A discrete event simulation tool to support and predict hospital and clinic staffing.
Journal Article (Journal Article)
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.
Full Text
Duke Authors
Cited Authors
- DeRienzo, CM; Shaw, RJ; Meanor, P; Lada, E; Ferranti, J; Tanaka, D
Published Date
- June 2017
Published In
Volume / Issue
- 23 / 2
Start / End Page
- 124 - 133
PubMed ID
- 26928193
Electronic International Standard Serial Number (EISSN)
- 1741-2811
Digital Object Identifier (DOI)
- 10.1177/1460458216628314
Language
- eng
Conference Location
- England