Antibiotic Utilization Patterns and Impact on Outcomes for Patients with Respiratory Viral Sepsis

尽管越来越多的人认识到病毒是败血症的重要原因，但大多数临床医生和 政策制定者倾向于将脓毒症等同于细菌感染。因此，当前的指导方针强调 对所有疑似脓毒症患者立即给予抗生素治疗，即使抗生素不会 使纯病毒败血症患者受益，并可能在个人和人群水平上造成损害。 然而，病毒对脓毒症总体负担的贡献没有得到很好的描述，而且很重要。 关于抗生素的使用模式和潜在的抗生素相关危害的问题仍然存在 人口。拟议的项目试图提供对社区发病比例的严格估计。 由呼吸道病毒引起的脓毒症，描述目前抗生素在病毒性败血症中的使用情况，量化潜力 与抗生素相关的危害，并确定哪些患者亚组可以安全地限制抗生素。这个 该提案的最终目标是促进对脓毒症患者进行更安全、更细微的治疗，符合 AHRQ声明的优先事项是提高患者安全和避免伤害。建议的研究将实现 通过使用来自200多个不同种类的电子健康记录(EHR)的具有丰富临床数据的大型数据集来实现这一目标 医院，一种基于EHR的有效方法来识别脓毒症，以及复杂的因果推断统计 解决混淆的技术，以追求三个目标：(1)确定社区的比例- 呼吸道病毒引起的首发脓毒症和抗生素使用的特征及延长的预测因素 抗生素在这一人群中的应用；(2)评估病毒性肝炎患者抗生素处方的医院水平差异。 并评估高使用率和低使用率医院患者的风险调整结果；以及(3) 评估阳性病毒检测和低降钙素原水平相结合作为指标的潜在实用性 抗生素可以安全地被扣留或迅速停用。 候选人克莱尔·沙佩尔博士是一名高级研究员，也是肺部和重症监护内科医生 在布里格姆妇女医院(BWH)拥有使用EHR数据的经验，以获得对以下方面的可行见解 重症监护中的问题。Sappell博士在K08期间的目标是提高对以下方面的熟练程度 获取、准备和处理大型医疗保健数据集；学习因果关系的统计方法 推理分析，包括对多水平数据的倾向评分方法和方法；获得以下方面的专业知识 使用R统计计算软件；加强科学交流能力。要实现 为了实现这些目标，她组建了一个由Michael Klompas博士和Chanu博士领导的多学科指导团队 将EHR数据用于脓毒症监测和结果研究的专家。在完成 K08颁奖期间，谢佩尔博士将处于有利地位，实现她成为一名 独立内科医生-科学家，具有使用大型临床数据集改善危重病人护理的专业知识 患者，特别关注败血症和抗生素的使用。

Although there is increasing recognition that viruses are an important cause of sepsis, most clinicians and policymakers tend to equate sepsis with bacterial infection. As a result, current guidelines emphasize immediate administration of antibiotics for all patients with suspected sepsis, even though antibiotics will not benefit patients with pure viral sepsis and may cause harm at both the individual and population levels. However, the contribution of viruses to the overall burden of sepsis is poorly characterized, and important questions remain about antibiotic utilization patterns and potential antibiotics-associated harms in this population. The proposed project seeks to provide rigorous estimates of the proportion of community-onset sepsis caused by respiratory viruses, describe current antibiotic utilization in viral sepsis, quantify potential antibiotic-associated harms, and identify patient subgroups in whom antibiotics can safely be limited. The ultimate goal of the proposal is to promote safer, more nuanced treatment for patients with sepsis, in line with AHRQ’s stated priorities of improving patient safety and avoiding harm. The proposed research will accomplish this goal by using large datasets with rich clinical data from electronic health records (EHR) at over 200 diverse hospitals, a validated EHR-based approach to identifying sepsis, and sophisticated causal inference statistical techniques to address confounding in order to pursue three aims: (1) Determine the fraction of community- onset sepsis attributable to respiratory viruses and characterize antibiotic use and predictors of prolonged antibiotics in this population; (2) Assess hospital-level variation in antibiotic prescribing for patients with viral sepsis and evaluate risk-adjusted outcomes for patients at high- versus low- utilization hospitals; and (3) Assess the potential utility of the combination of positive viral assay and low procalcitonin level as an indicator that antibiotics can safely be withheld or rapidly discontinued. The candidate, Dr. Claire Shappell, is an advanced research fellow and Pulmonary and Critical Care physician at Brigham and Women’s Hospital (BWH) with experience using EHR data to gain actionable insights into problems in critical care. Dr. Shappell’s goals during the K08 period are to develop advanced proficiency with the acquisition, preparation, and handling of large healthcare datasets; learn statistical methods for causal inference analysis including propensity score methods and approaches to multilevel data; acquire expertise in the use of R statistical computing software; and strengthen abilities in scientific communication. To achieve these goals, she has assembled a multidisciplinary mentorship team led by Drs. Michael Klompas and Chanu Rhee, experts in the use of EHR data for sepsis surveillance and outcomes research. By the completion of the K08 award period, Dr. Shappell will be well-positioned to achieve her long-term goal of becoming an independent physician-scientist with expertise using large clinical datasets to improve care for critically ill patients, with a particular focus on sepsis and antibiotic utilization.