research paper on emergency department

• Subscribe to journal Subscribe
• Get new issue alerts Get alerts

Secondary Logo

Journal logo.

Colleague's E-mail is Invalid

Your message has been successfully sent to your colleague.

Save my selection

Emergency medicine: past, present, and future challenges

Wei, Shujian a,b,c,d,e,∗

a Department of Emergency Medicine and Chest Pain Center, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China

b Clinical Research Center for Emergency and Critical Care Medicine of Shandong Province, Institute of Emergency and Critical Care Medicine of Shandong University, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China

c Key Laboratory of Emergency and Critical Care Medicine of Shandong Province, Key Laboratory of Cardiopulmonary-Cerebral Resuscitation Research of Shandong Province, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China

d Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese Ministry of Health and Chinese Academy of Medical Sciences, State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China

e Qilu Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China.

∗Corresponding author. Address: Department of Emergency Medicine and Chest Pain Center, Qilu Hospital, Cheeloo College of Medicine, Shandong University, No. 107, Wenhuaxi Road, Jinan, Shandong, 250012, China. E-mail address: [email protected] (S. Wei).

How to cite this article: Wei S. Emergency medicine: past, present, and future challenges. Emerg Crit Care Med. 2021;1:49–52. doi: 10.1097/EC9.0000000000000017

Sponsorships or competing interests that may be relevant to content are disclosed at the end of this article.

This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0

Origin and history of emergency medicine

The term “emergency,” first used in the 1630s, is derived from the Latin word emergere , meaning unforeseen events that require immediate attention. The term “emergency medicine” can be traced to the French Revolution (1789–1799). In 1792, Dominique Jean Larrey, a military medical surgeon, gained a position in the Army of the Rhine and left for Strasbourg, where he witnessed great mobility of the horse artillery and then suggested that General Adam Philippe de Custine have the medical staff use this method to speed up transport of the wounded. The general approved Larrey's proposal. Larrey's “ambulance” was a simple carriage, despite the exposure to enemy fire. In 1797, during the first Italian campaign, Larrey created a complete rescue system with an active medical team in the battlefield. In contrast to previous rescue methods, Larrey transported critically wounded patients to the rescue station and operated on them as soon as possible, instead of delaying the operation after the battle. The timely rescue system created by him enabled every wounded soldier to be treated within 24 hours, which significantly reduced the mortality rate. Therefore, Larrey has often been referred to as “the father of emergency medical services.” [1]

Medicine, as a professional field, dates back to the early 19th century, while emergency medicine can only be traced back to 50 years ago, making it the most recently developed major field in medicine. Before the 1960s, staff in hospital emergency departments usually worked in rotation with family doctors, general surgeons, physicians, and other specialists. In many small emergency departments, nurses conducted the triage of patients, and specialty doctors were called in based on the type of injury or disease. Many pioneers of emergency medicine were family doctors and other specialists, who believed that extra training in first aid was necessary. A group of doctors left their professional positions and devoted themselves to education. In 1952, Maurice Ellis was appointed as the first “first aid consultant” at Leeds General Infirmary in England. In 1967, the Casualty Surgeons Association was founded, with Maurice Ellis as its president. [2,3] In 1961, in the United States, Dr James DeWitt Mills, along with 4 assistant physicians, established 24/7 emergency care at Alexandria Hospital in Alexandria, Virginia; it was later known as the Alexandria Plan. [4] In 1970, the University of Cincinnati launched the first emergency resident physician program in the world. In 1971, the University of Southern California became the first American medical school to establish a department of emergency medicine. [5] History was made in 1979, when the American Board of Medical Specialties voted to make emergency medicine a recognized medical specialty in the United States. [5]

In China, emergency medicine started relatively late. The Ministry of Health issued “Suggestions on Strengthening First Aid Work in the City” and “On the Release of the Construction Plan of Hospital Emergency Departments (Trial)” on October 30, 1980 and June 11, 1984, respectively. These 2 documents stipulated the work direction, scope, and tasks of the emergency department; thereby, laying the foundation for the construction of emergency departments in China. In 1985, Peking Union Medical College Hospital established the first postgraduate program in emergency medicine. [6–8]

Current state of emergency medicine

Emergency medicine mainly involves the rapid assessment, treatment, and triage of critically ill patients, and has transformed from the emergency room to the emergency department or emergency center. Hospitals typically set up a relatively complete emergency medical system of “out-of-hospital emergency medical services, in-hospital emergency medical services, and critical care.” Numerous emergency diagnostic and treatment technologies, such as cardiopulmonary resuscitation, emergency percutaneous coronary intervention, continuous renal replacement therapy, left ventricular assistive devices, and extracorporeal membrane oxygenation, are applied in emergency medicine. Moreover, a growing number of qualified physicians have devoted themselves to emergency medicine, and several academic platforms have been established, which facilitate knowledge exchange.

With the continuous reform of the medical system and the comprehensive implementation and promotion of hierarchical diagnostic and treatment systems from medical reform, the development of emergency medicine is confronted with rare opportunities and more challenges. For example, the construction of emergency systems varies across nations and regions. Practitioners in emergency services have the vital task of establishing a complete emergency diagnosis and treatment system to maintain the daily health of the public and to satisfy the emergency demands of major public health events. It is necessary to move the front of first aid forward, carry out multidisciplinary cooperation, treat all types of critically ill patients, deal with public health emergencies, and boost hierarchical diagnosis and treatment work. Amid the rapid growth of modern medicine, advanced technology and innovative drugs continue to emerge. In many cases of emergency work, it is the timely, orderly, and efficient application of these technologies and drugs to the early treatment of critically ill patients that matters. Therefore, “process optimization and early treatment” is an important direction in emergency medicine research.

With the development of a medical discipline, each medical specialty is more characterized, and even some single diseases tend to form specialties. [9] Following the law of medical development, emergency medicine also gives full play to specialty characteristics and the development of subspecialties. [10] For example, in areas with a high incidence of cardiovascular diseases, emergency centers have subspecialty focus areas for cardiovascular diseases, and in rural areas with a common occurrence of acute poisoning, emergency departments of primary hospitals establish a subspecialty for the treatment of acute poisoning. In developing subspecialties, emergency medicine focuses on the advancement of diagnostic and treatment technologies for life-threatening diseases and integration with other subspecialties. The construction of high-quality subspecialties in emergency medicine is conducive to the development of new diagnostic and treatment equipment and technology.

Future of emergency medicine

The coronavirus disease pandemic has brought huge challenges to medical systems, especially emergency medicine. [11] Elevating the capability of early identification, appropriate treatment, and life support for severe or critical patients will always be the core topics of emergency medicine.

Emergency medicine in the future will be characterized by continuous advances in practices, research, technologies, and so forth. In terms of clinical practices, problems such as inefficiency and crowding may arise and cause tension in emergency departments. The development of emergency medicine is still in its primary stage and is extremely uneven between rural and urban areas. The resolution of such issues and optimization of processes in emergency medicine can be realized by implementing an increasing number of equipment configurations, improving the structure of emergency medical personnel, and establishing a closer linkage between out-of-hospital and in-hospital emergency services. In essence, “process optimization and early treatment” manifests as an influential component in the development of emergency medicine. In the optimization of the emergency process, the stability of emergency medical professionals is a valuable resource. Upgrading clinical emergency care competence, including rapid response, effectiveness, and service attitude, and improving the skills of medical professionals in the emergency department are of great importance.

The demands for technology are certain to direct the course of emergency services, as the need for timely diagnosis and treatment of patients continues to grow. Information technology can be used to tap available resources and collect information on patients and disease management to aid emergency staff in real time via telemedicine. Specifically, in the absence of specialists or general practitioners on site, the vital signs of patients and critical information can be wirelessly transmitted to experts who can provide remote guidance that may be critical to saving lives. [12] In addition, remote monitoring also enables hospitals to grasp the condition of patients at the earliest time, formulate emergency plans in advance, and ensure a seamless connection between out-of-hospital emergency and in-hospital treatment. By virtue of networks, the real-time transmission of medical devices that monitor information, ambulances’ positioning information, and video footage from inside and outside ambulances can facilitate remote consultation and guidance. Moreover, the collection, processing, storage, transmission, and sharing of out-of-hospital emergency information can fully enhance treatment efficiency and service quality, thereby optimizing the process and mode of service.

Big data technology can fully explore medical information to aid in the management and decision-making of emergency care. [13] One of the applications of big data in the medical field is the establishment of a cloud platform for emergency and critical care information management. Such a platform would collect the diagnosis-, examination-, and treatment-related information of patients from databases, such as an emergency logbook, a hospital information system, a picture archiving and communication system, a microbial detection and management system, and a pathology information system. Next, the data were classified, cleaned, extracted, and explored in depth using the platform. Based on this information, a teaching management system can be obtained, including a multidisciplinary triage management system, a critical care score and grading management system, and an early warning system for serious emergencies. The application of big data technology in emergency medicine provides medical practitioners with access to various information databases for each individual and possible treatment options, which will greatly improve teaching efficiency and the ability to diagnose and treat related diseases.

Precision medicine is a medical model that fully considers individual differences in the genes, environment, and lifestyle of patients to achieve the most effective treatment and prevention of diseases. The emergency department is the first critical link in the clinical diagnosis and treatment of critical illnesses and infectious diseases, and individualized accurate assessment and prevention of disease susceptibility is a valuable research direction for precision emergency medicine. [14] Acute infectious diseases are among the most common diseases in the emergency department. However, given the complexity of diseases, lag in detection technology, and lack of multidimensional clinical information integration technology, the diagnosis and treatment of common diseases such as community-acquired pneumonia remain stagnant. In addition, the emergence of drug-resistant pathogens and emerging microorganisms poses a challenge to empirical therapy protocols. Identifying pathogenic microorganisms quickly and accurately is critical for initiating individualized treatment plans and is also the core component of precision emergency medicine systems. The ideal method of monitoring the outbreak of drug-resistant pathogenic microorganisms in communities or hospitals is to analyze the genetic ancestry of pathogenic microorganisms through genome technology. One of the essential tasks of emergency medicine is to use clinical information to provide individualized diagnosis and treatment for cases without a clear etiology. To some extent, it is necessary to establish etiological diagnoses through emergency treatment processes. In addition to molecular etiology diagnoses based on pathogenic specimens (eg, throat swabs, sputum, and body fluids), diagnostic techniques based on omics information have also seen rapid advances, which will improve precision emergency treatment services. For the differential diagnosis of emergency and critical care illnesses, precision emergency medicine can enhance diagnostic effectiveness significantly with the help of multidimensional and omics data, thus creating the ideal conditions for individualized diagnosis and treatment.

