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

这个小企业创新研究（SBIR）第二阶段项目的更广泛的影响/商业潜力非常重要。急诊科和医院的次优业务决策导致效率低下，导致病人等待时间过长，救护车被转移到其他急诊科，浪费资源，病人在接受治疗前离开或不听医嘱。通过将现代分析方法（包括统计建模和系统工程方法）与医院定期收集的实时数据相连接，拟议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置决策。这种明智的决策不仅会提高医院的效率，而且会使患者更健康、更满意，同时大幅增加收入和利润。这项技术将有可能为美国大约5,000家医院增加重要价值，通常是每年数百万美元的数量级。医院和卫生系统现在已经意识到有效分析的价值，这里提出的分析平台对于任何急诊科或医院来说都是一项明显的投资，其目标是以更低的成本为患者提供最好的护理。拟议的项目有望产生一套决策支持应用程序，急诊科和医院每天都将根据这些应用程序做出决策。医院和卫生系统对信息技术的大量投资，特别是电子健康记录，为基于证据、数据驱动的决策奠定了基础。这些决策将有效地利用实时数据沿着分析方法，如统计预测和事件模拟建模。特别是，这个拟议的项目将开发软件应用程序，基于这些分析方法，并连接到实时数据源，为急诊科和医院量身定制。该项目将涉及1）解决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见解必须在正确的时间以正确的格式交付给正确的决策者，然后才能大幅提高整个医院的护理质量和效率。

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.