An ED simulation fueled by automated data collection

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Operational Performance Improvement

Bill Ferris
Senior Analyst, HSE

Tim Ward
Principal, Tefen

A challenge in simulation modeling is data collection. This is especially true in clinical settings where capturing relevant data and not being intrusive can be difficult. At Rush University Medical Center we utilized existing information systems and a sensor network to capture the data necessary for staffing and facility-sizing models.

When creating any simulation one of the most difficult steps is collecting the proper data. At Rush University Medical Center we were able to use data stored in their EDIS to obtain several years of patient movement information. Concurrently, we installed an infrared sensor network to track staff movement throughout the ED for a 6 month time period. The result is a robust database that we were able to query to determine how long patients spent in different stages of treatment, and how much staff time was required. Because of the quantity of data available, it was possible to break down patients by disease category in addition to acuity. This information was input into a MedModel simulation model that is able to determine staffing and facility requirements. Furthermore, because patient conditions are taken into account, it is easy to see the operational impact on changes in patient population.