With the combination of big data and precision medicine, information technology can promote the growth of scientific research and clinical work in emergency medicine, such as sequencing, information construction, data integration, and analysis, and improve the use of big data in emergency medicine. Under these circumstances, it is possible to achieve breakthroughs in the development of targeted drugs for precision therapy, complete the closed-loop service of precision emergency medicine, and establish a disciplinary system for precision emergency medicine in China.

Artificial intelligence can promote the growth of emergency medicine. [15] Equipped with capabilities in prediction, analysis, and response, artificial intelligence systems can aid emergency staff in diagnosis and treatment. When artificial intelligence tools execute instructions, they can learn from big data through image recognition, speech recognition, human–computer interaction, physical sensing, and other means. After finishing examinations quickly, artificial intelligence tools can formulate a relatively accurate diagnosis and individualized medicine. In addition, artificial intelligence can assist in locating potential risks and threats in advance. In some emergency events, artificial intelligence can assess the situation and predict the required medical services. Another example of artificial intelligence is the use of medical robots. Apart from their application during complex surgeries, medical robots can deliver objects to patients in quarantine and help avoid human contact during virus epidemics. In short, the use of artificial intelligence will undoubtedly benefit emergency medicine in the future.

As more countries are improving their emergency medical systems, the global scale of information exchange is empowering international emergency medicine. Promoting the quality of academic exchange among countries is a priority in the development of international emergency medicine. Moreover, the variety and complexity of emergency diseases pose challenges to timely and accurate emergency medical treatment, and require emergency medical staff to possess rich medical knowledge and accurate judgment.

Although the development of emergency medicine is confronted with quite a few challenges, it has entered the era of communication among various schools of thought. This journey provides opportunities to the field of emergency medicine. With the joint efforts and hard work of stakeholders worldwide, emergency medicine will accomplish more historic advancements.

Conflict of interest statement

Shujian Wei is the Executive Editor of Emergency and Critical Care Medicine . The author declares no conflicts of interest.

Author contributions

Shujian Wei wrote the article.

Ethical approval of studies and informed consent

Acknowledgements.

• Cited Here |
• Google Scholar
• PubMed | CrossRef |
• View Full Text | PubMed | CrossRef |
• + Favorites
• View in Gallery

Readers Of this Article Also Read

Bioinformatics analysis of sars-cov-2 infection-associated immune injury and..., emergency medicine and covid-19: now and next year, new problems and countermeasures in the prevention and control of covid-19, expert consensus by qilu hospital of shandong university on the diagnosis,..., treatment of acute pulmonary edema by blocking vegf-induced vascular leakage.

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here .

Loading metrics

Open Access

Peer-reviewed

Research Article

The effect of overcrowding in emergency departments on the admission rate according to the emergency triage level

Roles Conceptualization, Data curation, Writing – original draft

Affiliation Department of Emergency Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea

Roles Conceptualization, Data curation, Methodology

Roles Conceptualization, Data curation

Roles Methodology, Supervision

Roles Supervision

Roles Data curation, Formal analysis, Investigation, Methodology, Supervision, Writing – review & editing

* E-mail: [email protected]

• Hae Min Jung, 
• Min Joung Kim, 
• Ji Hoon Kim, 
• Yoo Seok Park, 
• Hyun Soo Chung, 
• Sung Phil Chung, 
• Ji Hwan Lee

• Published: February 17, 2021
• https://doi.org/10.1371/journal.pone.0247042
• Reader Comments

Overcrowding in emergency departments is a serious public health issue. Recent studies have reported that overcrowding in emergency departments affects not only the quality of emergency care but also clinical decisions about admission. However, no studies have examined the characteristics of the patient groups whose admission rate is influenced by such overcrowding. This retrospective cohort study was conducted in a single emergency department between January 1 and December 31, 2018. Patients over 19 years old were enrolled and divided into three groups according to the degree of overcrowding—high, low, and non—based on the total number of patients in the emergency department. An emergency triage tool (the Korean Triage and Acuity Scale) was used, which categorizes patients into five different levels. We analyzed whether the degree of change in the admission rate according to the extent of overcrowding differed for each triage group. There were 73,776 patients in this study. In the analysis of all patient groups, the admission rate increased as the degree of overcrowding rose (the adjusted odds ratio for admission was 1.281 (1.225–1.339) in the high overcrowding group versus the non-overcrowding group). The analysis of the patients in each triage level showed an increase in the admission rate associated with the overcrowding, which was greater in the patient groups with a lower triage level (adjusted odds ratios for admission in the high overcrowding group versus non-overcrowding group: Korean Triage and Acuity Scale level 3 = 1.215 [1.120–1.317], level 4 = 1.294 [1.211–1.382], and level 5 = 1.954 [1.614–2.365]).

Citation: Jung HM, Kim MJ, Kim JH, Park YS, Chung HS, Chung SP, et al. (2021) The effect of overcrowding in emergency departments on the admission rate according to the emergency triage level. PLoS ONE 16(2): e0247042. https://doi.org/10.1371/journal.pone.0247042

Editor: Juan F. Orueta, Osakidetza Basque Health Service, SPAIN

Received: October 8, 2020; Accepted: January 31, 2021; Published: February 17, 2021

Copyright: © 2021 Jung et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the manuscript and its Supporting Information files.

Funding: The authors received no specific funding for this work.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Overcrowding in the emergency department (ED) is a serious public health issue worldwide. Overcrowding in the ED is defined as a situation in which the demand for emergency services exceeds the ability of a department to provide quality care within acceptable time frames [ 1 ]. In 2018, the number of patients who were treated in EDs in Korea was 10,609,107, which was an increase of 1.76% compared to the previous year, and the number of patients admitted through EDs grew by 2.95% compared to the previous year. In contrast, the total number of ED beds in Korea was 6,945 in 2018, which decreased by 1.68% compared to the previous year [ 2 ]. These statistics indicate that the supply volume is not meeting the growing demand for emergency care, so the overcrowding in the EDs is an ongoing public health issue in Korea.

According to the national policy, the national medical insurance program covers almost all citizens and all medical institutions in Korea. Therefore, patients can freely choose the medical institution in which they wish to receive treatment [ 3 ]. This, coupled with the preferences of patients for large medical institutions, causes an overflow of patients in the EDs of those medical institutions.

This problem of overcrowding in the ED is caused by multiple factors, which include an increasing number of incoming ED patients (input factor), a shortage of ED resources (throughput factor), and the number of admitted patients who are waiting to move from the ED to a hospital ward (output factor) [ 4 , 5 ]. Overcrowding in the ED directly decreases the quality of medical care, such as delaying medication time and increasing the mortality rate of admitted patients [ 6 , 7 ]. It also causes various indirect problems, such as prolonged waiting times, decreased patient satisfaction, and profit loss by the medical institutions [ 4 , 8 , 9 ].

Ideally, medical decisions, such as triage decisions and admission decisions, should be based on the urgency of treatment and level of treatment needed by the patient. And these decisions should not be affected by the degree of overcrowding in the ED. The Emergency Severity Index and Canadian Triage and Acuity Scale, which are well-known triage tools, have warned clinicians that the “triage drift” phenomenon, which involves the adjustment of the triage level according to the degree of overcrowding in the ED, can have a negative effect on the patient’s prognosis [ 10 – 12 ]. However, previous studies have shown that medical decisions that are related to admission or the triage level may be distorted due to overcrowding in the ED [ 13 , 14 ]. While previous research has investigated the relationship between overcrowding in the ED and the probability of admission, no studies have analyzed the characteristics of the admitted patients in the overcrowded ED environment.

An emergency triage tool is used to efficiently utilize limited medical resources in an overcrowded ED, and although various triage tools are used and differences exist in terms of their composition, a common factor is that the triage level is determined based on each patient’s overall medical condition, such as the urgency of the patient’s initial medical treatment and the severity of patient’s diseases [ 15 , 16 ]. Therefore, this study aimed to investigate the effect of overcrowding in the ED on the admission rate, and especially how it differs depending on the triage level. Furthermore, this study was the first research done on study the problem of overcrowding in the ED in terms of both triage level and the admission rate.

Materials and methods

Study population and setting.

This study was a retrospective cohort study that was conducted in one ED, which was visited by 100,000 patients in 2019. This hospital has 2,400 beds, and its ED is divided into an adult area and pediatric area. The adult practice area consists of 45 beds and 20 clinic chairs. This study included patients who were 19 years old or above and who visited the ED from January 1, 2018 to December 31, 2018.

In the research institution, the emergency physician provides primary care for all adult patients and makes decisions about admission and discharge. If the emergency physician determines that admission is necessary, the emergency physician decides the department in which the patient should be admitted and then consults with that department. And, final admission decision was made by physician who was requested consultation.

Some patients were excluded for the following reasons: canceled registration, visiting the ED other than for medical purposes, and omission of the analysis variables. In addition, patients who died before arrival or who expired in the ED were excluded because they were not considered for admission or discharge. The institutional review board of Severance Hospital approved this study, and informed consent was waived because this study was a retrospective study that analyzed previously collected medical records. (Approval number: 4-2020-0023)

The Korean Triage and Acuity Scale

The Korean Triage and Acuity Scale (KTAS) was used as the emergency triage tool. The KTAS is a five-level triage tool that was developed based on the Canadian Triage and Acuity Scale [ 17 ]. The KTAS determines the patient’s priority for treatment by providing possible waiting time for treatment based on patient’s main symptoms, vital signs, and intensity of pain. In Korea, KTAS is used as a triage tool in all EDs and to triage, triage staff must complete six hours of a regular education session conducted by the Korean Society of Emergency Medicine according to the national policy. So all of the triage staff of this institution had completed regular education session. Ambulatory patients were triaged by nurses, and patients who were transferred by an ambulance were triaged by physicians.

