Infection Control in Home Care and Predictive Risk Modeling

项目总结 家庭医疗保健(HHC)是美国增长最快的医疗保健部门，在 在急性后护理中的作用。2011年，超过470万名患者接受了HHC，超过一半的患者住院 就在HHC入院前。感染在家庭护理中很普遍；在之前由NIH资助的研究中，我们 发现在HHC患者住院的前五个原因中，有三个与感染有关。在……里面 事实上，感染控制被联合委员会列为其国家HHC患者安全目标之一。 这表明，在国家努力实现以下目标的过程中，重点关注HHC的感染控制和预防具有重要意义 减少再次住院治疗。实施任何感染控制干预措施之前的关键步骤包括 识别潜在的感染高危患者，并描述当前的感染控制 在HHC实习。临床决策往往受到缺乏对复杂性的系统评估的限制。 患者及其环境的需求；特别是在HHC环境中，对工作人员感染知之甚少 控制做法以及如何识别高危患者。 为了应对这些挑战，本项目的目标是：1)开发和测试可预测的风险模型 识别HHC环境中感染风险较高的患者，以及2)评估当前的感染控制做法 并探讨如何将预测性风险建模应用于HHC环境中的临床实践。 拟议的项目将在纽约访问护士服务(VNSNY)进行，该服务是纽约最大的 美国非盈利机构HHC。对于AIM 1，将在70%的样本中开发预测性风险模型 然后在剩余30%的样本中进行验证。预测性风险模型决策也将是 验证了HHC感染控制专家的临床判断。对于目标2，混合方法包括 观察、调查、半结构访谈和焦点小组将被用来提供全面的 了解目前的感染控制做法和潜在的障碍。我们的研究团队有大量的 在护理、决策分析、建模、流行病学、混合方法、传染病和 感染控制和访问哥伦比亚大学医学中心和 因此，位于VNSNY的家庭护理政策和研究中心是进行这项研究的理想人选。 研究结果是迈向未来发展有效风险模型的关键的第一步。 HHC环境中的感染控制干预。

PROJECT SUMMARY Home health care (HHC), the most rapidly growing health care sector in the U.S., plays a significant role in post-acute care. Over 4.7 million patients received HHC in 2011, and over half had an inpatient stay immediately before HHC admission. Infection is prevalent in home care; in previous NIH-funded work, we found that three of the top five reasons for hospitalization among HHC patients were related to infections. In fact, infection control was listed by The Joint Commission as one of its national patient safety goals for HHC. This indicates the importance of focusing on infection control and prevention in HHC in national efforts to reduce re-hospitalization. Critical steps before implementation of any infection control intervention include identifying patients who are potentially at high risk for infections, and characterizing current infection control practices in HHC. Clinical decision making is often limited by a lack of systematic assessment of the complex needs of patients and their environments; specifically in the HHC setting, little is known about staff infection control practices and how high risk patients are identified. To address these challenges, the aims of this project are to 1) develop and test a predictive risk model to identify patients at high risk of infection in HHC setting, and 2) assess current infection control practices in the HHC setting and explore how predictive risk modeling can be utilized in clinical practice in HHC setting. The proposed project will be conducted in the Visiting Nurse Service of New York (VNSNY), the largest not-for-profit HHC agency in the U.S. For Aim 1, a predictive risk model will be developed in 70% of the sample and then validated in the remaining 30% of the sample. The predictive risk model decision will also be validated with HHC infection control specialists’ clinical judgment. For Aim 2, mixed methods including observation, survey, semi-structured interviews and focus groups will be used to provide a comprehensive understanding of current infection control practices and potential barriers. Our research team has substantial expertise in nursing, decision analysis, modeling, epidemiology, mixed methods, infectious disease, and infection control and access to the rich statistical resources from Columbia University Medical Center and the Center for Home Care Policy and Research in the VNSNY, therefore is ideally qualified to conduct this study. The study findings are the critical first step toward future development of an efficient risk model guided infection control intervention in the HHC setting.