Applying Human Factors and Mathematical Modeling Approaches to Prevent Transmission of High-Consequence Pathogens

应用人为因素和数学建模方法来防止高后果病原体的传播

• 批准号: 9075150
• 负责人: Peter J. Pronovost
• 金额: $ 219.94万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-30 至 2018-09-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9075150
• 关键词: Applying; Human; Factors; Mathematical; Modeling

 DESCRIPTION (provided by applicant): The purpose of this proposal is to translate basic, epidemiologic, and technologic discoveries into new strategies to prevent healthcare-associated transmission of Ebola and other high-consequence pathogens. Healthcare-associated transmission of high-consequence pathogens such as the Ebola virus, SARS coronavirus, MERS coronavirus, novel respiratory pathogens, multidrug resistant bacteria, and Clostridium difficile poses a significant risk to patients, families, and healthcare workers (HCWs), leading to morbidity and mortality and dramatically increased healthcare costs. Recent experience with Ebola has shown that current infection prevention strategies may be inadequate to prevent transmission of high-consequence pathogens in healthcare settings. Using our broad experience and expertise and our history of successful collaboration, we propose a multifaceted and innovative framework integrating infection prevention, human factors engineering, and mathematical modeling approaches to address knowledge gaps in current infection prevention methods and to develop new interventions to prevent the transmission of high-consequence pathogens in healthcare settings. We hypothesize that: 1) self-contamination of HCW while doffing personal protective equipment (PPE) can be prevented by elucidating risk factors for HCW self-contamination and designing effective risk mitigation strategies to prevent HCW self-contamination events, 2) pathogen transmission from environmental sources can be effectively prevented by elucidating specific risk factors in environmental service (EVS) worker training, communication, culture and processes and designing effective interventions to optimize environmental cleaning and disinfection, 3) mathematical modeling will improve understanding of how resistance mechanisms impact transmission routes of carbapenem-resistant Enterobacteriaciae (CRE) in healthcare settings and the effectiveness of contact precautions for the prevention of CRE transmission. We will apply human factors and mathematical modeling (T0) approaches to gather data on risk factors and potential failure modes that contribute to pathogen transmission during HCW PPE doffing, EVS cleaning and disinfection of the environment, and the care of patients who are colonized or infected with CRE. We will then use the identified risk factors and epidemiologic transmission data to develop (T1), implement (T2) and assess new strategies within a large tertiary care hospital and across a health system of hospitals (T3). In addition to our expertise in infection prevention surveillance, intervention trils, and antimicrobial stewardship, in this proposal we demonstrate our capacity to integrate distinct scientific disciplines and introduce novel applications of evidence-based risk mitigation strategies to expand the science of infection prevention. The findings from this proposal will inform CDC guidance for frontline HCWs by providing concise and practical, evidence-based recommendations to prevent pathogen transmission in order to reduce harm to patients and healthcare workers.

 描述（由申请人提供）：本提案的目的是将基础、流行病学和技术发现转化为新的战略，以预防埃博拉和其他高后果病原体的医疗相关传播。医疗保健相关的高后果病原体传播，如埃博拉病毒、SARS冠状病毒、MERS冠状病毒、新型呼吸道病原体、多重耐药细菌和艰难梭菌，对患者、家庭和医疗保健工作者（HCW）构成重大风险，导致 发病率和死亡率以及显著增加的医疗保健成本。最近的埃博拉经验表明，目前的感染预防策略可能不足以防止医疗机构中高后果病原体的传播。利用我们广泛的经验和专业知识以及我们成功合作的历史，我们提出了一个多方面的创新框架，将感染预防，人为因素工程和数学建模方法整合在一起，以解决当前感染预防方法中的知识空白，并开发新的干预措施，以防止高后果病原体在医疗环境中的传播。我们假设：1）通过阐明HCW自污染的风险因素和设计有效的风险缓解策略来防止HCW自污染事件，可以防止在脱下个人防护设备（PPE）时HCW的自污染，2）通过阐明环境服务（EVS）工作人员培训、沟通、3）数学建模将提高对耐药机制如何影响医疗机构中碳青霉烯类耐药肠杆菌（CRE）传播途径的理解，以及预防CRE传播的接触预防措施的有效性。我们将应用人为因素和数学建模（T0）方法来收集有关风险因素和潜在故障模式的数据，这些风险因素和潜在故障模式有助于在HCW PPE脱落，EVS清洁和环境消毒以及对被殖民或感染CRE的患者的护理期间传播病原体。然后，我们将使用确定的风险因素和流行病学传播数据，在大型三级保健医院和整个医院卫生系统（T3）内制定（T1），实施（T2）和评估新策略。除了我们在感染预防监测、干预trils和抗菌药物管理方面的专业知识外，在本提案中，我们还展示了我们整合不同科学学科的能力，并介绍了基于证据的风险缓解策略的新应用，以扩大感染预防科学。该提案的调查结果将为疾病预防控制中心对一线医护人员的指导提供信息，提供简洁实用、基于证据的建议，以预防病原体传播，以减少对患者和医护人员的伤害。