Study variables

The research data were extracted from the electronic medical record system of Severance Hospital in Korea, which data were completely anonymized during the extraction process. Among the study population, the date on which the last patient left the ED was January 6, 2019. Therefore, the period for collecting medical records was from January 1, 2018 to January 6, 2019. Basic demographic information was collected, such as age, sex, ambulance arrival, ED arrival time and medical/non-medical problems. If the patients’ problems were caused by external environmental factors, such as trauma and intoxication, this study defined these as non-medical problems. If the problems had not happened due to external factors, they were defined as medical problems. The complaint category variables were sorted by bodily system into 17 different categories based on the patients’ symptoms and they were used when the KTAS was employed to triage patients. When the data were analyzed, we included seven categories that were applied for more than 5% of the total number, and the remaining categories were labeled as “others.” The patient group who arrived during the day shift time (08:00–17:59), which is the regular bed assignment time, was defined as the day shift time arrival, and the patient group who arrived at other times was defined as the non-day shift time arrival. The research institute’s electronic medical recording system automatically records the number of patients in the adult area and pediatric areas every 10 minutes. This number includes the total number of patients in both the treatment and waiting areas; hence, these data were used. The number of patients at the time (the minute of each patient’s arrival time was rounded-up from the original time) was used as the standard value in this study. The patients were divided into three different groups based on the tertiles of the number of patients: a high overcrowding group (HOG), low overcrowding group (LOG), and non-overcrowding group (NOG). The outcome variable was whether the patient was admitted or not. Admission was defined as the situation wherein a patient was actually admitted to an inpatient bed. Therefore, even if the patient was in the ED for a long time, and if the destination at the time of leaving the ED was an inpatient bed, it was classified as admission.

Statistical analysis

SAS (version 9.3, SAS Institute Inc., Cary, NC, USA) was used for the statistical analysis. Categorical variables were presented as n (%), and continuous variables were presented as the median (inter-quartile range). To compare the demographic data, the chi-square test was used for the categorical variables. The Kruskal-Wallis test was used for the continuous variables because they did not have a normal distribution. To analyze the correlation between ED overcrowding and the admission rate according to the KTAS level, the entire patient group was divided into five groups according to the KTAS level, and an individual analysis was performed. By using logistic regression, the results were presented as adjusted odds ratios, which were obtained after applying the adjustment variables, such as age, sex, medical/non-medical problem, use of an ambulance, complaint category, and day shift time arrival / non-day shift time arrival. When comparing the degree of overcrowding, the NOG was set as the reference group. In addition, the linear predictor of each KTAS group was extracted by using logistic regression not only for the group comparisons but also to calculate the changes in the admission rate according to the increasing number of patients in the ED.

During the study period, the total number of patients who visited the ED was 112,178. Of these, 36,248 patients who were aged under 19 years, 1,611 patients who visited the ED other than for medical purposes, and another 543 patients who met the aforementioned exclusion criteria, were excluded from this study ( Fig 1 ). The final number of enrolled patients was 73,776. The number of admitted patients was 17,499 (23.7%). The number of patients in the ED at any given time ranged from 12 to 98. Based on the number of patients in the ED at the time of arrival of each patient, patients were classified into three different groups. If the number of patients ranged from 12 to 49, they were classified into NOG. If it ranged from 50 to 62, they were classified into LOG, and if it ranged from 63 to 98, they were classified into the HOG. The number of patients in each group was 24,977 (33.9%), 23,714 (32.1%), and 25,085 (34%), respectively. The collected information is presented in Fig 1 .

• PPT PowerPoint slide
• PNG larger image
• TIFF original image

ED, emergency department; NOG, non-overcrowding group; LOG, low overcrowding group; HOG, high overcrowding group.

https://doi.org/10.1371/journal.pone.0247042.g001

Characteristics of the patients

The median age of the patients was 54 years (24–69), and there were 39,655 female patients (53.8%). When comparing the groups, patients in the HOG had the highest median age and this group had the lowest proportion of patients who had non-medical problems. In addition, the admission rate was high. The proportion of patients classified into KTAS levels 1–3, which are considered to be relatively high-emergency grades, was 33.5% in the HOG, 30.3% in the LOG, and 30.9% in the NOG. The demographic information is provided in Table 1 .

https://doi.org/10.1371/journal.pone.0247042.t001

Differences in the admission rates of each ED overcrowding group

The analysis of all of the patients indicated that the admission rate increased as the ED overcrowding grew. The odds ratios for admission gradually rose to 1.106 (95% confidence interval [CI]: 1.057, 1.159) and 1.281 (1.225, 1.339), respectively, as the overcrowding increased to the LOG and HOG compared to the NOG ( p < 0.001). In the analysis according to the KTAS level, the odds ratio for admission in KTAS group 2 tended to rise as the overcrowding increased, although there was no statistically significant difference. However, in the groups with a KTAS level of 3 or lower, the admission rate increased as the overcrowding rose. As the ED overcrowding changed from non to low and high, the odds ratios for admission were 1.109 (1.020, 1.206) and 1.215 (1.120, 1.317) in KTAS group 3, 1.100 (1.027, 1.178) and 1.294 (1.211, 1.382) in KTAS group 4, and 1.407 (1.149, 1.722) and 1.954 (1.614, 2.365) in KTAS group 5, respectively, which were statistically significant. Table 2 presents the odds ratios for admission according to the overcrowding groups.

https://doi.org/10.1371/journal.pone.0247042.t002

Differences in the admission rates according to the increase in the number of patients in the ED

The difference in the admission rates due to the increase in the number of existing patients in the ED was the same as in the above inter-group comparison. No statistically significant correlations were found in KTAS groups 1 and 2 for changes in the admission rate as the number of existing patients grew; however, a statistically significant relationship was found in KTAS groups 3 to 5 ( p < 0.001). In addition, the lower the KTAS level, the greater the increase in the admission rate as the number of existing ED patients rose (the coefficient of KTAS level 3 = 0.00576, the coefficient of KTAS level 4 = 0.00747, and the coefficient of KTAS level 5 = 0.01930) ( Fig 2 ).

KTAS, Korean Triage and Acuity Scale; ED, emergency department.

https://doi.org/10.1371/journal.pone.0247042.g002

This study found that the greater the overcrowding in the ED, the greater the likelihood of the patients being admitted. In addition, the findings indicated that the impact of the overcrowding on the admission rate was greater in the patient groups with a lower triage level (KTAS 3, 4, and 5).

Previous studies have analyzed the correlation between overcrowding in the ED and the admission rates. In 2019, Chen et al. reported that the odds ratio of a patient being admitted when the number of patients in the ED increased by one was 1.007 (95% CI: 1.006, 1.008) [ 13 ]. In addition, in 2017, Gorski et al. stated that as the number of patients waiting for ED treatment grew, the odds ratio to be admitted was 1.011 (95% CI: 1.001, 1.020) [ 14 ]. In our study, as the total number of ED patients increased, the odds ratio of the patients being admitted was 1.007 (95% CI: 1.006, 1.008), which is similar to that of previous studies. Therefore, this result strongly supports the previous research.

Some studies have explained that the cause of this phenomenon is the admission of patients in the “gray zone,” which is in the boundary between admission and discharge, when the ED is overcrowded. The changes in the physicians’ decision-making process can be explained as follows. As the number of ED patients rises, the amount of patients that the physicians have to deal with simultaneously increases, which causes information overload for the doctors [ 14 ]. Along with this, their mental resources become depleted when repeated decisions related to the ED patients’ dispositions are made without adequate resting time [ 18 ]. Both of these situations lead to the decision-makers avoiding difficult choices and simplifying their decision-making. As a result, physicians are more likely to avoid additional assessments, judgments, or discharge plans that need to be implemented for safe discharge and they are more likely to make easier admission decisions.

Although previous studies have reasonably suggested the above mentioned reasons, they have not been able to provide information about the actual changes in the admission rate of patients with certain characteristics. Emergency triage tools evaluate the patients’ overall medical condition, such as the urgency and severity of their problem; however, the emergency triage level is not an absolute measure of the need for admission. Nevertheless, in general, when emergency physicians use the KTAS, which is a five-step emergency classification triage tool, they recognize that KTAS levels 1 and 2 are severe emergency patients, KTAS levels 3 and 4 are general emergency patients, and those with KTAS level 5 are non-emergency or mild illness patients. Therefore, from the perspective of emergency medical personnel, and assuming that patients considered to be in the gray zone are included in KTAS groups 3 and 4, and this study was conducted to confirm the hypothesis that was suggested from the previous studies. However, our results confirmed that the admission rate of non-emergency patients who were triaged as level 5, who were not assumed to be gray-zone patients, also increased. This can be due to the influence of the characteristics of the patient group in the hospital where this research was conducted. This study was performed in a tertiary referral hospital where the ratio of patients who have severe underlying diseases, such as cancer, autoimmune diseases, and organ transplants, is comparatively very high. However, in the KTAS triage tool used in this study, patients’ underlying conditions are not considered, other than immunosuppressed conditions in fever patients and hemorrhagic tendency with bleeding [ 17 ]. Therefore, the degree of the emergency of the patients visiting the ED with severe underlying chronic symptoms or diseases could be relatively under-triaged. In fact, among the 818 patients who were triaged as KTAS level 5 and admitted to the hospital, about 270 had a history of malignant tumor, and about 40 were identified as having received transplantations. Therefore, it is assumed that there were a number of gray-zone patients among those who were classified into the KTAS group 5.

There are several limitations to this study. First, this research was conducted with a sample from a single institution; therefore, the results of this study cannot be generalized to all medical institutions. Therefore, additional research is needed that involves multi-center studies. Second, the degree of ED overcrowding is usually evaluated through various factors, such as the number of ED beds and hospital beds, the number of patients in the ED, the number of admitted patients, the number of respirators in the ED, the longest admitted time, and the waiting room time of the last patient [ 19 ]. However, in this study, overcrowding was assessed only by the number of ED patients, and other factors were not evaluated. Third, the physicians who made the admission decisions changed during the study period according to the regular ED duty schedule of the research institution. Therefore, we cannot rule out the possibility that differences in the individual physicians’ inclinations about the patients’ admission influenced their decision-making. Finally, in this study, only the trend in the patients’ admission rate was confirmed, and the appropriateness of each individual admission was not evaluated.

Conclusions

This study found that there is a positive relationship between overcrowding in the ED and the admission rate of patients, and this effect increases for those patients who are triaged as having a lower acuity level. These results suggest that overcrowding in the ED possibly causes multiple problems, such as the unnecessary consumption of medical resources and needless admissions.

