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脓毒症的重要原因，但大多数临床医生和 决策者往往将败血症等同于细菌感染。因此，目前的指导方针强调， 对所有疑似脓毒症的患者立即给予抗生素，即使抗生素不会 对纯病毒性脓毒症患者有益，但可能在个体和群体水平上造成伤害。 然而，病毒对脓毒症总体负担的贡献特征不佳，并且重要的是， 关于抗生素使用模式和潜在的抗生素相关危害的问题仍然存在， 人口拟议的项目旨在提供社区发病比例的严格估计， 呼吸道病毒引起的脓毒症，描述目前病毒性脓毒症中抗生素的使用，量化潜在的 与抗生素相关的伤害，并确定可以安全限制抗生素使用的患者亚组。的 该提案的最终目标是促进脓毒症患者更安全，更细致的治疗， AHRQ声明的优先事项是改善患者安全和避免伤害。这项研究将实现 通过使用来自200多个不同的电子健康记录（EHR）的丰富临床数据的大型数据集， 医院，一个有效的EHR为基础的方法来识别败血症，和复杂的因果推理统计 技术来解决混淆，以追求三个目标：（1）确定社区的分数- 呼吸道病毒引起败血症发作、抗生素使用特征和长期败血症的预测因素 （2）评估病毒性肝炎患者抗生素处方的医院水平差异 脓毒症，并评估高利用率医院与低利用率医院患者的风险调整结局;以及（3） 评估阳性病毒检测和低降钙素原水平联合作为指标的潜在效用 抗生素可以安全地停用或迅速停用。 候选人Claire Shappell博士是一名高级研究员，也是肺部和重症监护医生 在布里格姆妇女医院（BWH）的经验，使用EHR数据，以获得可操作的见解， 重症监护中的问题。Shappell博士在K 08期间的目标是发展高级熟练程度， 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，包括倾向评分方法和多层次数据的方法;获得专业知识， R统计计算软件的使用;加强科学交流能力。实现 为了实现这些目标，她组建了一个由Michael Klompas博士和Chanu博士领导的多学科导师团队。 Rhee是使用EHR数据进行脓毒症监测和结局研究的专家。在完成 K 08奖期间，Shappell博士将处于有利地位，以实现她的长期目标，成为一个 独立医生兼科学家，拥有使用大型临床数据集改善重症患者护理的专业知识 患者，特别关注脓毒症和抗生素使用。

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.