Christopher J. DeFlitch

A Systematic Review of Simulation Studies Investigating Emergency Department Overcrowding

The problem of emergency department (ED) overcrowding has reached crisis proportions in the last decade. In 2005, the National Academy of Engineering and the Institute of Medicine reported on the important role of simulation as a systems analysis tool that can have an impact on care processes at the care-team, organizational, and environmental levels. Simulation has been widely used to understand causes of ED overcrowding and to test interventions to alleviate its effects. In this paper, we present a systematic review of ED simulation literature from 1970 to 2006 from healthcare, systems engineering, operations research and computer science publication venues. The goals of this review are to highlight the contributions of these simulation studies to our understanding of ED overcrowding and to discuss how simulation can be better used as a tool to address this problem. We found that simulation studies provide important insights into ED overcrowding but they also had major limitations that must be addressed.

Improving patient flow in a hospital emergency department

Hospital emergency departments in the US are facing increasing challenges due to growth in patient demand for their services, and inability to increase capacity to match demand. We report on a new approach to patient flow in emergency departments, and a simulation model of the approach. Initial results from the model show that the approach is feasible, and a pilot study demonstrates substantial improvements in patient care.

R-CAST-MED: Applying Intelligent Agents to Support Emergency Medical Decision-Making Teams

Decision-making is a crucial aspect of emergency response during mass casualty incidents (MCIs). MCIs require rapid decisions to be taken by geographically-dispersed teams in an environment characterized by insufficient information, ineffective collaboration and inadequate resources. Despite the increasing adoption of decision support systems in healthcare, there is limited evidence of their value in large-scale disasters. We conducted focus groups with emergency medical services and emergency department personnel who revealed that one of the main challenges in emergency response during MCIs is information management. Therefore, to alleviate the issues arising from ineffective information management, we propose R-CAST-MED, an intelligent agent architecture built on Recognition-Primed Decision-making (RPD) and Shared Mental Models (SMMs). A simulation of R-CAST-MED showed that this tool enabled efficient information management by identifying relevant information, inferring missing information and sharing information with other agents, which led to effective collaboration and coordination of tasks across teams.

Information and communication tools as aids to collaborative sensemaking

Collaborative sensemaking occurs when multiple actors engage in understanding an unfamiliar, information-rich environment. We present preliminary results from a field study of the collaborative activities of healthcare providers in an emergency department. The goal of our study was to explore the nature of collaborative sensemaking and the role various information and communication tools play in the process. We describe how paper, whiteboards, and the computerized provider order entry system support common external representations to enhance collaborative sensemaking; but at the same time gaps in collaborative sensemaking occur, leading to representation shifts.

Healthcare Systems Engineering: Griffin/Healthcare Systems Engineering

The Healthcare Systems Engineering program at Johns Hopkins University provides engineers and healthcare professionals with the indepth knowledge and skills necessary to apply systems engineering principles and best practices to address today’s healthcare challenges and create healthcare of the future. Students will be well prepared to re-engineer healthcare delivery on a broad scale by using a systems approach. This approach will lead to solutions that seamlessly integrate technology into the cultural and workflow dynamics prevalent in healthcare, while holistically addressing interoperability, security/ privacy, safety, cost, performance (i.e., outcomes, etc.), and other key requirements.

Assessment of emergency department efficiency using data envelopment analysis

ABSTRACT Despite the important role of emergency department (ED) performance measurement, commonly used metrics remain disaggregated and are not standardized. The objectives of this study are to develop an aggregated performance measure that enables benchmarking EDs with respect to technical and scale efficiencies, and to investigate significant exogenous factors affecting the technical efficiency of EDs. To our best knowledge, this is the first study that examines the scale and technical efficiencies of EDs and helps to address hospital redesign/reengineering. This study formulated input-oriented data envelopment analysis (DEA) models that involve three inputs and three outputs and derived efficiency scores for individual EDs. The DEA analysis indicated that many EDs may not need to modify the size of their operations to improve efficiency. Instead, they may need to focus their efforts on re-engineering their processes to use their inputs more efficiently. The logistic regression analysis demonstrated that additional functional areas within the ED, length of stay, and percent of patients who arrive by ambulance were associated with the technical efficiency of EDs. This research is significant in that hospitals can use these models as benchmarking tools, and the findings can be a basis to redesign EDs with respect to critical hospital resources for performance improvement.