Supporting information

S1 data. raw data used in this study..

https://doi.org/10.1371/journal.pone.0247042.s001

• View Article
• PubMed/NCBI
• Google Scholar
• 2. National Emergency Medical Center. Emergency Medical Statistical Yearbook 2018. [posted 2019 Aug 26; cited 2020 Oct 02]: [126p]. Available from: https://www.e-gen.or.kr/nemc/statistics_annual_report.do .

• Search by keyword
• Search by citation

Page 1 of 23

Case series: star anise toxicity presenting to the emergency department in Eastern Regional Referral Hospital in Bhutan

Star anise fruit has been used in spice in Asian cuisine, ingredient for traditional medicines, component for antiviral drugs and as parts of tea and beverage across the globe. Toxicity from these plants has b...

• View Full Text

Provider perception of presentations with nonspecific back pain in the emergency department and primary care practices: a semi-structured interview study

Increasing numbers of patients treated in the emergency departments pose challenges to delivering timely and high-quality care. Particularly, the presentation of patients with low-urgency complaints consumes r...

Surviving a classic heat stroke/hyperthermia > 42 °C – a case report

Classic heat stroke is a severe trauma which can lead to multi-organ dysfunctions and is associated with a high mortality.

Emergency department service utilisation of older patients with urgent conditions: a cross-sectional observational study

As with many countries worldwide, Singapore is experiencing a rapidly ageing population. Presentation of older persons for urgent but non-emergent conditions to the Emergency Department (ED) represents a growi...

Posterior reversible encephalopathy syndrome (PRES) on the second postpartum day: learning experience from a case report and literature review

Posterior reversible encephalopathy syndrome (PRES) is an uncommon neurological disorder which is characterised by variable symptoms. The transient clinical condition may be underestimated and misdiagnosed as ...

Aortoesophageal fistula with hemorrhagic shock successfully treated with resuscitative endovascular balloon occlusion of the aorta

Aortoesophageal fistula (AEF) is a rare cause of upper gastrointestinal hemorrhage. Despite diagnostic and therapeutic advances, the mortality rate in AEF patients remains high because of its fulminant course,...

Evaluation of advanced multi-purpose trauma moulage-based training on clinical skills for dealing with trauma-affected individuals in undergraduate nursing students

Simulation-based training courses have been developed and widely accepted.The use of simulators can prevent bitter consequences that may sometimes put human lives in danger. Increasing the skill of nursing stu...

Cervical epidural hematoma: a case series highlighting uncommon causes

Cervical epidural hematoma (CEH) is a rare but potentially devastating condition, characterized by the accumulation of blood within the epidural space of the cervical spine, leading to spinal cord compression ...

Decrease of haemoconcentration reliably detects hydrostatic pulmonary oedema in dyspnoeic patients in the emergency department – a machine learning approach

Haemoglobin variation (ΔHb) induced by fluid transfer through the intestitium has been proposed as a useful tool for detecting hydrostatic pulmonary oedema (HPO). However, its use in the emergency department (...

Management of gunshot injury to the abdominal aorta and inferior vena cava: a case report of a combat patient wounded in the Russo-Ukrainian war

Russo-Ukrainian war is associated with severe traumas, including injuries to the major vessels. Penetrating aortic injury remains one of the most difficult injuries; the mortality rate is 90–100% in case of gu...

Entrustable professional activities, emergency medicine and medical education: a systematic review

Entrustable professional activities (EPAs) are one way to assess competencies, and are designed to bridge the gap between theoretical competencies and real world clinical practice.

Unexpected Grave’s-induced acute myocardial infarction in a young female, a literature review based on a case report

Myocardial ischemia can occur due to several causes, which result in an imbalance between the supply and demand of oxygen to cardiac muscles. One potential reason for this condition is the overwork of the hear...

Utility of pelvic examination in assessing women with bleeding in early pregnancy: a multicenter Canadian emergency department study

Bleeding in early pregnancy is a common emergency department (ED) presentation. Although variability in approaches has been demonstrated, research is relatively uncommon on practices and outcomes. This study i...

Emergency care via video consultation: interviews on patient experiences from rural community hospitals in northern Sweden

Delivering emergency care in rural areas can be challenging, but video consultation (VC) offers opportunities to make healthcare more accessible. The communication and relationship between professionals and pa...

An unsuspected extracranial internal carotid pseudoaneurysm following dog bites: a case report and review of literature

Extracranial internal carotid artery (ICA) pseudoaneurysm is a rare condition that can be caused either by penetrating or blunt trauma, including dog bites, which is an uncommon occurrence. Together with the p...

Vaping-associated illness: a reassessment

In 2019, there was widespread presentation of respiratory distress as well as other organ system involvement in patients with a history of vaping. There continue to be reports of vaping-associated illness (VAI...

Cytokine release syndrome following COVID-19 infection during treatment with nivolumab for cancer of esophagogastric junction carcinoma: a case report and review

Cytokine release syndrome (CRS) is an acute systemic inflammatory syndrome characterized by fever and multiple organ failure, which is triggered by immunotherapy or certain infections. Immune checkpoint inhibi...

Incidence, characteristics, and prehospital outcomes of out-of-hospital cardiac arrest in Qatar: a nationwide gender-based investigation

Research on incidence and characteristics of Out-of-Hospital Cardiac Arrest (OHCA) in the Middle East is limited. We assessed the incidence, prehospital characteristics, and outcomes of OHCA in Qatar, a Middle...

Neuraxial anesthesia for non-neurological emergency surgery in a patient with acute ischemic stroke: a case report

The recent guidelines recommend delaying elective non-neurological surgery after an index stroke, but there is a lack of consensus regarding emergency surgery in patients with a recent stroke. Impaired cerebra...

Safety of adenosine for pediatric tachyarrhythmia treatment in the emergency department: a multi-hospital 10-year cross-sectional study

Supraventricular tachycardia is the most common dysrhythmia in children. Initial vagal maneuvers are successful less than half of the time. Adenosine, a potent AV nodal blocker with a short half-life, is recom...

Rupture of a calcified right ventricle to pulmonary artery homograft by balloon dilation– emergency rescue by venus P-Valve

Percutaneous pulmonary valve implantation (PPVI) is a recognized alternative treatment to surgery for patients with dysfunctional right ventricular outflow tracts. Patient selection is essential to avoid serio...

U-shaped correlation of lymphocyte count with all-cause hospital mortality in sepsis and septic shock patients: a MIMIC-IV and eICU-CRD database study

In sepsis, the relationship between lymphocyte counts and patient outcomes is complex. Lymphocytopenia and lymphocytosis significantly influence survival, illustrating the dual functionality of lymphocytes in ...

Diagnostic laparoscopy with indocyanine green fluorescence test for the evaluation of intestinal perfusion in abdominal blunt injury: a case report

The indocyanine green (ICG) fluorescence test has become a standard test in surgical procedures, facilitating the assessment of blood perfusion in real-time. While its utility in emergency surgeries for evalua...

Extended reality training for mass casualty incidents: a systematic review on effectiveness and experience of medical first responders

Mass casualty incidents (MCI) are unforeseeable and complex events that occur worldwide, therefore enhancing the training that medical first responders (MFRs) receive is fundamental to strengthening disaster p...

IFEM model curriculum: emergency medicine learning outcomes for undergraduate medical education

The International Federation for Emergency Medicine (IFEM) published its model curriculum for medical student education in emergency medicine in 2009. Because of the evolving principles of emergency medicine a...

Mortality and morbidity associated with new onset acute kidney injury in critically ill COVID-19 infection patients

The recent global pandemic due to severe acute respiratory syndrome coronavirus-2 resulted in a high rate of multi-organ failure and mortality in a large patient population across the world. As such, a possibl...

The MINUTES bundle for the initial 30 min management of undifferentiated circulatory shock: an expert opinion

Acute circulatory shock is a life-threatening emergency requiring an efficient and timely management plan, which varies according to shock etiology and pathophysiology. Specific guidelines have been developed ...

Catecholamine concentration as a predictor of mortality in emergency surgical patients

Trauma and emergency surgery are major causes of morbidity and mortality. The objective of this study was to determine whether serum levels of epinephrine and norepinephrine are associated with aging and morta...

A diagnostic dilemma: distinguishing a sulfasalazine induced DRESS hypersensitivity syndrome from a CD30 + lymphoma in a young patient

Drug reaction with eosinophilia and systemic symptoms (DRESS) is a severe hypersensitivity reaction characterized by cutaneous rash, lymphadenopathy, fever, eosinophilia, leukocytosis, and life-threatening org...

Comparing online and onsite simulation modules for improving knowledge and confidence in disaster preparedness among undergraduate medical students

Disaster preparedness is one of the critical strategies for effectively managing disasters and has been an area of high focus in the healthcare sector over the past few decades. The current Indian medical unde...

“Iliacus muscle abscess as an unexpected cause of posterior hip pain in a healthy young adult female”: a case report

Iliacus muscle abscess is an uncommon but potentially life-threatening condition that can present with nonspecific symptoms, posing diagnostic challenges. This case report highlights the importance of consider...

Dabigatran accumulation in acute kidney injury: is more better than less to prevent bleeding? A case report

Dabigatran is an oral anticoagulant that is mainly renally excreted. Despite its efficacy in preventing thromboembolic events, concerns arise regarding bleeding complications in patients with acute kidney inju...

Airway breathing circulation dengue: a case of multifactorial shock due to major trauma and severe dengue infection

Dengue is the most common arboviral illness reported globally, endemic to most tropical and sub-tropical regions of the world. Dengue Shock Syndrome is a rare complication of severe Dengue infection resulting ...

Treatment strategy for compartment syndrome at multiple regions due to injuries caused by a tree fall: a case report

Compartment syndrome commonly occurs in patients with forearm and lower leg fractures. Compartment syndromes of the gluteal and thigh muscles are less common. It is imperative that compartment syndrome be diag...

Early colonic-preparation and salvage laparoscopic appendectomy (ECSLA)- innovative protocol for the management of magnets ingestion

Ingestion of magnets carries risks for significant morbidity. We propose a new protocol designed to reduce the need for surgery, shorten length of stay, and decrease morbidity.

