SBIR Phase II: An Interactive Graphical Application for Next-Generation Surveillance of Hospital-Acquired Infections using Whole Genome Sequencing and Advanced Analytics

这个小企业创新研究（SBIR）二期项目的更广泛的影响/商业潜力将是一个用户友好和可扩展的感染控制监测软件平台，使用先进的生物技术和数据分析来监测医院获得性感染。医院存在一个严重的临床问题，每25个就诊的人中就有1人会患上医院获得性感染。目前，医院感染控制从业人员（icp）几乎没有分析工具来识别这些感染的来源，这些感染可能是致命的，每年给医疗保健行业造成的损失估计为450亿美元。正在开发的这项创新在一个易于使用的应用程序中利用了先进的流行病学方法，使icp能够使用细菌遗传学作为监测其系统内感染传播的手段，从而消除其来源。这项SBIR II期提案的智力优势在于开发一种使用病原体全基因组测序和高级数据分析的感染控制监测软件系统。这一创新解决了为当地感染控制监测而设计的遗传分析应用程序严重缺乏的问题。医院观察到抗生素耐药感染率不断上升。这些药物价格昂贵，危及患者，而且随着医疗服务变得更加复杂和分散在多个机构中，它们变得越来越难以追踪。不幸的是，icp除了最佳卫生习惯外，几乎没有新的工具来降低其不断上升的感染率。几十年的研究表明，使用遗传分析的流行病学监测提供了强大的病原体可追溯性；然而，由于缺乏技术基础设施和分析能力，这些知识尚未转移到急需这些知识的医院。在这个二期项目中，目标是完成一个软件应用程序的开发，使icp能够在自己的办公室轻松准确地处理细菌遗传数据，并生成丰富，有意义且易于解释的关于其网络中细菌传播的报告。当感染源相互关联时，icp将得到警告，这表明需要进行更深入的调查。其结果是，目前被遗漏的感染源将被主动识别和定位。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project will be a user-friendly and scalable infection control surveillance software platform using advanced biotech and data analytics for monitoring hospital-acquired infection. There is a significant clinical problem in hospitals, where 1 in 25 people who check in will develop a hospital acquired infection. Currently, hospital infection control practitioners (ICPs) have few analytical tools to identify the source of these infections, which can be deadly and cost the health care industry an estimate of $45 billion year. The innovation under development harnesses advanced epidemiological approaches in an easy-to-use application that will enable ICPs to use bacterial genetics as a means to monitor infectious spread within their system so that their sources can be eliminated.The intellectual merit of this SBIR Phase II proposal is to develop an infection control surveillance software system using whole-genome sequencing of pathogens and advanced data analytics. The innovation addresses the critical lack of accessible genetic analysis applications designed for local infection control surveillance. Hospitals are observing ever increasing rates of antibiotic resistant infections. These are expensive, endanger patients, and are becoming harder to trace as medical care becomes more complex and spread over multiple facilities. Unfortunately, ICPs have few new tools, other than best hygiene practices, to reduce their mounting infection rates. Decades of research has revealed that epidemiological surveillance using genetic analysis provides a robust level of pathogen traceability; however, this knowledge has not been transferred into hospitals where it is critically needed, due to a lack of technical infrastructure and analytical accessibility. In this Phase II project, the goal is to complete the development of a software application that will enable ICPs to easily and accurately process bacterial genetic data in their own offices and generate rich, meaningful and easy to interpret reports concerning bacterial spread in their networks. ICPs will be warned when infection sources relate to each other, suggesting that a deeper investigation is needed. The result is that infection sources, which are currently missed, will be proactively identified and targeted.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.