The Impact of Input and Output Factors on Emergency Department Throughput

Emergency Medicine Division, Washington University School of Medicine, St. Louis, MO, USA.
Academic Emergency Medicine (Impact Factor: 2.01). 04/2007; 14(3):235-42. DOI: 10.1197/j.aem.2006.10.104
Source: PubMed


To quantify the impact of input and output factors on emergency department (ED) process outcomes while controlling for patient-level variables.
Using patient- and system-level data from multiple sources, multivariate linear regression models were constructed with length of stay (LOS), wait time, treatment time, and boarding time as dependent variables. The products of the 20th to 80th percentile ranges of the input and output factor variables and their regression coefficients demonstrate the actual impact (in minutes) of each of these factors on throughput outcomes.
An increase from the 20th to the 80th percentile in ED arrivals resulted in increases of 42 minutes in wait time, 49 minutes in LOS (admitted patients), and 24 minutes in ED boarding time (admitted patients). For admit percentage (20th to 80th percentile), the increases were 12 minutes in wait time, 15 minutes in LOS, and 1 minute in boarding time. For inpatient bed utilization as of 7 AM (20th to 80th percentile), the increases were 4 minutes in wait time, 19 minutes in LOS, and 16 minutes in boarding time. For admitted patients boarded in the ED as of 7 AM (20th to 80th percentile), the increases were 35 minutes in wait time, 94 minutes in LOS, and 75 minutes in boarding time.
Achieving significant improvement in ED throughput is unlikely without determining the most important factors on process outcomes and taking measures to address variations in ED input and bottlenecks in the ED output stream.

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Available from: Phillip V Asaro, Jan 16, 2015
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    • "Some studies propose mechanisms that decrease service times; KC and Terwiesch (2009) have reported, for example, that hospital transporters speed up during busy periods. Other studies propose mechanisms that increase service times; Asaro et al. (2007) report that nurses intentionally work slower when a new 1 patient is admitted, for example. Yet other studies propose a combination of mechanisms that results in non-monotonic relationships; Tan and Netessine (2014) report, for example, that the meal duration in a restaurant first increases and then decreases with the number of diners. "
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    DESCRIPTION: In this paper, we develop a general framework to analyze the influence of system load on service times in queueing systems. Our proposed framework unifies previous results and ties them to possible future studies to help empirical and analytical researchers to investigate and model the ways in which load impacts service times. We identify three load characteristics: changeover, instantaneous load, and extended load. The load characteristics induce behaviors, or mechanisms, in at least one of the system components: the server, the network, and the customer. A mechanism influences the service-time determinants: the work content or the service speed. We identify and define mechanisms that cause service times to change with load and use the framework to categorize them. We propose that an understanding of the relationship between load and service times can come about only by understanding the underlying mechanisms.
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    • "Patients presenting to EDs are often very sick or in a great deal of pain and, as a result, may not be receptive to a brief intervention for their substance use. Likewise, urban EDs are often fast paced and overcrowded [27] with tremendous pressure placed on providers to improve patient throughput, leaving little time for alcohol/drug interventions , which may last from 5 to 30 minutes. Regardless of setting, health professionals frequently cite time constraints as a major barrier to alcohol screening and intervention implementation [28] [2]. "
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    ABSTRACT: The strongest evidence for effectiveness of screening, brief intervention, and referral to treatment (SBIRT) programs is in primary care settings. Emergency department (ED) studies have shown mixed results. Implementation of SBIRT into ED settings is complicated by the type of patients seen and the fast-paced, high-throughput nature of the ED environment that makes it difficult to reach patients flagged for SBIRT services. This study uses data from an ED-based SBIRT program to examine the relationship between screen-positive rate, ED patient flow, and SBIRT service delivery. Data for the study (N = 67137) were derived from weekly reports extracted directly from one hospital's electronic health record. Measures included time and day of patient entry, drug/alcohol screen result (positive or negative), and whether the patient was reached by SBIRT specialists. Factorial analysis of variance compared variations in screen-positive rates by day and time and the percentage of patients reached by SBIRT specialists during these periods. Overall, 56% of screen-positive patients received SBIRT services. Only 5% of patients offered SBIRT services refused. Day and time of entry had a significant interaction effect on the reached rate (F12,14166 =3.48, P < .001). Although patient volume was lowest between 11 pm and 7 am, screen-positive rates were highest during this period, particularly on weekends; and patients were least likely to be reached during these periods. When implementing an ED-based SBIRT program, thoughtful consideration should be given to patient flow and staffing to maximize program impact and increase the likelihood of sustainability. Copyright © 2014 Elsevier Inc. All rights reserved.
    American Journal of Emergency Medicine 10/2014; 33(1). DOI:10.1016/j.ajem.2014.10.021 · 1.27 Impact Factor
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    • "The national standard of 30 minutes between presentation to first analgesia is difficult to achieve in the ED setting where delayed access to care is not uncommon in the current health landscape (Asaro and Boxerman, 2007; Huang et al., 2010). There are numerous variables which impact upon the patients' journey to access definitive care: the time taken to register the patient demographics for basic registration, assessment by a streaming nurse, data entry into the ED patient information system, allocation of a treatment zone, time to travel to the zone and then the ability of a clinician being available to assess the patient. "
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    ABSTRACT: Objectives To evaluate quality of care delivered to patients presenting to the emergency department (ED) with pain and managed by emergency nurse practitioners by measuring: 1) Evaluate time to analgesia from initial presentation 2) Evaluate time from being seen to next analgesia 3) Pain score documentation Background The delivery of quality care in the emergency department (ED) is emerging as one of the most important service indicators being measured by health services. Emergency nurse practitioner services are designed to improve timely, quality care for patients. One of the goals of quality emergency care is the timely and effective delivery of analgesia for patients. Timely analgesia is an important indicator of ED service performance. Methods A retrospective explicit chart review of 128 consecutive patients with pain and managed by emergency nurse practitioners was conducted. Data collected included demographics, presenting complaint, pain scores, and time to first dose of analgesia. Patients were identified from the ED Patient Information System (Cerner log) and data were extracted from electronic medical records Results Pain scores were documented in 67 (52.3%; 95% CI: 43.3-61.2) patients. The median time to analgesia from presentation was 60.5 (IQR 30-87) minutes, with 34 (26.6%; 95% CI: 19.1-35.1) patients receiving analgesia within 30 minutes of presentation to hospital. There were 22 (17.2%; 95% CI: 11.1-24.9) patients who received analgesia prior to assessment by a nurse practitioner. Among patients that received analgesia after assessment by a nurse practitioner, the median time to analgesia after assessment was 25 (IQR 12-50) minutes, with 65 (61.3%; 95% CI: 51.4-70.6) patients receiving analgesia within 30 minutes of assessment. Conclusions The majority of patients assessed by nurse practitioners received analgesia within 30 minutes after assessment. However, opportunities for substantial improvement in such times along with documentation of pain scores were identified and will be targeted in future research.
    International Emergency Nursing 07/2014; 23(2). DOI:10.1016/j.ienj.2014.07.002 · 0.72 Impact Factor
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