Successful management of a delayed presentation of traumatic descending thoracic aorta pseudoaneurysm: a literature review based on a case report

Blunt traumatic aortic injury (BTAI) is the second leading cause of death due to traumas in young patients. The primary presentation might be chest or interscapular pain, difficulty in breathing, and, in sever...

Do-not-attempt-resuscitation decision making: physicians’ recommendations differ from the GO-FAR score predictions

In-hospital cardiac arrest (IHCA) is a major cause of mortality globally, and over 50% of the survivors will require institutional care as a result of poor neurological outcome. It is important that physicians...

Severe COVID-19 multisystem inflammatory syndrome versus severe dengue in children from Indonesia: a cross-sectional study

Severe multisystem inflammatory syndrome in children (MIS-C) and severe dengue are challenging to identify during the COVID-19 pandemic in dengue-endemic areas. Fever, multiorgan involvement, and shock charact...

Creating a master training rotation schedule for emergency medicine residents and challenges in using artificial intelligence

The allocation of resident physicians to clinical rotations presents a complex challenge that requires balancing multiple objectives with the goals of providing optimal patient care, maintaining adequate depar...

Violence in the emergency department: a quantitative survey study of healthcare providers in India

Workplace violence (WPV) in Emergency Departments (EDs) is an increasingly recognized challenge healthcare providers face in low-resource settings. While studies have highlighted the increased prevalence of WP...

Low-dose tenecteplase during cardiopulmonary resuscitation in massive pulmonary embolism

We report the case of an 18-year-old male who presented to the Emergency Department with sudden onset dyspnea. The patient was intubated on arrival, but suffered a cardiac arrest soon after. Point-of-care echo...

Paracetamol overdose causing acute kidney injury without hepatotoxicity: a case report

Paracetamol is a widely used analgesic and antipyretic. Paracetamol-induced hepatotoxicity is well known, but nephrotoxicity without hepatotoxicity is rarely seen.

The wolf in sheep’s clothing: vasovagal syncope in acute aortic dissection

The presentation of acute aortic dissection can pose a challenge for emergency physicians, as it may occur without pain. Atypical presentations can lead to significant delays in diagnosis and increased mortali...

A rare cause of abdominal pain in pregnancy - mesenteric artery thrombosis and miscarriage in a 34-year-old patient

Mesenteric arterial thrombosis is an extremely rare thrombotic event, especially during pregnancy, that can cause rapid fatal consequences unless the patient receives early definitive treatment.

A potentially lifesaving error: unintentional high-dose adrenaline administration in anaphylaxis-induced cardiac arrest; a case report

Cardiopulmonary resuscitation is a crucial skill for emergency medical services. As high-risk-low-frequency events pose an immense mental load to providers, concepts of crew resource management, non-technical ...

Beyond urinalysis: evaluation of various clinical and laboratory reflex criteria to warrant urine culture collection in the emergency department

Clinical criteria are essential for diagnosing urinary tract infections (UTIs) followed by urine testing, including urinalysis (UA). No study has evaluated the potential related factors that may guide the appr...

Identifying trigger cues for hospital blood transfusions based on ensemble of machine learning methods

Traumatic shock is the leading cause of preventable death with most patients dying within the first six hours from arriving to the hospital. This underscores the importance of prehospital interventions, and gr...

Emergency medicine residents’ learning curve in diagnosing deep vein thrombosis with 3-point venous point-of-care ultrasound

Many cases of deep vein thrombosis (DVT) are diagnosed in the emergency department, and abbreviated lower extremity venous point-of-care ultrasound (POCUS) has already shown an accuracy comparable to that of s...

Mortality predictors in patients with suspected sepsis in the emergency department of a tertiary care hospital: a retrospective cohort study

Sepsis remains a worldwide major cause of hospitalization, mortality, and morbidity. To enhance the identification of patients with suspected sepsis at high risk of mortality and adverse outcomes in the emerge...

Clinical and laboratory parameters as predictors of mortality in patients with chronic liver disease presenting to emergency department- a cross sectional study

The World Health Organization (WHO) reports that Asia and Africa have the highest Chronic Liver Disease (CLD) mortality rate. Cirrhosis, responsible for 22.2 fatalities per 100,000 people, is India’s 10th most...

• Editorial Board
• Manuscript editing services
• Instructions for Editors
• Sign up for article alerts and news from this journal
• Follow us on Twitter

Annual Journal Metrics

Citation Impact 2023 Journal Impact Factor: 2.0 5-year Journal Impact Factor: 2.3 Source Normalized Impact per Paper (SNIP): 1.157 SCImago Journal Rank (SJR): 0.700 Speed 2023 Submission to first editorial decision (median days): 27 Submission to acceptance (median days): 134 Usage 2023 Downloads: 985,950 Altmetric mentions: 682

• More about our metrics
• ISSN: 1865-1380 (electronic)
• ISSN: 1865-1372 (print)

International Journal of Emergency Medicine

ISSN: 1865-1380

• General enquiries: [email protected]

The Productivity of Professions: Evidence from the Emergency Department

This paper studies the productivity of nurse practitioners (NPs) and physicians, two professions performing overlapping tasks but with starkly different backgrounds, training, and pay. Using quasi-experimental variation in patient assignment to NPs versus physicians in Veterans Health Administration emergency departments, we find that, on average, NPs use more resources and achieve less favorable patient outcomes than physicians. However, the NP-physician performance difference varies by case complexity and severity. Importantly, even larger productivity variation exists within each profession, leading to substantial overlap between the productivity distributions of the two professions; NPs perform better than physicians in 38 percent of random pairs.

We are grateful to Ricardo Alonso, Sandy Black, Kate Bundorf, Marika Cabral, David Card, Stuart Craig, Janet Currie, Shooshan Danagoulian, Qing Gong, Joshua Gottlieb, Mitch Hoffman, Tom Hubbard, Bapu Jena, Amanda Kowalski, Brad Larsen, Darren Lubotsky, Bentley MacLeod, Neale Mahoney, Benjamin McMichael, David Molitor, Jessica Monnet, Ciaran Phibbs, Maria Polyakova, Julian Reif, Michael Richards, Steve Rivkin, Evan Rose, Susan Schmitt, Molly Schnell, Brad Shapiro, Isaac Sorkin, Chris Walters, and many seminar and conference participants for helpful comments and suggestions. Sam Bock, Noah Boden-Gologorsky, Damien Dong, Akriti Dureja, Jesse Kozler, Matthew Merrigan, Francis Peng, Jonatas Prates, Aadit Shah, Kemin Wang, Justine Weng, Sam Wylde, Melinda Xu, and Saam Zahedian provided excellent research assistance. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

MARC RIS BibTeΧ

Download Citation Data

• October 26, 2022
• June 20, 2023

Working Groups

Conferences, mentioned in the news, more from nber.

In addition to working papers , the NBER disseminates affiliates’ latest findings through a range of free periodicals — the NBER Reporter , the NBER Digest , the Bulletin on Retirement and Disability , the Bulletin on Health , and the Bulletin on Entrepreneurship  — as well as online conference reports , video lectures , and interviews .

• Feldstein Lecture
• Presenter: Cecilia E. Rouse

• Methods Lectures
• Presenter: Susan Athey

• Panel Discussion
• Presenters: Karen Dynan , Karen Glenn, Stephen Goss, Fatih Guvenen & James Pearce

• Research article
• Open access
• Published: 17 June 2020

Waiting times in emergency departments: a resource allocation or an efficiency issue?

• Milena Vainieri   ORCID: orcid.org/0000-0002-0914-4487 1 ,
• Cinzia Panero 2 &
• Lucrezia Coletta 3  

BMC Health Services Research volume  20 , Article number:  549 ( 2020 ) Cite this article

15k Accesses

10 Citations

12 Altmetric

Metrics details

In recent years, the flow of patients to the Emergency Departments (ED) of Western countries has steadily increased, thus generating overcrowding and extended waiting times. Scholars have identified four main causes for this phenomenon, related to: continuity of primary care services; availability of specific clinical pathways for chronic patients; ED’s personnel endowment; organization of the ED. This study aims at providing a logical diagnostic framework to support managers in investigating specific solutions to be applied to their EDs to cope with high ED waiting times. The framework is based on the ED waiting times and ED admission rate matrix. It was applied to the Tuscan EDs as illustrative example.

To provide the factors to be analyzed once the EDs are positioned into the matrix, a list of issues has been identified. The matrix was applied to Tuscan EDs. Data were collected from the Tuscan performance evaluation system, integrated with specific data on Tuscan EDs’ personnel. The Tuscan EDs matrix, the descriptive statistics for each quadrant and the Spearman’s rank correlation analysis among waiting times, admission rates and a set of performance indicators were conducted to help managers to read the phenomena that they need to investigate.

The combined reading of the correlations and waiting times-admission rates matrix shows that there are no optimal rules for all the EDs in managing admission rates and waiting times, but solutions have to be found considering mixed and personalized strategies.

Conclusions

The waiting times-admission rates matrix provides a tool able to support managers in detecting the problems related to the management of ED services. In particular, using this matrix, healthcare managers could be facilitated in the identification of possible solutions for their specific situation.

Peer Review reports

In recent years, in many Western countries the flow of patients to the Emergency Departments (ED) has constantly increased [ 1 ]. This flow has often determined the ED overcrowding [ 2 , 3 , 4 , 5 , 6 ], that occurs every time the number of the waiting patients exceeds the available resources, in terms of beds and/or personnel. Therefore, overcrowding is a phenomenon that seriously limits the hospital functions [ 7 ] in terms of both delays in the patients’ care and poorer outcomes [ 8 , 9 , 10 , 11 ]. Overcrowding is also associated to the dissatisfaction of both physicians and nurses, working under pressure, and patients waiting to be treated [ 12 ]. In particular, the waiting times are among the most important causes of ED patient dissatisfaction [ 8 ] and they negatively influence patients’ perception of the service quality [ 13 ]. Complaints of dissatisfied patients are often vividly reported on the media thus causing pressure on policy makers and hospital managers.

This trend seems irreversible, because it is based on the evolution of health expectations and needs of the populations. This led a high number of scholars focusing on the factors affecting the overcrowding and ED waiting time.

In particular, these factors can be grouped into four main categories: 1) how primary care and continuity are organized; 2) the existence and effectiveness of organizational models and clinical pathways for chronic patients; 3) the presence of bottlenecks related to ED’s personnel or equipment endowment; 4) how the ED is organized and its connection with the rest of the hospital. The first two are related to the admissions to the ED services, the others to the way the ED and the hospital are organized to manage the flow of the patients.

With reference to the first group of factors, how primary care and continuity are organized, some authors underlined that overcrowding may depend on the high number of non-urgent patients seeking help from the ED [ 14 , 15 ], while these patients could turn to other health settings, namely primary care. There could be several reasons behind this patient’s choice such as the capacity of ED to provide a full, timely service, including diagnosis and examinations [ 16 , 17 ] as well as the higher perceived quality of ED services [ 18 ]. However, there are scholars outlining that admissions to the EDs are higher when there are problems related to the supply side, in particular when primary care services fail to respond to patients’ needs [ 17 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ].

The second group of factors influencing the ED admissions is related to the existence and effectiveness of organizational models and clinical pathways for chronic patients. Indeed, since the beginning of 2000 disease management programs have been proposed, like the chronic care management [ 26 , 27 ] with the aim to improve the health conditions of the patients [ 28 ], by identifying the health needs before the disease appears or it becomes serious. These programs may be particularly relevant to cope with potential avoidable ED access, considering that chronic patients are frequent users (i.e. patients with at least four ED admissions per year) [ 29 , 30 , 31 , 32 , 33 ].

A third group of factors influencing the waiting times in ED is related to potential bottlenecks such as the ED structural endowment of physicians and nurses (and rooms). Some studies outlined that the waiting times may depend on the insufficient number of physicians and nurses [ 34 , 35 , 36 ] or equipment like the existence of diagnostic imaging reserved to the ED [ 37 , 38 ].

The last group of factors influencing the ED overcrowding and the waiting times concerns how the ED is organized and its integration with the rest of the hospital. For instance, the existence of fast track for specific health problems (such as pregnancy or eye issues) may reduce waiting times because patients going to ED for these conditions have been taken in care directly by the specialists’ ambulatories or wards thus helping the ED personnel to cope with the visits’ demand [ 37 , 38 ].

Another aspect related to the organization is the boarding, that occurs when patients needing a hospitalization have to wait in the ED because the ward beds are not available [ 3 , 35 , 39 , 40 ]. This implies that the effort of ED personnel is diverted, at least in part, from the new patients that come to the ED because they have to pay attention also to patients waiting for being hospitalized [ 41 ].

To support hospital managers to cope with the third and the fourth groups of factors affecting the ED waiting times, some scholars have proposed operation or lean management approaches [ 42 , 43 ]. Whilst to cope with the first two groups of factors, many scholars suggested to re-arrange primary care or healthcare pathways. However, how to discover which is or are the factors that may affect the waiting times in a specific ED is an issue still uncovered in literature. It is a topic often left in the hands of hospital managers who have to analyze their own data. It may result also difficult because of the possible bias coming from the lack of comparisons (such as the definition of personnel endowment) or the lack of information at hospital level (such as the primary care efficiency or the effectiveness of the healthcare pathways).

This study aims at providing a logical framework that both the meso-level of government (such as Regional governments) and hospital managers can use as a logical diagnostic tool to understand their specific positioning with reference to the different potential factors influencing the ED waiting times and, therefore, to support them to find the solutions that can suit their EDs. This diagnostic logical framework was applied to the Tuscan health system to illustrate how to read it.

Methodology

Designing the logical framework to investigate ed waiting times.

To provide a diagnostic logical framework to detect the specific situation and the factors that potentially influence ED waiting times, we propose a descriptive study, based on a matrix that compares the ED waiting times with the ED admission rate. This framework has been designed and applied to other services [ 44 , 45 ]. It is based on a matrix that compare performance service waiting times and service use-rates. The position into the matrix allows to rapidly realize if the waiting times or the service use rates are higher or lower than the median of the other units observed in a specific geographical area. The four quadrants coming from the use of median value for waiting times and service use-rates identify four situations (higher waiting times higher service use rates; lower waiting times lower service use rates; higher waiting times lower service use rates; lower waiting times higher service use rates) that may require different strategies. Strategies need to be personalized on the basis of the service analyzed. Hence, in order to adapt this matrix to the ED services we followed three steps.

The first step was to select indicators that can be monitored to detect the factors associated with the ED waiting times and ED admission rates. Indicators were based on both the categories identified in the literature, reported in the first paragraph, and the consolidated experience of the performance evaluation system in the Tuscany Region [ 13 ], which is using more than 300 performance indicators also covering ED and primary care services also share with other Italian Regions [ 36 , 46 , 47 , 48 ]. This experience guarantees that the indicators’ selection already received a validation process by professionals and healthcare managers [ 36 , 47 ].

The second step was to propose for each quadrant the issues to be investigated in order to cope with ED waiting times and ED admission rates. Hence, we identified the indicators that we suggest to be analyzed for each quadrant to disentangle why the ED got that performance in terms of waiting times and admission rates.

The third step was to apply this logical framework to the real world data presenting it to ED heads of departments in the Tuscany Region. The illustrative example was coupled with the correlation analysis of the factors identified in the first step.

Study setting

This matrix was applied to the Tuscan EDs data to better highlight the support that this diagnostic logical framework can provide to managers and policymakers in coping with EDs’ waiting times.

Tuscany is a medium-size Italian Region, with a population of 3,75 million with a good level of performance of its healthcare services [ 46 ]. However, there is a wide variability of performance results among its Districts and EDs. Consistently with the international trend, the number of admissions to the Tuscan EDs increased by 5,4% in the last 7 years arriving at 1 million and half of admissions.

The service is provided by 38 EDs, which refer to 3 LHAs and 4 Teaching Hospitals, and are grouped into 25 territorial Districts.

In 2018, the overall admission rate to the EDs per 1.000 inhabitants was 361.49, with a great variability among the Districts (from 279.99 to a maximum of 556.49) and among the ED admission rate referred to minor priority codes, that which was 88.28 per 1.000 inhabitants (from 43.59 to a maximum of 146.52). With reference to the waiting times, the median waiting time is 72 min, from a minimum of 36 min to a maximum of 282 min. Urgent priority codes, which need immediate admission to the treatment, are included.

Data analysis

The analysis conducted is a qualitative description of the application of the diagnostic logical framework to the Tuscany data.

The data concerning the ED admission rates, the waiting times and the performance of primary care were retrieved from the publicly disclosed data on Tuscan performance evaluation system ( https://performance.santannapisa.it/ ); data related to personnel come from a research report [ 36 ]. For what concerns the data about the endowment of ED personnel, we used the last data available (2015), whereas all the other data are updated to 2018.

To design the matrix, we linked ED admission rates, computed at the District level, and ED waiting times, computed at the hospital level. Therefore, as a methodological criterion, for those Districts which comprehend more than one hospital, we considered the waiting times of the prevalent ED. The number of admissions of the selected EDs represents always more than 70% of the admission per inhabitants. The reference lines that identify the quadrants represent the regional median values. We reported some descriptive statistics for the four quadrants to illustrate how this matrix can help managers to detect their situation.

We reported some descriptive statistics for the four quadrants to illustrate how this matrix can help managers to detect their situation.

To complete the study a correlation analysis among variables was performed with a level of significance at 10%. We executed the Spearman’s rank correlation because most of the variables were not normally distributed. The correlation analysis may help to identify common patterns among the Tuscan EDs in association to the factors analyzed, suggesting that some issues may require a regional intervention.

The diagnostic logical framework to cope with ED waiting times

The selected indicators where presented in Table  1 . In particular, for factors related to primary care and continuity (group 1), we investigated the GP’s density; for factors related to the existence and effectiveness of chronic management programs (group 2), we considered the indicators of the avoidable hospitalizations as well as the enrolment into the Tuscan chronic care program monitored by the Tuscan performance evaluation system [ 48 ]; for factors related to the presence of bottleneck (group 3) we used the indicators coming from a Tuscan research on EDs’ personnel [ 36 ]; for factors related to EDs performance and hospitals’ organization (group 4) we considered all the indicators referred to the Tuscan performance evaluation system. These indicators cover both quality aspects (such as the number of EDs readmission) and the appropriateness (such as the percentage of hospitalized patients admitted to the ward within 8 h) [ 48 ].

Positioning the EDs inside the four quadrants allows to draw down a list of potential factors affecting that performance (see Fig.  1 ). Accordingly, specific hypotheses concerning the solution to the problems and the consequent strategies can be outlined.

A scheme for the waiting times-admission rate matrix

The EDs in the upper left quadrant (High waiting times/Low admission rate) show a good performance with reference to the admission rates but some problems to manage the waiting times. Therefore, these EDs may primarily look at solutions inside their organization. In such circumstances managers can investigate factors related to the abovementioned third and fourth groups of potential factors affecting high ED waiting times. In particular, the list of questions (not exhaustive) that hospital managers may detect are related to the ED staff endowment, staff productivity and equipment availability. Other potential factors leading to higher waiting times can be referred to the hospital organization, such as the existence of fast track paths or the capacity of the wards to rapidly take in charge those patients who need to be hospitalized. In the case of the upper right quadrant (High waiting times/High admission rate) the EDs show problems with reference to both the admission rate and the waiting times. In these circumstances the list of questions is longer because solutions may refer not only to the ED/hospital but also to the primary care. The managers could investigate a mix of issues related to all the four groups of factors identified in literature. The problems referring to the high ED admission rate pertain to the overall organization and performance of the health care system, usually outside the ED control. In particular, the factors of the first two groups refer to i) how primary care and continuity are organized; ii) the existence and effectiveness of organizational models and clinical pathways for chronic patients. Another group of issues that may affect the situation of EDs positioned in that quadrant may concern the third and fourth groups: delays both in the admission phase (for instance, in terms of presence of fast track protocols), and in the discharge phase (due, for instance, to boarding for the admission to the wards); bottlenecks concerning for instance the imaging diagnostic services and the structural efficiency (staff productivity and staff endowment).

The EDs in the bottom right quadrant (Low waiting times/High admission rate) are efficient with reference to the waiting times, but the situation may suggest a sub-optimal resource distribution among the settings of care and a potential inappropriate answer of primary care services to the health needs of the population.

The EDs that are in the bottom left quadrant (Low waiting times/Low admission rate) are in an apparently good situation where the demand (admission rate) and the waiting times seem to be under control.

