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Health Informatics J. 2017 Jun;23(2):124-133. doi: 10.1177/1460458216628314. Epub 2016 Feb 29.

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

Author information

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.

KEYWORDS:

decision-support systems; forecasting; management; simulation tool

PMID:
26928193
DOI:
10.1177/1460458216628314
[Indexed for MEDLINE]

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