CASE STUDY
CLIENT: Mid-Atlantic Regional Community Emergency Department
Testing variations of a newly designed process before implementation uncovers potential inefficiencies. Among the critical factors identified for rapid study was the need to right-size the building program to avoid constructing superfluous square footage. An optimized program was achieved by developing a patient flow that incorporates universal resources that could flex as demand fluctuates during the day.
SERVICE: Transformation
EXECUTIVE SUMMARY
METHOD: Process Design
When given the opportunity to design a greenfield hospital, our client knew they wanted to do it correctly. Their desire to improve applied to the physical space and the processes performed within. Using process analysis and design, we engaged a crossfunctional team from the emergency department (ED) as they explored the impact of
Challenge
multiple solutions.
Explore different process designs to minimize the emergency department’s waiting time and incorrect resource utilization. Determine potential benefits of universal resources.
We began by observing current ED operations, exposing us to the process and revealing potential areas for improvement. Using process analysis, we worked with the team to map the current process. This mapping exercise allowed the team to see where reality deviated from expectations, and how their traditional triage model impacted patient waiting times.
Solution
As the clinical team developed their desired future state, they began to realize how
Using 15 months of patient data, Array built multiple variations of a discrete event simulation model to show resource utilization and waiting times for different patient types. The simulation results helped emergency department physicians, who were concerned with the ability to offer a specialized pediatric experience, see the benefits of operating under a universal model.
PROJECT HIGHLIGHTS
8
different variables could affect waiting times for varied patient types. Many questions surfaced, including the effects of providing dedicated pediatric care. Our Healthcare Systems Engineer developed a simulation model to test the impact of each potential patient flow and demonstrate the effect of varying resource allocation strategies. Ultimately, the team chose a hybrid model that combined a specialized pediatric experience with universal flex beds. The new process includes quick triage to help minimize patient waiting and improve the delivery of care.
PATIENT FLOW VARIATIONS TESTED
15
mths
PATIENT DATA DRIVING SIMULATION MODEL
18
%
PATIENTS ARRIVE 9A-12P