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Intern Emerg Med ; 17(3): 829-837, 2022 04.
Artigo em Inglês | MEDLINE | ID: mdl-34292458

RESUMO

To investigate the effects of the dramatic reduction in presentations to Italian Emergency Departments (EDs) on the main indicators of ED performance during the SARS-CoV-2 pandemic. From February to June 2020 we retrospectively measured the number of daily presentations normalized for the number of emergency physicians on duty (presentations/physician ratio), door-to-physician and door-to-final disposition (length-of-stay) times of seven EDs in the central area of Tuscany. Using the multivariate regression analysis we investigated the relationship between the aforesaid variables and patient-level (triage codes, age, admissions) or hospital-level factors (number of physician on duty, working surface area, academic vs. community hospital). We analyzed data from 105,271 patients. Over ten consecutive 14-day periods, the number of presentations dropped from 18,239 to 6132 (- 67%) and the proportion of patients visited in less than 60 min rose from 56 to 86%. The proportion of patients with a length-of-stay under 4 h decreased from 59 to 52%. The presentations/physician ratio was inversely related to the proportion of patients with a door-to-physician time under 60 min (slope - 2.91, 95% CI - 4.23 to - 1.59, R2 = 0.39). The proportion of patients with high-priority codes but not the presentations/physician ratio, was inversely related to the proportion of patients with a length-of-stay under 4 h (slope - 0.40, 95% CI - 0.24 to - 0.27, R2 = 0.36). The variability of door-to-physician time and global length-of-stay are predicted by different factors. For appropriate benchmarking among EDs, the use of performance indicators should consider specific, hospital-level and patient-level factors.


Assuntos
COVID-19 , Serviço Hospitalar de Emergência , Médicos , COVID-19/epidemiologia , Serviço Hospitalar de Emergência/normas , Serviço Hospitalar de Emergência/estatística & dados numéricos , Humanos , Itália , Tempo de Internação , Análise Multivariada , Pandemias , Médicos/estatística & dados numéricos , Análise de Regressão , Estudos Retrospectivos , SARS-CoV-2 , Fatores de Tempo
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