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Discrete event simulation modelling to evaluate the impact of a quality improvement initiative on patient flow in a paediatric emergency department.
McKinley, Kenneth W; Babineau, John; Roskind, Cindy G; Sonnett, Meridith; Doan, Quynh.
Afiliación
  • McKinley KW; Emergency Medicine Section of Data Analytics, Children's National, Washington, DC, USA kmckinley@childrensnational.org.
  • Babineau J; Department of Emergency Medicine, New York-Presbyterian Hospital/Columbia University Medical Center, New York, NY, USA.
  • Roskind CG; Department of Emergency Medicine, New York-Presbyterian Hospital/Columbia University Medical Center, New York, NY, USA.
  • Sonnett M; Department of Emergency Medicine, New York-Presbyterian Hospital/Columbia University Medical Center, New York, NY, USA.
  • Doan Q; Department of Pediatrics, British Columbia Children's Hospital, Vancouver, BC, Canada.
Emerg Med J ; 37(4): 193-199, 2020 Apr.
Article en En | MEDLINE | ID: mdl-31915264
ABSTRACT

OBJECTIVE:

We developed a discrete event simulation model to evaluate the impact on system flow of a quality improvement (QI) initiative that included a time-specific protocol to decrease the time to antibiotic delivery for children with cancer and central venous catheters who present to a paediatric ED with fever.

METHODS:

The model was based on prospective observations and retrospective review of ED processes during the maintenance phase of the QI initiative between January 2016 and June 2017 in a large, urban, academic children's hospital in New York City, USA. We compared waiting time for full evaluation (WT) and length of stay (LOS) between a model with and a model without the protocol. We then gradually increased the proportion of patients receiving the protocol in the model and recorded changes in WT and LOS.

RESULTS:

We validated model outputs against administrative data from 2016, with no statistically significant differences in average WT or LOS for any emergency severity index (ESI). There were no statistically significant differences in these flow metrics between the model with and the model without the protocol. By increasing the proportion of total patients receiving this protocol, from 0.2% to 1.3%, the WT increased by 2.8 min (95% CI 0.6 to 5.0) and 7.6 min (95% CI 2.0 to 13.2) for ESI 2 and ESI 3 patients, respectively. This represents a 14.0% increase in WT for ESI 3 patients.

CONCLUSIONS:

Simulation modelling facilitated the testing of system effects for a time-specific protocol implemented in a large, urban, academic paediatric ED, showing no significant impact on patient flow. The model suggests system resilience, demonstrating no detrimental effect on WT until there is a 7-fold increase in the proportion of patients receiving the protocol.
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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Simulación por Computador / Eficiencia Organizacional / Mejoramiento de la Calidad / Tiempo de Internación Tipo de estudio: Observational_studies / Prognostic_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Emerg Med J Asunto de la revista: MEDICINA DE EMERGENCIA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Simulación por Computador / Eficiencia Organizacional / Mejoramiento de la Calidad / Tiempo de Internación Tipo de estudio: Observational_studies / Prognostic_studies Límite: Humans País/Región como asunto: America do norte Idioma: En Revista: Emerg Med J Asunto de la revista: MEDICINA DE EMERGENCIA Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos