Martin J. Miller

Fixing the emergency department: a transformational journey with EDSIM

Hospitals today are investing time and money to expand and improve their emergency departments (ED). Using simulation to test their many improvement ideas can necessitate running numerous scenarios. Model changes such as the number of ED beds, inpatient beds and process improvements will yield an exponentially growing list of permutations in alternative ED designs. This paper uses recent project experience to describe where to begin and which steps to take to go from an As-Is ED configuration to the best to-be configuration.

Using RFID technologies to capture simulation data in a hospital emergency department

Simulation professionals understand the importance of accurate data for model validation. Traditional sources of simulation data come from information technology systems, manual records from staff, observations, and estimates by subject matter experts. This paper discusses how radio frequency identification (RFID) technologies were used on a recent consulting engagement at a hospital. Data collected through RFID can validate or replace activity duration estimates from traditional sources. However, the accuracy and cost effectiveness of RFID is not guaranteed. A sound methodology was developed, which included rigorous planning and testing of hardware, processes and data analysis. Hardware vendors needed to understand what the simulation required so they could properly setup equipment and software. Also, ED staff needed to understand the purpose of this data collection to avoid anxiety about personnel evaluations. Finally, efficient and reliable issue and collection of patient tags was crucial to the success of this effort

Analyzing incentives and scheduling in a major metropolitan hospital operating room through simulation

This paper discusses the application of simulation to analyze the value proposition and construction of an incentive program in an operating room (OR) environment. The model was further used to evaluate operational changes including scheduling processes within the OR and utilization rates in areas such as post anesthesia care unit (PACU) and the ambulatory surgery department (ASD). Lessons learned are presented on developing multiple simulation models from one application as well as issues regarding model transition to a client.

Lean sigma and simulation, so what's the correlation?: V2

This paper explores the fundamental relationships between Lean Sigma and simulation. A basic overview of Lean Sigma includes: 1) Lean Sigma philosophy, 2) basic tools, 3) theory of variation, 4) SPC, 5) process capability, 6) Lean Sigma infrastructure, and 7) DMAIC and DFSS processes. Simulation is applied to the appropriate areas of the overview. Improvement in the robustness of the Lean Sigma methodology is discussed and the strengths of simulation is presented as capable and preferable enhancements to the Lean Sigma processes. Quotes from Lean Sigma and industry leaders are presented. Simulation is presented as an innovation tool enhancing the Lean Sigma DMAIC and DFSS processes.

Discrete event simulation: optimizing patient flow and redesign in a replacement facility

This study observed the challenges of taking an existing facility¿s inpatient volumes and procedures and projecting them into a replacement facility with differently sized units, overall scale, and layout. Discrete event simulation is used to examine the impacts of this transition as well as the operational impacts of capacity changes, process redesign, and process improvements. This effort to optimize patient flow throughout the inpatient units is done while modeling and observing the impacts on other interdependent parts of the hospital such as the Emergency Department, and Operating Rooms.

Merging six emergency departments into one: a simulation approach

Simulation of existing systems can reinforce a Subject Matter Experts gut feelings. However, it is more difficult to develop intuition for proposed systems, particularly when considering the consolidation of multiple systems. This paper discusses the use of simulation to determine the operational ramifications of combining six Emergency Departments into one of the largest in the country. Each of these six existing Emergency Departments serve a different type of patient population and each maintains their own independent processes. This hospital required all Emergency Departments to effectively function using the same floor space, processes and ancillary services, such as testing facilities, waiting rooms, and registration. Healthcare planners need to understand the ramifications of sharing resources among multiple departments and the operational impact of high volume systems. This project explored these challenges to find key bottlenecks and mitigation strategies using simulation.

Estimating patient surge impact on boarding time in several regional emergency departments

The sudden or prolonged increase in patient arrivals to hospital Emergency Departments can cause overcrowding which adversely affects patient care. Healthcare leadership must anticipate and prepare for patient surge before it happens. They need to understand how much overcrowding will occur with each incremental increase in patient volume. This paper describes how simulation was used to determine the impact of various patient surge levels on three regional Emergency Departments. This paper also describes the impact of potential action items which the hospitals can take to mitigate their overcrowding.

Electronic workflow for transaction-based work cells in a financial services firm

In determining an electronic workflow system, a financial services firm utilized simulation to determine the necessary capital expenditure. Analysis included batching options, service level agreements and full time equivalent allocations and schedules. This information was then processed in transaction-based work cells which were redesigned using simulation. This paper discusses the approach, benefits and lessons learned while developing multiple simulation models for an electronic documentation system.

Allocating outpatient clinic services using simulation and linear programming

A large number of operational tools exist to help researchers determine business solutions for their customers. Each individual tool serves a distinct purpose for specific types of problems. Deciding which tool to use requires knowledge and experience. Sometimes, the researcher should integrate several tools because each tool may get too complex or not form a complete solution. This paper discusses how simulation, linear programming and spreadsheet analysis were integrated to help a new hospital determine ideal space assignments, schedule configurations and throughput targets for numerous clinic services.

The application of simulation methodology in a hospital's six sigma project

Simulation was recently utilized as the key component of a Six Sigma project at a major hospital in the southeastern United States. The project team used various statistical analysis tools to assess current process performance and measure improvements with process changes. However, simulation provided the best insight into which process changes had the best opportunity to succeed and which would yield little value. This paper briefly discusses the methodology of this project and how simulation provided a better quality solution.