Operations Research Contributions to Emergency Department Patient Flow Optimization: Review and Research Prospects

Saghafian, Soroush; Austin, Garrett; Traub, Stephen J.

doi:10.2139/ssrn.2420163

Cited by 5 publications

(7 citation statements)

References 292 publications

(164 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Emergency Department (ED) is the gate to the hospital, through which virtually all non-elective patients enter. Patient flow within the ED has been widely investigated, both academically (Hall et al, 2006;Saghafian, Austin and Traub, 2014;Zeltyn et al, 2011) and in practice (IHI, 2011;McHugh et al, 2011). Here we thus content ourselves with its empirical macro (black box) view.…”

Section: Patient Flow In Hospitalsmentioning

confidence: 99%

On Patient Flow in Hospitals: A Data-Based Queueing-Science Perspective

et al. 2015

View full text Add to dashboard Cite

Hospitals are complex systems with essential societal benefits and huge mounting costs. These costs are exacerbated by inefficiencies in hospital processes, which are often manifested by congestion and long delays in patient care. Thus, a queueing-network view of patient flow in hospitals is natural for studying and improving its performance. The goal of our research is to explore patient flow data through the lens of a queueing scientist. The means is exploratory data analysis (EDA) in a large Israeli hospital, which reveals important features that are not readily explainable by existing models. Questions raised by our EDA include: Can a simple (parsimonious) queueing model usefully capture the complex operational reality of the Emergency Department (ED)? What time scales and operational regimes are relevant for modeling patient length of stay in the Internal Wards (IWs)? How do protocols of patient transfer between the ED and the IWs influence patient delay, workload division and fairness? EDA also underscores the importance of an integrative view of hospital units by, for example, relating ED bottlenecks to IW physician protocols. The significance of such questions and our related findings raise the need for novel queueing models and theory, which we present here as research opportunities. Hospital data, and specifically patient flow data at the level of the individual patient, is increasingly collected but is typically confidential and/or proprietary. We have been fortunate to partner with a hospital that allowed us to open up its data for everyone to access. This enables reproducibility of our findings, through a user-friendly platform that is accessible via the Technion SEELab.

show abstract

Section: Patient Flow In Hospitalsmentioning

confidence: 99%

On Patient Flow in Hospitals: A Data-Based Queueing-Science Perspective

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Inspired by Asplin et al (2003), Saghafian et al (2014a), and Welch (2012) that all split up the ED in three parts, the articles will be structured according to the framework of Figure 1; the intake-treatment-outflow model. The intake and outflow of the ED have received less interest in the OR/OM literature.…”

Section: Scopementioning

confidence: 99%

“…In practice, however, the intake and outflow have been identified as 'problem areas', in need of well-founded improvements (Crawford et al, 2013;Hall, 2006;Richardson & Mountain, 2009;Welch & Savitz, 2012;Wiler et al, 2010). Since good literature reviews already exist on capacity management (Defraeye & Nieuwenhuyse, 2013;Saghafian et al, 2014a), we will thus focus on the first and last step where the ED interacts with its environment.…”

Section: Scopementioning

confidence: 99%

Improving Patient Flow in Emergency Departments with OR Techniques: A Literature Overview

Carmen

Nieuwenhuyse

2014

SSRN Journal

View full text Add to dashboard Cite

“…Following [2], we chose to use the term 'crowding' in this article. Crowding has received attention since the early '90s in the medical literature (see, e.g., [1][2][3][4][5]) and in the field of Operations Research and Operations Management [6,7]. Simultaneously, there is increasing pressure on EDs to improve their operational performance, and decrease the length of stay (LOS) of patients in the ED [6].…”

Section: Introductionmentioning

confidence: 99%

“…The issue is that EDs are highly complex environments: patient arrival rates vary over time, patient care paths depend on urgency and pathology, resources (staff and beds) may or may not be suited for treating all patient types, urgent patients typically get priority over (and may even preempt resources from) non-urgent patients, patients who need to be admitted often board in ED beds (i.e., they remain blocked in ED beds due to the unavailability of beds in the inpatient units (IUs)), etc. While in reality, the patient flow through the ED results from the interplay of all these factors, the majority of academic models tend to analyse only one factor [6]. This article presents a practical DSS for improving patient flow in real-life EDs.…”

Section: Introductionmentioning

confidence: 99%

A Decision Support System for Capacity Planning in Emergency Departments

Carmen¹,

Defraeye²,

Nieuwenhuyse³

2015

Int. j. simul. model.

View full text Add to dashboard Cite

In this article, we present a decision support system (DSS) for improving patient flow in emergency departments (EDs). The core of the system is a discrete-event simulation (DES) model that aims to support capacity planning in the ED, in view of controlling patients' length of stay (LOS). Conceptually, it regards the patient LOS as the result of different queueing systems, the behaviour of which is influenced by different types of capacities. Taking inputs from ED patient record data, the DSS allows to analyse the impact of different capacity changes on patient flow, and to detect efficient capacity combinations using data envelopment analysis (DEA). We report on the insights obtained from a case study in a large regional hospital in Belgium.

show abstract

Operations Research Contributions to Emergency Department Patient Flow Optimization: Review and Research Prospects

Cited by 5 publications

References 292 publications

On Patient Flow in Hospitals: A Data-Based Queueing-Science Perspective

On Patient Flow in Hospitals: A Data-Based Queueing-Science Perspective

Improving Patient Flow in Emergency Departments with OR Techniques: A Literature Overview

A Decision Support System for Capacity Planning in Emergency Departments

Contact Info

Product

Resources

About