Figure  2 shows how the Tuscan EDs are positioned into the matrix while Table  2 reports the descriptive statistics for each quadrant. Some distinctive traits for these four quadrants emerge from the matrix.

The ED waiting times-admission rate matrix for all the Tuscan EDs

EDs belonging to the upper-left quadrant (high waiting times/low admission rate) are characterized by the highest number of General Practitioners per 1.000 inhabitants but lower performance in the chronic management indicators. It seems to suggest that the primary care is well structured in terms of number of GPs (the first group of factors) but it is not well organized to treat chronic patient (the second group of factors). Despite the lower ED admission rates EDs of this quadrant, on average it presents a number of FTE of physicians per 10,000 admissions slightly lower than the regional mean, which could be a reason behind the higher ED waiting times (the third group of factors). In addition, with reference to the organization (the fourth group of factors), these EDs show the highest percentage of hospitalized patients and also the highest bed occupancy rate; another interesting aspect that characterizes this group of EDs is the lower recourse to the observation unit. All these aspects could be among the main causes of boarding and delay in the discharge phase.

In the upper-right quadrant (high waiting times/high admission rate) EDs show a poor primary care structure, because they have the lowest rate of GPs per inhabitant (the first group of factors), but a good performance of chronic management (the second group of factors); the personnel endowment is the lowest of the four groups which can be one of the reasons for the high ED waiting times (the third group of factors); the factors related to the organization (the fourth group) show that the bed occupancy rate is on average but these EDs seem to wait more than other to hospitalize patients in the intensive care units and have less patients in observation units although for more time. These organizational reasons may lead to higher waiting times.

The bottom right quadrant (low waiting times/high admission rates) comprehends EDs with a primary care structure slightly better than the regional average and good performance of the chronic management so that the reasons of high admission rates rely on other factors. The low waiting times are coherent with an average ED endowment of personnel. The bed occupancy rate is the lowest among the four quadrants. In addition, the Observation Unit is intensively used, above all for the short stays: this could alleviate the pressure on the wards and contributing to the highest percentage of patients hospitalized within 8 h.

The bottom left quadrant (low waiting times/low admission rates) comprehends EDs characterized by an adequate number of GPs per 1.000 inhabitants, good performance on primary care related to chronic disease management, which are coherent with a low admission rate. The low waiting times may be also explained by the highest endowment of ED personnel. Moreover, the organizational factors here investigated seem useful to reduce potential problems of boarding, such as the low bed occupancy rate and the highest percentage of access to Observation unit.

The correlation analysis

Table  3 shows the Spearman’s rank correlation matrix. It is worth to be noticed that association between ED waiting times and the ED admission rate registers a p -value higher than 0.10. Although, a high level of ED admission per inhabitants may lead to overcrowding, it seems that in Tuscany other factors (or a mix of them) may cloud out this relationship.

According to the findings of Table 3 , some common patterns seem to characterize the Tuscan EDs.

With reference to the factors related to the first group, the continuity of care, investigated looking at the number of GPs per inhabitant, seems not to be related neither to the ED waiting times nor to the ED admission rate. As regards the second group of factors, most of the indicators used as proxies to analyze chronic management suggest that better performances in chronic management are also related to lower ED waiting times.

For what concerns the factors used to analyze the presence of potential bottlenecks, from one side the number of ED FTE per 10,000 admissions is negatively correlated with ED waiting times: EDs with lower FTE per 10,000 admissions show higher level of waiting times. From the other side, the number of ED FTE per 10,000 admissions shows a moderate negative association with ED admission: EDs with lower FTE per 10,000 admissions show higher level of ED admission rates. While the first association may suggest a potential resource allocation strategy at regional level, the second one suggests that when ED admission rates are high staff endowment may be not able to timely cope with the high demand.

Finally, the most represented group of factors are those related to the organization. There are several associations among variables. In particular, higher occupancy rates are associated to higher ED waiting times, this suggests that the collaboration among hospital wards and ED is an issue that Tuscan EDs have to look at. This relationship was also found in other indicators looking for similar aspects such as the prompt admission to the hospital ward. Some organizational structures such as the Observation Unit seem to help ED to cope with high waiting times. Other associations suggest that the more EDs are able to respond to non-urgent patients treated within 4 h the higher the level ED admission rates, while the higher the percentage of ED patient hospitalized, the higher are the ED waiting times (also related to the capacity of the hospital ward to board them) as well as the lower are the ED admission rates.

Correlation analysis suggests some elements that seem to characterize Tuscan EDs, however, some elements need to be further investigated on a case based. Hence, in order to help hospital and local health authority managers to disentangle which are the issues to be investigated in their situations, the ED waiting times and admission rate matrix may be used.

The ED is part of a service delivery system, and therefore the diagnostic logical framework presented in Fig. 1 seeks to help managers to identify the flaws and the strengths of the overall system, and the mixed strategies the local or regional health system has to apply. Indeed, the matrix allows an integrated analysis that takes into account the main factors that are bivariately associated with waiting times and admission rates, for instance the organization of EDs, ED personnel endowment and performance of primary care. The formulation of hypotheses to be investigated throughout the positioning of ED into the quadrants of the matrix and the identification of an initial list of measures already identified in literature, may support managers to address the questions that primarily can be referred to their case, thus helping them to find out the solution. Hence, this approach may support regional and hospital managers to shortlist the questions they have to answer to identify which are the potential strategies that the ED or the health system can take into account in order to better manage the waiting times. While other scholars have already highlighted the importance of some factors such as the functioning of the primary care services [ 17 , 19 , 20 , 21 , 22 , 23 , 24 , 25 ] with a particular focus on programs related to chronic patients who are the among the ED frequent users [ 26 , 27 , 49 ]; the presence of bottlenecks both considering personnel [ 34 , 35 , 36 ] or equipment [ 37 , 38 ] and other organizational aspects [ 37 , 38 ], trying to find out general rules, this paper seeks to support managers and policy makers identifying those elements that specifically refers to their ED. Hence, the matrix seeks to support managers to reflect upon the application of these general rules to their case.

The descriptive statistics provide illustrative example of the suggestions coming from this diagnostic logical framework. The combined use of the matrix and the Spearman’s rank of correlation can help to understand common patterns among Tuscan EDs and more specific issues to investigate for each ED or group of EDs.

The findings of the correlation analysis highlight that resource allocation strategies and resource efficiency choices are associated to ED waiting times. In particular, FTE personnel per admission is negatively associated to ED waiting times thus suggesting that one of the factors that a regional (or meso) level of government may consider in order to better manage ED waiting times is a more equitable allocation of FTE per admissions; another aspect that may be supported at the regional level is the chronic management program, already in place in Tuscany Region. It is negatively associated to ED waiting times so that monitoring and promoting its implementation across the Tuscan districts may be one of the factors that can help managing waiting times. In addition, the regional (or meso) managers and policy makers can promote protocols to suggest the organizational choices related to hospital resource allocation (such as the use of observational units, the higher it is the lower are the ED waiting times) or to the resource efficiency (such as the bed occupancy rate, the higher it is the higher the ED waiting times) that can help containing ED waiting times.

The findings of the analysis of the four quadrants of the matrix provide empirical examples of what has been found in the Van den Heede and Van de Voorde review [ 50 ]: there is no golden rule to reduce ED waiting times or ED admission rates, so that strategies that hospital and local managers may adopt have to be personalized. Indeed, in some cases, it seems that the organizational factor that may affect the ED waiting times are the relationships with the hospital wards despite an average bed occupancy rate. While in other cases, high ED waiting times seem to be related to the primary care structure or the low performance of chronic care management.

This paper adapted the waiting times-admission rate matrix already used in other services [ 44 , 45 ] to the ED context also using the illustrative example of the Tuscan EDs. The matrix can work as a logical diagnostic tool to help managers to analyze the situation of their EDs.

A strength of this study is the classification of the main factors that previous researchers have identified as main determinants of ED admission rate and waiting times into a logical framework that can support managers to address the questions that primarily can be referred to their case, thus helping them to find out the solution. Indeed, the matrix may help to shortlist the issues to focus on, based on the ED positioning among the quadrants.

In addition, this diagnostic logical framework attempts to lead local and regional managers to cope with ED waiting times using a systemic approach, thus not only looking at the hospital or ED organization but considering also other factors that may affect their situation.

This study has a number of limitations. First, the analyses and results refer to the context of one Region (Tuscany) in one country (Italy). However, the logical framework proposed in this study as well as the kind of analyses conducted and the type of variables considered, may be easily replicated in other contexts, since they are derived from theory. The results may be different but the approach in detecting the situation of each group of EDs could be the same. Second, the waiting times-admission rates matrix presented in this study works well and it is a supportive source of information for policy makers only when there is the opportunity to compare performances and data of both EDs as well as primary care, continuity and hospital performances. Moreover, countries and regions may enrich their analyses including more indicators per group of factors.

Third, the matrix was presented and discussed in a workshop with the head of the EDs but it has not been used yet by policy makers and managers to detect the factors affecting ED waiting times.

Finally, it is worth highlighting that this study is purely descriptive, without any claim to derive causal inference from the analyses presented. The matrix developed, together with the correlations analysis, provide a picture of the actual situation characterizing the Tuscan EDs, and an interesting starting point to support healthcare managers and policy makers in the analyses and potentially solution to problems linked to high EDs waiting times or inappropriate admission rates.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Emergency department

Local health Authority

General practitioner

Full-time equivalent

% Of inhabitants > = 16 years enrolled into the TUSCAN CHRONIC CARE PROGRAMS.

Bed occupancy rate

Chronic disease management for heart failure

Chronic disease management for diabetes

Chronic disease management for obstructive pulmonary disease; % of non-urgent, not hospitalized patients admitted to the ward within 4 h

% Hospitalized ED patients within 8 h.

Observation Unit length of stay > 48 h

% Admissions to the Observation Unit.

% Of hospitalized ED patients from the Observation Unit.

% Of ED patients hospitalized in the intensive care within 24 h.

% of hospitalized ED patients.

% Repeated admissions to the ED within 72 h.

Observation Unit length of stay < 6 h

% Patients left without being seen.

Berchet C. Emergency care services: trends, drivers and interventions to manage the demand, OECD health working papers, no. 83. Paris: OECD Publishing; 2015.

