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Decreased length of stay after addition of healthcare provider in emergency department triage: a comparison between computer-simulated and real-world interventions
OBJECTIVE: (1) To determine the effects of adding a provider in triage on average length of stay (LOS) and proportion of patients with >6 h LOS. (2) To assess the accuracy of computer simulation in predicting the magnitude of such effects on these metrics. METHODS: A group-level quasi-experimenta...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BMJ Group
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3582047/ https://www.ncbi.nlm.nih.gov/pubmed/22398851 http://dx.doi.org/10.1136/emermed-2012-201113 |
Sumario: | OBJECTIVE: (1) To determine the effects of adding a provider in triage on average length of stay (LOS) and proportion of patients with >6 h LOS. (2) To assess the accuracy of computer simulation in predicting the magnitude of such effects on these metrics. METHODS: A group-level quasi-experimental trial comparing the St. Louis Veterans Affairs Medical Center emergency department (1) before intervention, (2) after institution of provider in triage, and discrete event simulation (DES) models of similar (3) ‘before’ and (4) ‘after’ conditions. The outcome measures were daily mean LOS and percentage of patients with LOS >6 h. RESULTS: The DES-modelled intervention predicted a decrease in the %6-hour LOS from 19.0% to 13.1%, and a drop in the daily mean LOS from 249 to 200 min (p<0.0001). Following (actual) intervention, the number of patients with LOS >6 h decreased from 19.9% to 14.3% (p<0.0001), with the daily mean LOS decreasing from 247 to 210 min (p<0.0001). CONCLUSION: Physician and mid-level provider coverage at triage significantly reduced emergency department LOS in this setting. DES accurately predicted the magnitude of this effect. These results suggest further work in the generalisability of triage providers and in the utility of DES for predicting quantitative effects of process changes. |
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