Objective: Evaluate the impact of adding emergency medicine residents to a medium-size urban hospital by comparing emergency department (ED) admission rate, total census, length of stay (LOS), and proportion of patients who left without being seen (LWBS).

Methods: Using the student t-test, the study compared commonly used ED metrics for a mid-sized urban hospital (annual census 43,000) for the four-month period prior to (March-June 2006) and after (March-June 2007) residents began providing 24-hour coverage at the institution.

Results: There was no significant difference in the number of patients seen (NPS) in the two time periods, 14,471 and 14,699 patients respectively (p=0.507). Analysis of the NPS and LWBS was not statistically significant. The percentage of patients who LWBS decreased with the presence of residents (6.5% to 5.8%, p=0.531), and the overall ED LOS was similar (210 min vs. 219 min, p=0.56). Admission rate data demonstrated that residents had a similar admission rate (17.5% vs. 18%, p =0.332).

Conclusion: ED flow depends on a number of variables with complex interactions. When comparing two similar time periods in consecutive years, the presence of resident physicians in the ED had no effect on the number of patients seen, patient LOS in the ED, or LWBS, thus supporting the conclusion that residents did not adversely affect the patient flow within the ED. [West J Emerg Med. 2010; 11(4):333-335.]

Objective: Determine the effect that increased medical surgical (med/surg) bed occupancy has on the time interval from admission order to arrival in the bed for the patients admitted from the emergency department (ED).

Methods: This retrospective observational study compares the total hospital bed occupancy rate and the medical surgical inpatient bed occupancy rate to daily averages for the time interval from admission order (patient posting for admission) to the patient’s arrival in the inpatient bed. Medical surgical inpatient bed occupancy of 92% was chosen because beyond that rate we observed more frequent extended daily transfer times. The data is from a single large tertiary care institute with 590 beds and an annual ED census of 80,000.

Results: Group 1 includes 38 days with (med/surg) inpatient bed occupancy rate of less than 92%, with an average ED daily wait of 2.5 hrs (95% confidence interval 2.23-2.96) for transfer from the ED to the appropriate hospital bed. Group 2 includes 68 days with med/surg census greater than 92% with an average ED daily wait of 4.1 hours (95% confidence interval 3.7-4.5). Minimum daily average for the two groups was 1.2 hrs and 1.3 hrs, respectively. The maximum average was 5.6 hrs for group 1 and 8.6 hrs for group 2. Comparison of group 1 to 2 for wait time to hospital bed yielded p <0.01. Total reported hospital occupied capacity shows a correlation coefficient of 0.16 to transfer time interval, which indicates a weak relationship between total occupancy and transfer time into the hospital. Med/surg occupancy, the beds typically used by ED patients, has a 0.62 correlation coefficient for a moderately strong relationship.

Conclusions: Med/surg bed occupancy has a better correlation to extended transfer times, and occupancy over 92% at 5 AM in our institution corresponds to an increased frequency of extended transfer times from the ED. The process of ED evaluation, hospital admission, and subsequent transfer into the hospital are all complex processes. This study begins to demonstrate one variable, med/surg occupancy, as one of the intervals that can be followed to evaluate the process of ED admission and hospital flow. [WestJEM. 2009;10:93-96.]