Applying Systems Engineering Reduces Radiology Transport Cycle Times in the Emergency Department

Abstract

Introduction: Emergency department (ED) crowding is widespread, and can result in care delays, medical errors, increased costs, and decreased patient satisfaction. Simultaneously, while capacity constraints on EDs are worsening, contributing factors such as patient volume and inpatient bed capacity are often outside the influence of ED administrators. Therefore, systems engineering approaches that improve throughput and reduce waste may hold the most readily available gains. Decreasing radiology turnaround times improves ED patient throughput and decreases patient waiting time. We sought to investigate the impact of systems engineering science targeting ED radiology transport delays and determine the most effective techniques.

Methods: This prospective, before-and-after analysis of radiology process flow improvements in an academic hospital ED was exempt from institutional review board review as a quality improvement initiative. We hypothesized that reorganization of radiology transport would improve radiology cycle time and reduce waste. The intervention included systems engineering science-based reorganization of ED radiology transport processes, largely using Lean methodologies, and adding no resources. The primary outcome was average transport time between study order and complete time. All patients presenting between 8/2013-3/2016 and requiring plain film imaging were included. We analyzed electronic medical record data using Microsoft Excel and SAS version 9.4, and we used a two-sample t-test to compare data from the pre- and post-intervention periods.

Results: Following the intervention, average transport time decreased significantly and sustainably. Average radiology transport time was 28.7 ± 4.2 minutes during the three months pre-intervention. It was reduced by 15% in the first three months (4.4 minutes [95% confidence interval [CI] 1.5-7.3]; to 24.3 ± 3.3 min, P=0.021), 19% in the following six months (5.4 minutes, 95% CI [2.7-8.2]; to 23.3 ± 3.5 min, P=0.003), and 26% one year following the intervention (7.4 minutes, 95% CI [4.8-9.9]; to 21.3 ± 3.1 min, P=0.0001). This result was achieved without any additional resources, and demonstrated a continual trend towards improvement. This innovation demonstrates the value of systems engineering science to increase efficiency in ED radiology processes.

Conclusion: In this study, reorganization of the ED radiology transport process using systems engineering science significantly increased process efficiency without additional resource use.

Figure 1

Pre-intervention radiology process flow. Lean value-stream map demonstrating multiple process steps required to achieve plain film radiology testing in the emergency department.

Figure 2

Pre-intervention radiology process flow value-added time summary. Lean value-stream map demonstrating the ability to calculate low value added percent time (24%) of the plain film radiology process, demonstrating opportunity for improvement.

Figure 3

Post Intervention: Systems engineering-based radiology process flow. Lean value-stream map demonstrating opportunity to eliminate process steps and increase efficiency in the process, and minimize the effect of a single server queue.

Figure 4

Average radiology transport time 2013–2016. Average radiology transport time following the intervention (minutes), demonstrating a significant trend towards improvement.

Figure 5

Average radiology transport time. Average radiology transport time (minutes) pre intervention and post intervention three, six, and 12 months following the intervention.