Wouldn’t You Like to Prove that Your New Design Will Improve Productivity And Efficiency Before You Build It?

blog_prove before you build

July 10, 2014  |  Kristyna Culp, MBA

Many healthcare providers ask these common questions:

      • How many treatment rooms do I need in my Emergency Department?
      • How many waiting spaces do I need in my Outpatient Imaging Center?
      • How many Technicians do I need in my Urgent Care?
      • How many EKG machines do I need in my Surgery Center?
      • How many medication rooms do I need in the Med/Surg unit?

Many available benchmarks can help answer these questions, but may not fit your specific patient demographics, staffing models, or operational processes. There is danger in not knowing for certain that a proposed solution is the right solution: having too much or not enough of anything is unnecessarily burdensome in a capitally constrained environment.

      • Having too much space results in increased construction costs.
      • Not having enough space, staff, or equipment transfers the burden to staff, who must work inefficiently to compensate for a suboptimal workplace, resulting in increased staffing and operational costs.

Nearly every problem in healthcare is complicated and expensive, and few can afford unnecessary expenditures in either category.

How should providers determine a rightsized solution that will meet their needs for years to come? Computer simulation models assimilate several variables to model pertinent scenarios, and determine efficient operational models and the right size for your environment, even if a physical design is not part of the solution (or budget).

You may have heard about simulation modeling before: that it takes too long, is too complicated, too expensive, and excessively detailed. However, when the cost of one simulation model is a small fraction of the cost to build an unnecessary treatment room, how can you afford to be uncertain as to whether your design solution is correct? We posit that robust simulation models can generate results quickly.

A good, thorough simulation model can:

      • Quantify the amount of staff needed by type and by hour of the day relative to various operational models and physical designs. This approach can save thousands of annual operational dollars.
      • Test equipment utilization and location and provide the most efficient use and volume needed to support that equipment. Excess or insufficient equipment is costly.
      • Ensure that you have rightsized your facility relative to projections, staffing models, operational models and proposed physical designs or physical design constraints.
      • Quantify the changes you need to make in your current environment to maximize the space your have.
      • Allow you to test various projection scenarios and align the most efficient staffing model, operational flow and physical capacity needed to meet whatever budget goals you have. Modeling brings all of the variables together.

As unusual as it may sound in today’s environment, there is a potential to overbuild. Often it will not be obvious – staff and the process will fill up any space allotted – but through analysis it is possible to determine appropriate utilization. As an example: if you have an extra OR that is never utilized, how will you re-use that space? Storage? That’s a very expensive closet.

Computer simulation models can address all these issues and the interconnections within the whole system. Simulation models create a basis for understanding complex systems and allows for objective testing and comparison of scenarios.

 ABOUT THE AUTHOR    Kristyna Culp MBA
blog_Kristyna
Kristyna creates workflow mapping and computer simulation model frameworks to validate, test, and quantify various scenarios to help clients make informed decisions about both operational and physical design improvements.

(Image Source: Flickr)

Share

Share

Leave a Comment