Understanding and Informing Early Hospital Antibiotic Prescribing for Potential Infection

背景：每年有数百万美国人因疑似感染住院并接受抗生素治疗。 目前的指南强烈要求广谱抗生素在一生中最短的1小时内给药。 危险病例：严重败血症和感染性休克。然而，与其他时间敏感的医疗紧急情况不同， 严重脓毒症的诊断尚无客观标准。然而，政府的几项举措激励了 严重脓毒症的快速抗生素治疗。人们越来越担心，这种对早期的强烈关注 抗生素将增加抗生素的总体使用，从而导致抗菌素耐药性。这台R01将测量 与加快使用抗生素的时间相关的权衡，以便为个人床边决策提供信息 和联邦政策。 具体目标：(1)医院抗生素处方行为：当医院加快抗生素使用时间 对于严重脓毒症的分娩，这种变化与抗生素使用量的增加和更广泛的应用有多大关系 所有可能感染的人群的覆盖范围？(A2)个人损害/利益： 对于个别患者，我们将量化：(A)与极短疗程抗生素相关的伤害风险 (过敏反应、肾或肝损伤、细胞减少症、艰难梭菌感染、新耐药细菌的分离以及 死亡率)；(B)与较早提供抗生素有关的死亡率效益。A3)医院网络的危害/好处： 根据抗生素处方的时间变化(目标1)、患者水平的危害/益处(目标2)和医院 严重败血症和感染性休克的患病率，我们将估计与以下各项相关的净收益和危害 模拟抗生素处方的时间变化。 预期影响：这项工作将量化与加快实现以下目标相关的处方权衡 抗生素，非常短疗程的抗生素的个体患者水平的危害，以及更快的好处 抗生素注射，跨患者亚组。最后，我们将量化以下项目的净收益和危害 加快不同类型医院使用抗生素的时间，这些医院的脓毒症患病率和 与加速使用抗生素有关的负外部性的大小。 独特功能和创新：使用来自Kaiser Permanente Northern的细粒度、患者级别的数据 加州(KPNC)和全国退伍军人事务部(VA)，以及一项新的抗菌覆盖措施 频谱(频谱评分)，我们将评估更快的抗生素计时的整体好处和危害，使 关于利益平衡的简要判断直截了当，内容翔实。 项目方法：我们将审查所有可能入院的KNPC和VA住院(2013-2018年) 感染。我们将使用多层次评估特定医院抗生素处方模式的时间趋势 模特们。我们将使用匹配和回归来评估患者水平的损害/益处。我们将估计 通过模拟加速抗生素使用所产生的合理的权衡范围。

Background: Each year, millions of Americans are hospitalized for suspected infection and receive antibiotics. Current guidelines strongly urge broad-spectrum antibiotics be delivered within 1 hour in the most-life- threatening cases: severe sepsis and septic shock. However, unlike other time-sensitive medical emergencies, there is no objective standard for the diagnosis of severe sepsis. Yet, several government initiatives incentivize rapid antibiotic treatment for severe sepsis. There are growing concerns that this intense focus on early antibiotics will increase overall antibiotic use, contributing to antimicrobial resistance. This R01 will measure trade-offs associated with accelerating time-to-antibiotics to inform both individual bedside decision-making and federal policy. Specific Aims: (A1) Hospital antibiotic prescribing behavior: When hospitals accelerate timing of antibiotic delivery for severe sepsis, how often is this change associated with increasing antibiotic use and broader spectrum of coverage among all-comers with potential infection? (A2) Individual harms/benefits: For an individual patient, we will quantify the: (a) risks of harm associated with very short courses of antibiotics (allergic reaction, renal or liver injury, cytopenias, C. difficile infection, isolation of new resistant bacteria, and mortality); (b) mortality benefit associated with earlier delivery of antibiotics. A3) Hospital net harms/benefits: Based on temporal changes in antibiotic prescribing (Aim 1), patient-level harms/benefits (Aim 2), and hospital prevalence of severe sepsis and septic shock, we will estimate the net benefits and harms associated with temporal changes in antibiotic prescribing with simulation. Anticipated Impact: This work will quantify the prescribing trade-offs associated with accelerating time-to- antibiotics, the individual patient-level harms of very short courses of antibiotics, and the benefit of faster antibiotic delivery, across subgroups of patients. Finally, we will quantify the net benefits and harms of accelerating time-to-antibiotics across different types of hospitals with varying sepsis prevalence and magnitude of negative externalities associated with accelerating time-to-antibiotics. Unique Features and Innovation: Using granular, patient-level data from Kaiser Permanente Northern California (KPNC) and nationwide Veterans Affairs (VA), and a novel measure of antimicrobial coverage spectrum (Spectrum Score), we will evaluate the holistic benefits and harms of faster antibiotic timing, making summary judgements about the balance of benefits straightforward and informative. Project Methods: We will examine all KNPC and VA hospitalizations (2013-2018) admitted with potential infection. We will assess hospital-specific temporal trends in antibiotic prescribing patterns using multilevel models. We will assess patient-level harms/benefit using matching and regression. We will estimate the plausible range of trade-offs that result from accelerating time-to-antibiotics with simulation.