International perspectives on emergency department crowding

Effect of emergency department crowding on outcomes of admitted patients

STUDY OBJECTIVE

Emergency department (ED) crowding is a prevalent health delivery problem and may adversely affect the outcomes of patients requiring admission. We assess the association of ED crowding with subsequent outcomes in a general population of hospitalized patients.

METHODS

We performed a retrospective cohort analysis of patients admitted in 2007 through the EDs of nonfederal, acute care hospitals in California. The primary outcome was inpatient mortality. Secondary outcomes included hospital length of stay and costs. ED crowding was established by the proxy measure of ambulance diversion hours on the day of admission. To control for hospital-level confounders of ambulance diversion, we defined periods of high ED crowding as those days within the top quartile of diversion hours for a specific facility. Hierarchic regression models controlled for demographics, time variables, patient comorbidities, primary diagnosis, and hospital fixed effects. We used bootstrap sampling to estimate excess outcomes attributable to ED crowding.

RESULTS

We studied 995,379 ED visits resulting in admission to 187 hospitals. Patients who were admitted on days with high ED crowding experienced 5% greater odds of inpatient death (95% confidence interval [CI] 2% to 8%), 0.8% longer hospital length of stay (95% CI 0.5% to 1%), and 1% increased costs per admission (95% CI 0.7% to 2%). Excess outcomes attributable to periods of high ED crowding included 300 inpatient deaths (95% CI 200 to 500 inpatient deaths), 6,200 hospital days (95% CI 2,800 to 8,900 hospital days), and $17 million (95% CI $11 to $23 million) in costs.

CONCLUSION

Periods of high ED crowding were associated with increased inpatient mortality and modest increases in length of stay and costs for admitted patients.

Analysis and impact of delays in ambulance to emergency department handovers

OBJECTIVES

Delays in the clinical handover of patient care from emergency medical services (EMS) to the ED because of ED crowding are a substantial problem for many EMS systems. This study was conducted to quantify handover delays experienced by the Ambulance Service of New South Wales (ASNSW), and to investigate patient and system factors associated with handover delay.

METHODS

A retrospective study of EMS dispatch and ambulance patient care records was conducted for all patients transported by ASNSW in January/April/July/October 2009. Patient characteristics and time intervals were summarised using descriptive statistics, with handover delay categorised as <30 min, 30-60 min and ≥60 min. Times are reported as HH:MM:SS. Partial proportional odds models were used to investigate factors associated with delays.

RESULTS

Of 141 381 transports, 12.5% of patients experienced a handover delay of 30-60 min, and 5% a delay of ≥60 min. The median handover interval was 00:15:46 (IQR 00:08:58-00:24:52, maximum 08:43:13). Patients transported to large hospitals were more likely to experience a delay of ≥30 min (odds ratio [OR] 14.57, 95% CI 11.41-18.60) or ≥60 min (OR 15.75, 95% CI 12.27-20.23) than those transported to small hospitals. Patients in major cities were more likely to experience delays than those in other areas, and patients ≥65 years were more likely to experience delays than those <16 years. Delays were most likely in winter. Cardiac and major trauma patients had the lowest likelihood of experiencing delays.

CONCLUSIONS

Handover delays are relatively common at the EMS/ED interface in New South Wales, and are most pronounced at large hospitals, in urban areas and during winter.

Predictive variables of an emergency department quality and performance indicator: a 1-year prospective, observational, cohort study evaluating hospital and emergency census variables and emergency department time interval measurements

OBJECTIVE

Emergency department (ED) crowding impacts negatively on quality of care. The aim was to determine the association between ED quality and input, throughput and output-associated variables.

METHODS

This 1-year, prospective, observational, cohort study determined the daily percentage of patients leaving the ED in <4 h (ED quality and performance indicator; EDQPI). According to the median EDQPI two groups were defined: best-days and bad-days. Hospital and ED variables and time interval metrics were evaluated as predictors.

RESULTS

Data were obtained for 67 307 patients over 364 days. Differences were observed between the two groups in unadjusted analysis: number of daily visits, number of patients as a function of final disposition, number boarding in the ED, and time interval metrics including wait time to triage nurse and ED provider, time from ED admission to decision, time from decision to departure and length of stay (LOS) as a function of final disposition. Five variables remained significant predictors for bad-days in multivariate analysis: wait time to triage nurse (OR 2.36; 95% CI 1.36 to 4.11; p=0.002), wait time to ED provider (OR 1.93; 95% CI 1.05 to 3.54; p=0.03), number of patients admitted to hospital (OR 1.86; 95% CI 1.09 to 3.19; p=0.02), LOS of non-admitted patients (OR 9.5; 95% CI 5.17 to 17.48; p<0.000001) and LOS of patients admitted to hospital (OR 2.46; 95% CI 1.44 to 4.2; p=0.0009).

CONCLUSIONS

Throughput is the major determinant of EDQPI, notably time interval reflecting the work dynamics of medical and nursing teams and the efficacy of fast-track routes for low-complexity patients. Output also significantly impacted on EDQPI, particularly the capacity to reduce the LOS of admitted patients.

Evaluating the effect of clinical decision units on patient flow in seven Canadian emergency departments

OBJECTIVES

To evaluate the effect of emergency department (ED) clinical decision units (CDUs) on overall ED patient flow in a pilot project funded in 2008 by the Ontario Ministry of Health and Long-Term Care (MOHLTC).

METHODS

A retrospective analysis of unscheduled ED visits at seven CDU pilot and nine control sites was conducted using administrative data. The authors examined trends in CDU utilization and compared outcomes between pilot-CDU and control sites 1 year prior to implementation, with the first 18 months of CDU operation. Sites that were unsuccessful in their applications for CDU program funding served as controls. Outcomes included ED length of stay (LOS), admission rates, and ED revisit rates.

RESULTS

At CDU sites, roughly 4% of ED patients were admitted to CDUs. The presence of a pilot-CDU was independently associated with a small reduction in ED LOS for all low-acuity patients (-0.14 hour, 95% confidence interval [CI]=-0.22 to -0.07) and nonadmitted patients (-0.11 hour, 95% CI=-0.16 to -0.07). A small independent effect on absolute hospital admission rate for all high-acuity patients (-0.8%, 95% CI=-1.5% to -0.03%) and moderate-acuity patients (-0.6%, 95% CI=-1.1% to -0.2%) was also observed. Pilot-CDUs were not associated with changes in ED revisit rates.

CONCLUSIONS

With only 4% of ED patients admitted to CDUs, the potential for efficiency gains in these EDs was limited. Nonetheless, these findings suggest small improvements in the operation of the ED through CDU implementation. Although marginal, the observed effects of CDU operation were in the desired direction of reduced ED LOS, reduced admission rate, and no increase in ED revisit rate.