Electronic Surveillance for Hospital-Onset Sepsis to Expand Detection of Serious Healthcare-Associated Infections

对院内败血症进行电子监控，以扩大对严重医疗保健相关感染的检测

• 批准号: 10774471
• 负责人: Chanu Rhee
• 金额: $ 49.55万
• 依托单位: HARVARD PILGRIM HEALTH CARE, INC.
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-30 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10774471
• 关键词: Electronic; Surveillance; Hospital; Onset; Sepsis

PROJECT ABSTRACT Healthcare-associated infections (HAIs) are a leading cause of preventable harm in U.S. hospitals. Hospitals are therefore required to report selected HAIs, including central line-associated bloodstream infections, catheter-associated urinary tract infections, colon and abdominal hysterectomy surgical site infections, methicillin-resistant Staphylococcus aureus bacteremia, and Clostridioides difficile infections, to the Centers for Medicare & Medicaid Services (CMS) via CDC’s National Healthcare Safety Network. These data are used to benchmark hospitals and to inform CMS’s pay-for performance programs. In many cases, however, conducting surveillance for HAIs is complicated, resource intensive, and prone to high levels of interobserver variability. Furthermore, many of the most common and morbid HAIs, such as hospital-acquired pneumonia and most non-line associated bloodstream infections, are not routinely tracked or reported and are therefore largely neglected by hospitals. Our underlying hypothesis is that electronic surveillance for hospital-onset sepsis could provide a more complete, efficient, and objective method to identify a fuller array of the most serious HAIs compared to current surveillance methods. In particular, CDC’s hospital-onset Adult Sepsis Event definition uses routine electronic clinical data to identify patients with concurrent clinical indicators of presumed serious infections (blood culture orders and antibiotic treatment) and concurrent organ dysfunction (initiation of vasopressors or mechanical ventilation or significant changes in laboratory values). Preliminary data suggest that CDC’s hospital-onset sepsis surveillance definition may identify many more HAIs than current CMS reportable metrics and that hospital-onset sepsis is associated with very high mortality rates even when reportable HAIs are absent. Before hospitals and policymakers consider routinely tracking hospital-onset sepsis, however, data from diverse settings are needed to understand its incidence and variation across hospitals, its impact on long-term outcomes, and the specific infections leading to sepsis. This proposal will address these gaps through the following Specific Aims: 1) Characterize the incidence, in-hospital mortality, and hospital-level variation for hospital-onset sepsis versus currently reportable HAIs, 2) Determine the impact of hospital-onset sepsis versus reportable HAIs on patients’ long-term outcomes, and 3) Develop electronic algorithms using clinical and administrative data to automatically identify the types of infections precipitating hospital-onset sepsis. This work will be conducted using detailed clinical data from 145 HCA Healthcare hospitals that collectively care for more than 1.7 million inpatients per year (approximately 5% of U.S. acute care hospitalizations). In Aim 2, we will also link HCA data to CMS claims data to accurately capture post- discharge outcomes for Medicare beneficiaries. This proposal directly addresses the goals of AHRQ and its HAI Prevention Portfolio by providing the foundation for a new HAI surveillance paradigm that will help identify new targets for prevention and quality improvement and thereby help catalyze better outcomes for patients.

项目摘要 医疗相关感染（HAI）是美国医院可预防伤害的主要原因。医院 因此，需要报告选定的HAI，包括中心静脉导管相关血流感染， 导管相关尿路感染，结肠和腹式子宫切除术手术部位感染， 耐甲氧西林金黄色葡萄球菌菌血症和艰难梭菌感染，向中心 通过CDC的国家医疗保健安全网络提供医疗保险和医疗补助服务（CMS）。这些数据用于 基准医院，并告知CMS的薪酬绩效计划。在许多情况下， HAI的监测是复杂的、资源密集的，并且易于发生高水平的观察者间变异。 此外，许多最常见和病态的HAI，如医院获得性肺炎和大多数HAI， 非管路相关的血流感染，没有常规跟踪或报告，因此在很大程度上 被医院忽视。我们的基本假设是，电子监测医院发病败血症， 可以提供一个更完整，更有效，更客观的方法来确定一个更全面的最严重的 与目前的监测方法相比，HAI。特别是，CDC的医院发病成人败血症事件 定义使用常规电子临床数据来识别具有推定并发临床指标的患者 严重感染（血培养医嘱和抗生素治疗）和并发器官功能障碍（开始 血管加压药或机械通气或实验室值的显著变化）。初步数据表明 CDC的医院感染败血症监测定义可能比目前的CMS识别更多的HAI 报告的指标，医院发生的脓毒症与非常高的死亡率相关，即使当 不存在应报告的HAI。在医院和政策制定者考虑定期跟踪医院发病之前， 然而，需要来自不同环境的数据来了解脓毒症的发病率和变化。 医院，其对长期结果的影响，以及导致败血症的特定感染。这项建议会 通过以下具体目标解决这些差距：1）描述发病率，住院死亡率， 和医院水平的变化，医院发作的脓毒症与目前可报告的HAI，2）确定影响 医院发生的脓毒症与可报告的HAI对患者长期结局的影响，以及3）开发电子 使用临床和管理数据自动识别感染类型的算法 医院感染败血症这项工作将使用来自145 HCA Healthcare的详细临床数据进行 医院每年总共照顾超过170万住院病人（约占美国急性 护理住院）。在Aim 2中，我们还将把HCA数据与CMS索赔数据联系起来，以准确地捕捉 医疗保险受益人的出院结果。这一建议直接涉及到人权咨委会的目标， HAI预防组合，为新的HAI监测模式提供基础， 预防和质量改进的新目标，从而有助于促进患者获得更好的结果。