INSPIRE (INtelligent Stewardship Prompts to Improve Real-time Empiric Antibiotic Selection for Patients): The INSPIRE-ASP Trial for Intra-Abdominal and Skin and Soft Tissue Infections

摘要 INSPIRE-ASP试验(智能管理)提示改进实时经验性抗生素 患者选择)用于腹部、皮肤和软组织感染 INSPIRE-ASP试验(智能管理)提示改进实时经验性抗生素 腹部、皮肤和软组织感染的患者选择)是一项整群随机试验，以 改善腹部感染或非危重住院患者的合理抗生素处方 皮肤和软组织感染。目前，超过一半的非危重患者患有这些感染之一 当不到5%的病原体具有抗药性时，接受广谱抗生素治疗。的目标是 这项试验是为了建议医生开出标准与超广谱经验性抗生素。 一种算法，用于估计每个患者感染抗生素耐药的个性化概率。这 个性化概率基于电子健康记录中常规收集的患者信息 以及腹部或皮肤和软组织感染中耐药微生物的局部流行。 这项试验将比较以医院为基础的抗生素管理计划下的常规护理与 使用预测算法以及审计和反馈来减少不必要的经验的增强计划 开出超广谱抗生素的处方。在我们的第一个目标中，我们将开发特定疾病的预测 腹部感染以及皮肤和软组织感染的算法。在我们的第二个目标中，这一预测 算法将集成到计算机化的提供者订单录入(CPOE)系统中，以提示医生 当选择的抗生素与该抗生素的估计需求不一致时。医生将被提示 在耐药感染风险较低的情况下使用标准谱抗生素。60家医院将 随机接受常规护理或CPOE即时干预加反馈。这项为期18个月的研究将 评估约53,000名腹部感染患者和约37,000名皮肤和软组织感染患者。 该试验将评估实时风险计算器加上审计和反馈的能力，以降低 不必要的广谱抗生素，同时保持良好的临床结果，以长度衡量- 留下来，转到重症监护室。这些方法将很容易地适用于其他电子产品 健康记录处方系统。

Abstract The INSPIRE-ASP Trial (INtelligent Stewardship Prompts to Improve Real-time Empiric Antibiotic Selection for Patients) for Abdominal and Skin and Soft Tissue Infections The INSPIRE-ASP Trial (INtelligent Stewardship Prompts to Improve Real-time Empiric Antibiotic Selection for Patients) for Abdominal and Skin and Soft Tissue Infections is a cluster-randomized trial to improve judicious antibiotic prescribing for non-critically ill hospitalized patients with abdominal infections or skin and soft tissue infections. Currently, over half of non-critically ill patients with one of these infections receive extended-spectrum antibiotics when less than 5% have an antibiotic-resistant pathogen. The goal of this trial is to advise physicians to prescribe standard- vs extended spectrum empiric antibiotics based on an algorithm that estimates each patient’s personalized probability of having an antibiotic-resistant infection. This personalized probability is based upon routinely-collected patient information in the electronic health record and local prevalence of resistant organisms in abdominal or skin and soft tissue infections. This trial will compare routine care under hospital-based antibiotic stewardship programs to the enhanced program using the predictive algorithm plus audit and feedback to reduce unnecessary empiric prescribing of extended-spectrum antibiotics. In our first aim, we will develop disease-specific prediction algorithms for abdominal infections and for skin and soft tissue infections. In our second aim, this predictive algorithm will be integrated into the computerized provider order entry (CPOE) system to prompt physicians when selected antibiotics are discordant with the estimated need for that antibiotic. Physicians will be prompted to use standard-spectrum antibiotics when the risk of an antibiotic-resistant infection is low. Sixty hospitals will be randomized to either routine care or the CPOE prompt intervention plus feedback. This 18-month study will evaluate ~53,000 patients with abdominal infections and ~37,000 patients with skin and soft tissue infections. This trial will evaluate the ability of a real-time risk calculator plus audit and feedback to reduce unnecessary extended-spectrum antibiotics while maintaining good clinical outcomes as measured by length- of-stay and transfer to an intensive care unit. These methods will be readily applicable to other electronic health record prescribing systems.