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[June 11, 2014]
Simulation in healthcare [Industrial Engineer]
(Industrial Engineer Via Acquire Media NewsEdge) I had the pleasure of attending December's Winter Simulation Confer- ence in Washington, D.C. Simulation has many meanings to many people. To a simulationist or industrial engineer, simu- lation is a tool for imitating the operations of processes. Simulations model processes by using math equations that match the actual process. Often, simulation is done via software programs, such as ProModel, FlexSim, Simul8 and Simio.
The tool helps figure out how a system will behave, identifying bottlenecks and points where flow is not optimal. In health- care design, simulation can ensure the right quantity of spaces (the number of CT scanners that we need), the right location of spaces (the impact of locating trauma rooms next to the ambulance entry versus locating them next to the walk-in entrance), and the right size of spaces (the number of seats needed in this waiting area).
A pre-conference workshop reminded me of the two types of models: deter- ministic and stochastic, which brought back nightmares about a stochastics class I took in college. But I was able to ease into the stochastic side of things during the workshop as we mostly focused on discrete-event simulation, which is a dynamic, stochastic model. The workshop's overview can be summed up in the five steps in model development.
1. Conceptual: Define the goals and objectives of your model.
2. Specification: Gather data and define the algorithms.
3. Computation: Program the model.
4. Verification: Is the model I built correct? 5. Validation: Did I build the correct model? Many of us tend to focus on the compu- tation step; however, the other steps are just as important.
After the workshop, I attended the conference for two and a half days. I learned about many applications of simulation in healthcare from presenters from around the globe. One talk, "A Simulation-based Analysis on Reducing Patient Wait Time for Consultation in an Outpatient Clinic," focused on an eye clinic at a hospital in Singapore. Another talk, "Simulation as a Guide for Appointment Template Rede- sign in Endoscopy," looked at optimizing the scheduling of patients for endoscopy procedures at a large academic medical center in the United States. The French healthcare system was represented in the talk, "Ensuring the Overall Performance of a New Hospital Facility through Discrete- event Simulation." While the healthcare operational model is different in each country, the conference proved the relevance and applicability of simulation in healthcare environments. I was shocked to find that despite the varia- tions in how healthcare systems operate, we all seem to struggle with similar, if not the same, problems.
Simulation is one tool that healthcare improvement professionals use in their work. It helps us predict how a system will behave.It allows us to test scenarios without affecting the real system. Often, simulation in healthcare can facilitate consensus on what changes we want to make to achieve better results. However, simulation can be tricky if it is programmed incorrectly or the results are not interpreted correctly. Bad decisions can be made based on these errors. It is important to have someone who understands the process being simu- lated so that the computer programming accurately reflects the process.
Further, data is necessary to identify the statistical distribution that each step of the process follows. A lot of technicalities must be accounted for, and that takes time and knowledge of statistics, the process being modeled, and the simulation software. IEs are well-versed in statistics and process analyses, and that makes them perfect for trying simulation in healthcare. d It helps us predict how a system will behave.
Amanda Mewborn is an industrial engineer, registered nurse and lean black belt who works as a senior healthcare operational planner at Perkins+Will. She focuses on improving health- care efficiency, quality and experience. She can be reached at email@example.com.
(c) 2014 Institute of Industrial Engineers-Publisher
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