Quantile regression and an application: performance improvement of an emergency department in Eastern Europe

Abstract

ED (emergency department) overcrowding is a problem faced by hospitals worldwide. Several studies have been performed to find solutions, but only few have proposed to decrease the length of stay by employing a radiologist in the ED. This study aims to improve emergency care in an Eastern European ED by measuring the parameters of crowding, introducing interventions based on the results, and evaluating their outcomes. As the length of stay is a typically skewed distribution variable, robust quantile regression is applied. The number of patients visiting the ED was measured from July 2014 to December 2015. The input, throughput and output parameters of ED crowding were evaluated throughout this period. The time intervals between the various stages of patient visits to the ED significantly decreased during the study period. The continuous measure-ment of ED process parameters is important to maintain time intervals within a specified range. Decreased process times between the pre- and post-intervention phases of the study were obtained by introducing several staff-centric changes. The presence of a dedicated radiologist in the ED has significantly decreased the turnaround times of imaging studies.