Self-reported safety belt use among emergency department patients in Boston, Massachusetts

BACKGROUND: Safety belt use is 80% nationally, yet only 63% in Massachusetts. Safety belt use among potentially at-risk groups in Boston is unknown. We sought to assess the prevalence and correlates of belt non-use among emergency department (ED) patients in Boston. METHODS: A cross-sectional survey with systematic sampling was conducted on non-urgent ED patients age ≥18. A closed-ended survey was administered by interview. Safety belt use was defined via two methods: a single-item and a multiple-item measure of safety belt use. Each was scored using a 5-point frequency scale. Responses were used to categorize safety belt use as 'always' or less than 'always'. Outcome for multivariate logistic regression analysis was safety belt use less than 'always'. RESULTS: Of 478 patients approached, 381 (80%) participated. Participants were 48% female, 48% African-American, 40% White, median age 39. Among participants, 250 (66%) had been in a car crash; 234 (61%) had a valid driver's license, and 42 (11%) had been ticketed for belt non-use. Using two different survey measures, a single-item and a multiple-item measure, safety belt use 'always' was 51% and 36% respectively. According to separate regression models, factors associated with belt non-use included male gender, alcohol consumption >5 drinks in one episode, riding with others that drink and drive, ever receiving a citation for belt non-use, believing that safety belt use is 'uncomfortable', and that 'I just forget', while 'It's my usual habit' was protective. CONCLUSION: ED patients at an urban hospital in Boston have considerably lower self-reported safety belt use than state or national estimates. An ED-based intervention to increase safety belt use among this hard-to-reach population warrants consideration

Time Series Analysis of Emergency Department Length of Stay per 8-Hour Shift

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). METHODS: 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

Time Series Analysis of Emergency Department Length of Stay per 8-Hour Shift

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 11:00PM), and shift 3 (11:00 PM to 7:00 AM).Methods: 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) forevery 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) onshift 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, andelective 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. [West J Emerg Med. 2012;13(2):163–168.