SBIR Phase II: Data-Driven Decision Support Services for Emergency Department Operations

小型企业创新研究(SBIR)第二阶段项目的广泛影响/商业潜力非常显著。急诊科和医院的次优业务决策导致效率低下，导致患者等待时间过长，救护车被分流到其他急诊科，浪费资源，患者要么在接受治疗前离开，要么违背医疗建议。通过将包括统计建模和系统工程方法在内的现代分析方法与医院常规收集的实时数据联系起来，拟议中的项目有望产生一个非常有价值的分析平台，帮助管理员每天做出数十项运营和人员配备决策。这种明智的决策不仅将提高医院的效率，还将导致患者更健康、更满意，同时收入和利润也将大幅增加。这项拟议中的技术将有可能为美国约5,000家医院增加显著价值，通常每年约为数百万美元。医院和卫生系统现在意识到了有效分析的价值，对于任何目标是以更低成本为患者提供最佳护理的急诊科或医院来说，这里提出的分析平台将是一项明显的投资。拟议的项目承诺产生一套决策支持应用程序，急诊科和医院将基于这些应用程序每天做出决策。医院和卫生系统对信息技术，特别是电子健康记录的大量投资，为以证据为基础、以数据为导向的决策奠定了基础。这些决策将有效地利用实时数据以及统计预测和事件模拟建模等分析方法。特别是，这一拟议项目将根据这些分析方法并链接到实时数据源，为急诊科和医院量身定做软件应用程序。该项目将涉及1)满足医院运营决策者的实时需求，2)进一步开发统计和模拟建模平台，以告知这些实时需求，特别是反映急诊科和整个医院，以及3)最终确保以及时和直观的方式向关键利益相关者提供可操作的见解。这些来自数据和复杂方法的可操作的见解必须在正确的时间和正确的格式提供给正确的决策者，但随后将有能力大幅提高整个医院的护理服务质量和效率。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase II project is very significant. Suboptimal operational decision-making in emergency departments and hospitals leads to inefficiencies that result in excessive patient wait-times, the diversion of ambulances to other emergency departments, wasted resources and patients who either leave before being treated or against medical advice. By connecting modern analytical approaches, including statistical modeling and systems engineering methods, to real-time data routinely collected by hospitals, the proposed project promises to result in a tremendously valuable analytics platform that will assist administrators in making dozens of operational and staffing decisions each day. This informed decision-making will not only improve hospital efficiency, it will lead to both healthier and more satisfied patients and simultaneous dramatic increases in revenue and profit. The technology proposed will have the potential to add significant value to the approximately 5,000 hospitals in the U.S., often on the order of millions of dollars annually. Hospitals and health systems now realize the value of effective analytics, and the analytics platform proposed here will be an obvious investment for any emergency department or hospital whose goal is to provide the best care to its patients at lower costs.The proposed project promises to yield a set of decision-support applications upon which emergency departments and hospitals will base their decisions each day. Substantial investments by hospitals and health systems on information technology, and in particular, electronic health records, have set the stage for evidence-based, data-driven decisions. These decisions will effectively leverage real-time data along with analytical methods such as statistical forecasting and event-simulation modeling. In particular, this proposed project will develop software applications, based on these analytical methods and linking to real-time data sources, tailored to emergency departments and hospitals. This project will involve 1) addressing the real-time needs of hospital operational decision-makers, 2) further developing a statistical and simulation modeling platform to inform these real-time needs, specifically reflecting emergency departments and whole hospitals, and 3) ultimately ensuring that actionable insights are delivered in a timely and intuitive manner to key stakeholders. These actionable insights that derive from the data and sophisticated methods must be delivered to the right decision-maker at the right time and in the right format, but will then have the capacity to substantially improve both the quality and efficiency of care-delivery throughout the hospital.