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Association between adopting emergency department crowding interventions and emergency departments' core performance measures.
Alishahi Tabriz, Amir; Trogdon, Justin G; Fried, Bruce J.
Afiliação
  • Alishahi Tabriz A; Division of Pharmaceutical Outcomes and Policy, UNC Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Electronic address: amir17@live.unc.edu.
  • Trogdon JG; Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Electronic address: trogdonj@email.unc.edu.
  • Fried BJ; Department of Health Policy and Management, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. Electronic address: bruce_fried@unc.edu.
Am J Emerg Med ; 38(2): 258-265, 2020 02.
Article em En | MEDLINE | ID: mdl-31060861
OBJECTIVES: To estimate the association between adopting emergency department (ED) crowding interventions and emergency departments' core performance measures. METHODS: We analyzed the National Hospital Ambulatory Medical Care Survey (NHAMCS) data from 2007 to 2015. The outcome variables are ED length of stay for discharged and admitted patients, boarding time, wait time and percentage of patients who left ED before being seen (LWBS). The independent variables are whether or not a hospital adopted each of the 20 crowding interventions. Controlling for patient-level, hospital level and temporal confounders we analyze and report results using multivariable logit model. RESULTS: Between 2007 and 2015, NHAMCS collected data for 269,721 ED visit encounters, representing a nationwide of about 1.18 billion separate ED visits. Of 20 crowding interventions we tested, using adopting bedside registration (OR = 0.89, 95% CI = 0.75-0.98, P < .05), electronic dashboard (OR = 0.86, 95% CI = 0.76-0.98, P < .05), kiosk check-in technology (OR = 0.56, 95% CI = 0.41-0.83, P < .001), physician based triage (OR = 0.86, 95% CI = 0.73-0.99, P < .05) full capacity protocol (OR = 0.91, 95% CI = 0.79-0.99, P < .05) are associated with decrease in the odds of prolonged wait time. Adopting kiosk check-in (OR = 0.55, 95% CI = 0.35-0.85, P < .05) is associated with a decrease in the odds of prolonged boarding time. Using wireless communication devices (OR = 0.77, 95% CI = 0.57-0.97, P < .05), bedside registration (OR = 0.77, 95% CI = 0.64-0.094, P < .05) and pooled nursing (OR = 0.84, 95% CI = 0.72-0.98, P < .05) are associated with decrease in the odds of a patient LWBS. CONCLUSIONS: Majority of interventions did not significantly associated with ED' core performance measures.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aglomeração / Serviço Hospitalar de Emergência / Administração Hospitalar Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Child / Child, preschool / Female / Humans / Infant / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Aglomeração / Serviço Hospitalar de Emergência / Administração Hospitalar Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Aged / Child / Child, preschool / Female / Humans / Infant / Male / Middle aged Idioma: En Ano de publicação: 2020 Tipo de documento: Article