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1.
West J Emerg Med ; 13(2): 163-8, 2012 May.
Artigo em Inglês | MEDLINE | ID: mdl-22900106

RESUMO

INTRODUCTION: The mean emergency department (ED) length of stay (LOS) is considered a measure of crowding. This paper measures the association between LOS and factors that potentially contribute to LOS measured over consecutive shifts in the ED: shift 1 (7:00 am to 3:00 pm), shift 2 (3:00 pm to 11:00 pm), and shift 3 (11:00 pm to 7:00 am). SETTING: University, inner-city teaching hospital. PATIENTS: 91,643 adult ED patients between October 12, 2005 and April 30, 2007. DESIGN: For each shift, we measured the numbers of (1) ED nurses on duty, (2) discharges, (3) discharges on the previous shift, (4) resuscitation cases, (5) admissions, (6) intensive care unit (ICU) admissions, and (7) LOS on the previous shift. For each 24-hour period, we measured the (1) number of elective surgical admissions and (2) hospital occupancy. We used autoregressive integrated moving average time series analysis to retrospectively measure the association between LOS and the covariates. RESULTS: For all 3 shifts, LOS in minutes increased by 1.08 (95% confidence interval 0.68, 1.50) for every additional 1% increase in hospital occupancy. For every additional admission from the ED, LOS in minutes increased by 3.88 (2.81, 4.95) on shift 1, 2.88 (1.54, 3.14) on shift 2, and 4.91 (2.29, 7.53) on shift 3. LOS in minutes increased 14.27 (2.01, 26.52) when 3 or more patients were admitted to the ICU on shift 1. The numbers of nurses, ED discharges on the previous shift, resuscitation cases, and elective surgical admissions were not associated with LOS on any shift. CONCLUSION: Key factors associated with LOS include hospital occupancy and the number of hospital admissions that originate in the ED. This particularly applies to ED patients who are admitted to the ICU.

2.
Ann Emerg Med ; 49(3): 265-71, 2007 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-17224203

RESUMO

STUDY OBJECTIVE: We measure the effect of various input, throughput, and output factors on daily emergency department (ED) mean length of stay per patient (daily mean length of stay). METHODS: The study was a retrospective review of 93,274 ED visits between April 15, 2002, and December 31, 2003. The association between the daily mean length of stay and the independent variables was assessed with autoregressive moving average time series analysis (ARIMA). The following independent variables were measured per 24-hour period: number of elective surgical admissions, ED volume, number of ED admissions, number of ED ICU admissions, number of ED clinical attending hours, hospital medical-surgical occupancy (hospital occupancy), and day of the week. RESULTS: Three factors were independently associated with daily mean length of stay in time series analysis: number of elective surgical admissions, number of ED admissions, and hospital occupancy. The daily mean length of stay increased by 0.21 minutes for every additional elective surgical admission, 2.2 minutes for every additional admission, and 4.1 minutes for every 5% increase in hospital occupancy. Elective surgical admissions were associated with a maximum of 35 hours of additional ED dwell time. The model accounted for 31.5% of the variability in daily mean length of stay. The final model parameters for the ARIMA analysis were autoregressive term (1) moving average (1). CONCLUSION: Hospital occupancy and the number of ED admissions are associated with daily mean length of stay. Every additional elective surgical admission prolonged the daily mean length of stay by 0.21 minutes per ED patient. Autocorrelation exists between the daily mean length of stay of the current day and the previous day.


Assuntos
Serviço Hospitalar de Emergência/estatística & dados numéricos , Tempo de Internação/estatística & dados numéricos , Ocupação de Leitos/estatística & dados numéricos , Boston , Procedimentos Cirúrgicos Eletivos/estatística & dados numéricos , Humanos , Análise Multivariada , Admissão do Paciente/estatística & dados numéricos , Estudos Retrospectivos , Fatores de Tempo
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