In recent years, a growing proportion of patients flowing through inpatient hospital wards come from Emergency Departments (EDs). Because of ED overcrowding and the reduction of hospital beds, it is becoming crucial to improve the management of emergent patient flows to be admitted into inpatient wards. This study evaluates the impact and potential of introducing the so-called Bed Management function in a large city’s health district. Thanks to the collaboration with the Local Health Authority of the Liguria region, an observational analysis was conducted based on data collected over a 1-year period to develop a discrete event simulation model. The model has been utilised to evaluate several bed management strategies. Two scenarios at a tactical level, i.e. the opening of a discharge room and blocking elective arrivals, have also been simulated. The effects of such scenarios have been compared with respect to a set of performance metrics, such as waiting times, misallocated patients, trolleys in EDs, and inpatient bed occupancy rates.

Managing emergent patient flow to inpatient wards: A discrete event simulation approach

LANDA, PAOLO;SONNESSA, MICHELE;TANFANI, ELENA;TESTI, ANGELA
2015-01-01

Abstract

In recent years, a growing proportion of patients flowing through inpatient hospital wards come from Emergency Departments (EDs). Because of ED overcrowding and the reduction of hospital beds, it is becoming crucial to improve the management of emergent patient flows to be admitted into inpatient wards. This study evaluates the impact and potential of introducing the so-called Bed Management function in a large city’s health district. Thanks to the collaboration with the Local Health Authority of the Liguria region, an observational analysis was conducted based on data collected over a 1-year period to develop a discrete event simulation model. The model has been utilised to evaluate several bed management strategies. Two scenarios at a tactical level, i.e. the opening of a discharge room and blocking elective arrivals, have also been simulated. The effects of such scenarios have been compared with respect to a set of performance metrics, such as waiting times, misallocated patients, trolleys in EDs, and inpatient bed occupancy rates.
2015
9783319264691
9783319264691
File in questo prodotto:
File Dimensione Formato  
2016_Springer Book_simultech.pdf

accesso chiuso

Tipologia: Documento in versione editoriale
Dimensione 647.2 kB
Formato Adobe PDF
647.2 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/856132
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 1
social impact