Simulation FAQs

I’ve given two presentations on simulations in the last few months, one of which is included here: the Lean Healthcare Academic Conference at Stanford: Simulate to Innovate. And I’m preparing to talk about simulation at the Healthcare Systems Process Improvement Conference 2026 in February in Atlanta, GA. To support these presentations, I’m posting some FAQs (Frequently Asked Questions) here, and I’ll update them as I continue to present on this topic.

1.        Q: Why use simulation instead of spreadsheets or simple analysis?

1.        A:  Simulation captures variability, randomness, complex interactions, queues, and real-time dynamics that simple analytical methods cannot.

2.        Q:  What types of simulation exist?

2.        A:  Common types include Discrete-Event Simulation (DES), Agent-Based Modeling (ABM), System Dynamics (SD), and Monte Carlo simulation.

3.  Q: What kind of background do I need to understand simulation? Do I need to be a programmer or a statistician?

3. A:  That's a common concern, and it's a great question. If you can understand basic processes, read a process map/flowchart, and have some comfort with numbers, you can learn and understand basic simulation. We wrote our book, 'Simulation Solutions', specifically for healthcare professionals, not just programmers or statisticians. While some familiarity with data helps, the book focuses on the concepts and practical application of simulation. We demystify the technical jargon and provide clear, step-by-step guidance. You don't need to be a coding wizard to get immense value from it. We're teaching you how to think like a simulation expert, not necessarily how to build the most complex code.  Some core backgrounds will help with any Simulation. You should have or develop a basic competency in: algebra, probability, statistics, process mapping (flow charting), understanding cause-and-effect situations, and feedback loops. Many software programs today are drag-and-drop.

4. Q: There are many simulation software packages out there. Do you recommend a specific one, and will I need to buy expensive software?

4. A: An excellent point. We deliberately don't focus on one specific software package. The principles and methodologies we teach are universal and apply to virtually any simulation tool, from basic spreadsheets to more advanced dedicated software. In Simulation Solutions, we guide you on how to choose the right tool for your specific project and budget, rather than forcing you to find a particular solution. Many open-source or academic versions are available to get started, and our book's value is in methodology, not the tool itself. Some of the popular software tools today include:

·      FlexSim (which has a healthcare model component)

·      AnyLogic

·      Arena

·      Simio

·      Simul8

·      ProModel (MedModel is the healthcare component)

5. Q: How do I convince my organization to invest time and resources into simulation modeling, especially if they're focused on quick wins?

5. A:  This is the million-dollar question, and it's why Chapter 3 in Simulation Solutions, the focus on Organizational Change Management, is so critical. In the book, we provide frameworks for building a compelling business case, demonstrating ROI, and engaging key stakeholders early and often. It's about showing them that, while it might not be an 'instant fix,' simulation provides sustainable, data-backed solutions that prevent costly mistakes and yield much larger, long-term gains than any quick win could offer. We equip you with the arguments and strategies to get that buy-in.

6. Q: Can I really use this simulation to improve patient flow in a busy emergency department, which is inherently chaotic?

6. A:  Absolutely. In fact, chaotic environments like emergency departments are where simulation shines the brightest! Traditional methods struggle with that level of variability and interconnectedness. You will need to accurately represent randomness, patient arrivals, resource availability, and complex pathways within your model. Simulation allows you to test different staffing levels, triage protocols, and physical layouts to see their impact on wait times and throughput before making disruptive changes in the real world. We even include examples that tackle these very challenges.

7. Q: What if my data isn't perfect? Can I still build a useful model?

7. A:  Perfect data is a myth in healthcare, right? We completely understand that challenge. In our book and in numerous other articles, we and others address how to work with imperfect data, identify critical data gaps, and use reasonable assumptions where necessary. The main elements you’ll need are enough data to understand process steps, task times (averages and variability), arrival rates, resource availability, capacity constraints, and process flows. We also emphasize the importance of 'Verifying, Validating, and Accrediting' your model – a process that ensures your model is a credible representation of reality, even with real-world data limitations. You'll learn how to build models that are 'good enough' to provide actionable insights, not just theoretically perfect ones.

8. Q:  What’s the difference between a model and a simulation?

8.  A:   A model represents the system; simulation is the execution of the model over time to observe behavior.