Simulation Modeling to Right-Size a Strategic Plan

Simulation Modeling to Right-Size a Strategic Plan

A case study on simulating real-world processes in a virtual environment to assess outcomes

The Challenge

A regional hospital in a mountain community in Colorado was seeking a way to validate the recommendations of their facility master plan to ensure that they were correctly planning for capital investments over the next ten years. Given the extent of the financial commitments and the far-reaching implications of the plan, they wanted to make sure that they were properly allocating their resources.

The Process

The Boulder Associates team decided that the best way to validate the master plan was to use process modeling and digital simulation. Simulation modeling involves using models run on discrete-event modeling software that can simulate real world processes in a virtual environment. The software can quickly model countless different scenarios over multiple cycles and project outcomes. The ability to cycle through hundreds, if not thousands, of cases in a short amount of time allows the team to test and vet multiple scenarios under historical data as well as test future facility planning.
The starting point for developing a simulation model is always to obtain good data to establish a baseline. To that end, the team first had to document the existing space program to establish an understanding of the facility and the potential impact of regulatory changes to each functional area. The team then gathered national benchmark data to establish how the hospital ranked in their peer group.

Existing operational process flow was documented through careful on-site observations. This exercise captured between ten and 30 direct observations for each process step across seven departments. Historical data was used to understand patient arrival patterns by patient type.

A FlexSim model was created using the above information to generate a functional model that replicated the current operational performance of each department. The accuracy of this model was vetted by leadership and staff and certified as accurate.
Once the base model was complete, historical and industry-standard growth data was used to project anticipated 2026 patient volume. Simulations were then run for 2026 so each department could understand how many resources were needed to perform at the top quartile. For example, the scenarios tested the number of OR rooms, pre/post op beds required, and how many registration stations were needed. This analysis was done at each hour of the day for each month of the year. This in-depth analysis allowed for a clearer understanding of demand patterns throughout the year. This was critical in order to demonstrate what processes truly impact the size of each department. The outcome of the analysis provided projections for 2026 departmental sizes, against which the team could compare the recommendations of the master plan.

In addition, for central registration, sports therapy, and surgery, the team ran multiple scenarios for each to test the impact of shifts in staffing, acuity, and bed counts. The team was able to identify the ideal scenario and required space program for the departments if the hospital adopted specific improvements. For example, in the ED simulation, the team ran nine scenarios and recommended a program calling for eight treatment rooms, as it resulted in the lowest length of stay, and allowed for operational ratios of 1:4 RN to PT and 1:8 physician to PT.

The Results

The team then created two space programs for 2026. The first was based on the operations team implementing process improvements and the second was based on no improvements. The most important discovery was that the overall master facility plan had the correct overall square footage, but that the allocation or distribution of square footage needed to be adjusted between departments. As a result, revisions to the master plan were made to better align facility priorities and direction.