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

Published

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

Pubmed Central ID

  • 26928193

Electronic International Standard Serial Number (EISSN)

  • 1741-2811

International Standard Serial Number (ISSN)

  • 1460-4582

Digital Object Identifier (DOI)

  • 10.1177/1460458216628314

Language

  • eng