1.建立和测试用于分类和抗生素选择的实践变异模型和b. 将在整个退伍军人管理局系统中确定决策门槛高和低的急诊科。目标 2将使用混合方法来表征临床推理的认知过程和背景影响 通过与供应商的面谈影响决策。AIM 3将利用实时信息学工具进行测试 当前的最佳实践建议通过为医生提供机会来反对医生的决定 不同意任何建议，并收集关于不同意的原因的信息。 影响：这项工作将直接为退伍军人管理局肺炎信息学工具的开发提供信息。 最终，虽然我的临床兴趣是肺炎，但我开发的技能将应用于许多临床 在不确定的背景下做出决策的医学问题。

Introduction: This proposal aims to understand and improve the care of Veterans treated for pneumonia through informatics. Background: Pneumonia is the most common infectious cause of death in the United States, with an estimated 50,000 deaths and $8-10 billion in costs annually.12 Twenty-five thousand Veterans are seen per year in the Emergency Department, and 20,000 are hospitalized.13 Risk adjusted 30-day mortality rates range among VA facilities from 11% to 18%. The resources utilized for pneumonia also vary widely, with the cost of hospital care estimated at up to 25 times that of outpatient care.20 To improve the standard of pneumonia care, intense research and quality improvement efforts have been focused upon establishing evidence-based practice guidelines for pneumonia that represent a consensus of research and opinions generated from our best academic hospitals and pneumonia experts. However, we continue to see variation in both management and outcomes across the VA as in other systems, suggesting that guidelines may be difficult to apply to real practice. The recent advancement of our electronic health record allows us to measure actual practice at both the population and the individual level. By studying variation in triage and antibiotic decisions for patients with pneumonia, we can learn from our own population to generate evidence that includes the previously underrepresented patients, settings and scenarios, bringing it closer to real practice. Career Aims: My career goals are to: 1) Develop skills in advanced population analytics, 2) Gain a foundation in behavioral sciences, and 3) Develop a deeper understanding in informatics. Research Aims: My research aims build toward my career aims: (1) Examine sources of variation in triage and antibiotic selection decisions for pneumonia across VA emergency departments. (2) Characterize the cognitive processes influencing decision-making in pneumonia among providers at emergency departments demonstrating variation in decision-making. (3) Design and test an informatics tool that supports decision- making, integrates with workflow, and allows us to learn from clinical experience. Methods: Aim 1 A. will develop and test models of practice variation for triage and antibiotic selection and b. will identify emergency departments with high and low decision-making thresholds across the VA system. Aim 2 will use mixed methods to characterize the cognitive process of clinical reasoning and contextual influences impact decision-making through interviews with providers. Aim 3 will utilize a real-time informatics tool to test current best practice recommendations against physician decisions by providing physicians the opportunity to disagree with any recommendations, and collect information on reasons for disagreement. Impact: This work will directly inform the development of informatics tools for pneumonia for the VA. Ultimately, while my clinical interest is in pneumonia, the skills I develop will be applied to many clinical problems in medicine where decision-making occurs in the setting of uncertainty.