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

Roundtable Analytics, Inc., Larkspur CA

Investigators

Abstract

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.