292: Hourly Patient Arrivals Predict the Number of Patients Who Leave Without Being Seen

Identifying key metrics for reducing premature departure from the pediatric emergency department

OBJECTIVES

Approximately 2% to 5% of children presenting to pediatric emergency departments (PEDs) leave prior to a complete evaluation. This study assessed risk factors for premature departure (PD) from a PED to identify key metrics and cutoffs for reducing the PD rate.

METHODS

A 3-year cohort (June 2004-May 2007) of children presenting to a PED was evaluated. Children were excluded if they presented for psychiatric issues, were held awaiting hospital admission in the PED due to a lack of inpatient beds, were more than 21 years old, or died before disposition. Univariate analyses, multivariable logistic regression, and recursive partitioning were used to identify factors associated with PD. A fourth year of data (June 2007-May 2008) was used for validation and sensitivity analysis.

RESULTS

There were 132,324 patient visits in the 3-year derivation data set with a 3.8% PD rate, and 45,001 visits in the fourth-year validation data set with a 4.3% PD rate. PDs were minimized when average wait time was below 110 minutes, concurrent PDs were fewer than two, and average length of stay (LOS) was less than 224 minutes in the derivation set, with similar results in the validation set. When these metrics were exceeded, PD rates were over 10% among low-acuity patients. These findings were robust across a broad range of assumptions during sensitivity analysis.

CONCLUSIONS

The authors identified five key metrics associated with PD in the PED: average wait time, average LOS, acuity, concurrent PDs, and arrival rate. Operational cutoffs for these metrics, determined by recursive partitioning, may be useful to physicians and administrators when selecting specific interventions to address PDs from the PED.

Premature departure from the pediatric emergency department: a cohort analysis of process- and patient-related factors

OBJECTIVE

Previous literature suggests that process-related factors (eg, time of day, patient volume) and patient-related factors (eg, acuity, socioeconomic status) are associated with premature departure from emergency departments. We sought to evaluate the relationship of these and other factors with premature departure in a large, unselected cohort of pediatric emergency department patients.

METHODS

This study was a retrospective cohort analysis of visits to a single tertiary site during a 1-year period. Patients' zip codes determined assignment of census-based socioeconomic metrics. Multivariate regression identified factors associated with premature departure. Sensitivity and subset analyses were performed. Return visits within 48 hours after premature departure were also reviewed.

RESULTS

There were 46,417 visits, of which 2164 were premature departures. In multivariate analysis, independent predictors of premature departures were arrival time, arrival month, arrival day of week, patient acuity, concurrent premature departures, arrival rate, arrival period average length of stay, and poverty rate. Aside from patient acuity and poverty rate, no patient-related factors were significant in multivariate analysis. These results were robust in sensitivity analysis across different multivariate models. Among premature departures, there were 120 return visits (5.5%), of which 15 were admitted (0.7%). There were no deaths. Acuity was similar between initial and subsequent visits.

CONCLUSIONS

Process-related factors and individual patient acuity have the strongest influence on premature departure from the pediatric emergency department. Health care organizations concerned with premature departure should focus efforts on improving pediatric emergency process flow.