A discrete event simulation tool to support and predict hospital and clinic staffing

Author:

DeRienzo Christopher M12,Shaw Ryan J3,Meanor Phillip,Lada Emily4,Ferranti Jeffrey25,Tanaka David2

Affiliation:

1. Mission Health System, USA

2. Duke University Hospital, USA

3. Duke University School of Nursing, USA

4. SAS, USA

5. Duke Health Technology Solutions, USA

Abstract

We demonstrate how to develop a simulation tool to help healthcare managers and administrators predict and plan for staffing needs in a hospital neonatal intensive care unit using administrative data. We developed a discrete event simulation model of nursing staff needed in a neonatal intensive care unit and then validated the model against historical data. The process flow was translated into a discrete event simulation model. Results demonstrated that the model can be used to give a respectable estimate of annual admissions, transfers, and deaths based upon two different staffing levels. The discrete event simulation tool model can provide healthcare managers and administrators with (1) a valid method of modeling patient mix, patient acuity, staffing needs, and costs in the present state and (2) a forecast of how changes in a unit’s staffing, referral patterns, or patient mix would affect a unit in a future state.

Publisher

SAGE Publications

Subject

Health Informatics

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