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Analytical Modeling

Most major decisions in planning rely on judgment. Analytical tools can help focus that judgment on the most significant decisions and provide a method for estimating the implications of planning decisions on space needs and operational performance.

Over the past twenty years, FZA has pioneered the application of simulation modeling in health care facilities planning. Computer simulation tools provide a mechanism to understand interrelated space, staffing and resource decisions. It also provides a tool to replicate the variations in demand and use of space. Emergency service arrivals, treatment mix, and room use times can be modeled to estimate the need for patient care spaces. Other common applications include surgery suites, intensive care units, and obstetrical services.

 

 
Simulation Modeling  

Computer simulation modeling has evolved over the past twenty years into a powerful tool for understanding operational issues in health care delivery and the relationship between operational performance and building design. As pressures to achieve efficiencies in operation continue decisions will increasingly focus on understanding both "first" dollar and life cycle costs associated with capital plans. Identification of the space necessary to meet the anticipated demand and to implement new organizational plans on staff efficiency are the type of questions which must be addressed in the planning.

A key characteristic of simulation modeling is the ability to incorporate the behavior of key system elements into a computer "mock-up" of the area under investigation. In an emergency room, for example, the arrival of patients into the ER, their diagnoses, use of diagnostic services and length of stay in the facility vary significantly. To plan based on the "average" patient can lead to erroneous estimates of space requirements and staffing needs. Simulation models can take the statistical patterns for arrivals, length of stay, and other variables and incorporate them into the model of an existing or proposed service. This allows the decision makers to have detailed estimates of the performance of a service during peak periods of demand and other time periods. Room and staff utilization can be estimated along with information regarding queues that may develop for resources and information regarding waiting room capacity.

The development and implementation of a simulation model typically moves through three phases:

    • Model definition and data collection
    • Model validation
    • Simulation of proposed plans and outcome analysis

Our typical process is to work with clients to identify key issues and goals of the modeling. Once the outcome goals are identified, we will design a plan to collect required data. It is not uncommon to require some prospective time sampling of activities in the service that are not maintained in existing records and databases. Collection of this data is usually undertaken by staff from the client. We will frequently participate in limited observations to become familiar with the operations of the service and to help in the analysis of the results. Based on this information we design and implement a model tailored to the specific characteristics of the hospital's service.

Model validation is a cross-check to assure that the logic and data used in the model can replicate existing conditions. Once we are comfortable that the model is working correctly the final stage of analysis is initiated.

Simulations of all proposed organizational and workload options are run to estimate the behavior of the proposed system. Outputs from these models are analyzed and presented in graphic and tabular form, along with specific recommendations.

We have recently started using a new simulation package designed specifically for medical applications. MedModelŠ , developed by ProModel Corporation, allows the testing of both operational and facilities attributes through a powerful animation component. We can, for example, take a proposed plan drawn in AutoCAD and, based on anticipated workload patterns and operational policies, animate the use of the space along with providing estimated performance statistics. The animation characteristics provide a valuable tool to communicate the model logic to staff and administration, along with checking the circulation flow of the proposed design.