Google Scholar  

Di Somma S, Paladino L, Vaughan L, Lalle I, Magrini L, Magnanti M. Overcrowding in emergency department: an international issue. Intern Emerg Med. 2015;10(2):171–5.

Article   PubMed   Google Scholar  

Richardson DB, Mountain D. Myths versus facts in emergency department overcrowding and hospital access block. Med J Aust. 2009;190(7):369–74.

Dickinson G. Emergency department overcrowding. Can Med Assoc J. 1989;140(3):270.

CAS   Google Scholar  

Andrulis DP, Kellermann A, Hintz EA, Hackman BB, Weslowski VB. Emergency departments and crowding in United States teaching hospitals. Ann Emerg Med. 1991;20(9):980–6.

Article   CAS   PubMed   Google Scholar  

Schneider SM, Gallery ME, Schafermeyer R, Zwemer FL. Emergency department crowding: a point in time. Ann Emerg Med. 2003;42(2):167–72.

American College of Emergency Physicians. Crowding. Policy Statement.2006.January.

Pines JM, Hollander JE. Emergency department crowding is associated with poor care for patients with severe pain. Ann Emerg Med. 2008;51(1):1–5.

Bernstein SL, Aronsky D, Duseja R, Epstein S, Handel D, Hwang U, et al. The effect of emergency department crowding on clinically oriented outcomes. Acad Emerg Med. 2009;16(1):1–10.

Sprivulis PC, Da Silva JA, Jacobs IG, Jelinek GA, Frazer AR. The association between hospital overcrowding and mortality among patients admitted via Western Australian emergency departments. Med J Australia. 2006;184(5):208–12.

Guttmann A, Schull MJ, Vermeulen MJ, Stukel TA. Association between waiting times and short term mortality and hospital admission after departure from emergency department: population based cohort study from Ontario, Canada. BMJ. 2011;342:d2983.

Article   PubMed   PubMed Central   Google Scholar  

Higginson I. Emergency department crowding. Emerg Med J. 2012;29(6):437–43.

Nuti S. La valutazione della performance in sanità. Bologna: Il Mulino; 2008.

Young GP, Wagner MB, Kellermann AL, Ellis J, Bouley D. Ambulatory visits to hospital emergency departments: patterns and reasons for use. Jama. 1996;276(6):460–5.

Uscher-Pines L, Pines J, Kellermann A, Gillen E, Mehrotra A. Emergency department visits for nonurgent conditions: systematic literature review. Am J Manag Care. 2013;19(1):47–59.

PubMed   PubMed Central   Google Scholar  

Marcacci L, Nuti S, Seghieri C. Migliorare la soddisfazione in Pronto Soccorso: metodi per definire le strategie di intervento in Toscana. Mecosan. 2010;74:3–18.

Coster JE, Turner JK, Bradbury D, Cantrell A. Why do people choose emergency and urgent care services? A rapid review utilizing a systematic literature search and narrative synthesis. Acad Emerg Med. 2017;24(9):1137–49.

Ragin DF, Hwang U, Cydulka RK, Holson D, Haley LL Jr, Richards CF, et al. Reasons for using the emergency department: results of the EMPATH study. Acad Emerg Med. 2005;12(12):1158–66.

Chen BK, Cheng X, Bennett K, Hibbert J. Travel distances, socioeconomic characteristics, and health disparities in nonurgent and frequent use of hospital emergency departments in South Carolina: a population-based observational study. BMC Health Serv Res. 2015;15(1):203.

Sarver JH, Cydulka RK, Baker DW. Usual source of care and nonurgent emergency department use. Acad Emerg Med. 2002;9(9):916–23.

Cowling TE, Cecil EV, Soljak MA, Lee JT, Millett C, Majeed A, et al. Access to primary care and visits to emergency departments in England: a cross-sectional, population-based study. Plos One. 2013;8(6):e66699.

Cecil E, Bottle A, Cowling TE, Majeed A, Wolfe I, Saxena S. Primary care access, emergency department visits, and unplanned short hospitalizations in the UK. Pediatrics. 2016;137(2):e20151492.

Van den Berg MJ, Van Loenen T, Westert GP. Accessible and continuous primary care may help reduce rates of emergency department use. An international survey in 34 countries. Fam Pract. 2016;33(1):42–50.

Garthwaite C, Gross T, Notowidigdo M, Graves JA. Insurance expansion and hospital emergency department access: evidence from the affordable care act. Ann Intern Med. 2017;166(3):172–9.

Fishman J, McLafferty S, Galanter W. Does spatial access to primary care affect emergency department utilization for nonemergent conditions? Health Serv Res. 2018;53(1):489–508.

Wagner EH, Davis C, Schaefer J, Von Korff M, Austin B. A survey of leading chronic disease management programs: are they consistent with the literature? J Nurs Care Qual. 2002;16(2):67–80.

Article   Google Scholar  

Bodenheimer T, Wagner EH, Grumbach K. Improving primary care for patients with chronic illness. Jama. 2002;288(14):1775–9.

Coleman K, Austin BT, Brach C, Wagner EH. Evidence on the chronic care model in the new millennium. Health Affair. 2009;28(1):75–85.

Althaus F, Paroz S, Hugli O, Ghali WA, Daeppen JB, Peytremann-Bridevaux I, Bodenmann P. Effectiveness of interventions targeting frequent users of emergency departments: a systematic review. Ann Emerg Med. 2011;58(1):41–52.

Hoot NR, Aronsky D. Systematic review of emergency department crowding: causes, effects, and solutions. Ann Emerg Med. 2008;52(2):126–36.

Pines JM, Asplin BR, Kaji AH, Lowe RA, Magid DJ, Raven M, et al. Frequent users of emergency department services: gaps in knowledge and a proposed research agenda. Acad Emerg Med. 2011;18(6):e64–9.

Bieler G, Paroz S, Faouzi M, Trueb L, Vaucher P, Althaus F, et al. Social and medical vulnerability factors of emergency department frequent users in a universal health insurance system. Acad Emerg Med. 2012;19(1):63–8.

Hudon C, Courteau J, Krieg C, Vanasse A. Factors associated with chronic frequent emergency department utilization in a population with diabetes living in metropolitan areas: a population-based retrospective cohort study. BMC Health Serv Res. 2017;17(1):525.

Lambe S, Washington DL, Fink A, Laouri M, Liu H, Fosse JS, et al. Waiting times in California's emergency departments. Ann Emerg Med. 2003;41(1):35–44.

Trzeciak S, Rivers EP. Emergency department overcrowding in the United States: an emerging threat to patient safety and public health. Emerg Med J. 2003;20(5):402–5.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Panero C, Nuti S, Marcacci L, Rosselli A. Il quaderno del Pronto Soccorso. Firenze: Polistampa Editore; 2016.

Cooke MW, Wilson S, Pearson S. The effect of a separate stream for minor injuries on accident and emergency department waiting times. Emerg Med J. 2002;19(1):28–30.

Sanchez M, Smally AJ, Grant RJ, Jacobs LM. Effects of a fast-track area on emergency department performance. J Emerg Med. 2006;31(1):117–20.

Elder E, Johnston AN, Crilly J. Systematic review of three key strategies designed to improve patient flow through the emergency department. Emerg Med Australas. 2015;27(5):394–404.

Moskop JC, Sklar DP, Geiderman JM, Schears RM, Bookman KJ. Emergency department crowding, part 1—concept, causes, and moral consequences. Ann Emerg Med. 2009;53(5):605–11.

Derlet RW, Richards JR, Kravitz RL. Frequent overcrowding in US emergency departments. Acad Emerg Med. 2001;8(2):151–5.

Shi P, Chou MC, Dai JG, Ding D, Sim J. Models and insights for hospital inpatient operations: time-dependent ED boarding time. Manag Sci. 2016;62(1):1–28.

Improta G, Romano M, Di Cicco MV, Ferraro A, Borrelli A, Verdoliva C, et al. Lean thinking to improve emergency department throughput at AORN Cardarelli hospital. BMC Health Serv Res. 2018;18(1):914.

Nuti S, Vainieri M. Managing waiting times in diagnostic medical imaging. BMJ Open. 2012;2(6):e001255.

Lungu DA, Ruggieri TG, Nuti S. Decision making tools for managing waiting times and treatment rates in elective surgery. BMC Health Serv Res. 2019;19(1):369.

Nuti S, Vola F, Bonini A, Vainieri M. Making governance work in the health care sector: evidence from a ‘natural experiment’ in Italy. Health Econ Policy L. 2016;11(1):17–38.

Nuti S, Seghieri C, Vainieri M. Assessing the effectiveness of a performance evaluation system in the public health care sector: some novel evidence from the Tuscany region experience. J Manag Govern. 2013;17(1):59–69.

Faraoni M, La Mastra M, Profili F, Vainieri M. Welfare e salute in Toscana 2018. Firenze: ARS Toscana; 2019.

Gallo M, Panero C, Vainieri M. La segmentazione comportamentale dei pazienti non urgenti in Pronto Soccorso: specificità degli utenti frequent user ed occasionali. Economia del diritto terziario. 2017;3:423–41.

Van den Heede K, Van de Voorde C. Interventions to reduce emergency department utilisation: a review of reviews. Health Policy. 2016;120(12):1337–49.

Download references

Acknowledgements

Not applicable.

Author information

Authors and affiliations.

Associate Professor at Management and Health Laboratory, Institute of Management, Scuola Superiore Sant’Anna, Pisa, Italy

Milena Vainieri

Post-doctoral researcher at Università degli studi di Genova, Genoa, Italy

Cinzia Panero

PhD candidate, Management and Health Laboratory, Institute of Management, Scuola Superiore Sant’Anna, Pisa, Italy

Lucrezia Coletta

You can also search for this author in PubMed   Google Scholar

Contributions

MV and CP designed the study, LC analyzed data, CP conducted the review of ED’s literature. All authors contributed to writing and interpreting the results. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Milena Vainieri .

Ethics declarations

Ethics approval and consent to participate.

The study used publicly available secondary data, and therefore did not require approval by an ethics committee.

Consent for publication

Competing interests.

The authors declare that they have no competing interests.

Additional information

Publisher’s note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Vainieri, M., Panero, C. & Coletta, L. Waiting times in emergency departments: a resource allocation or an efficiency issue?. BMC Health Serv Res 20 , 549 (2020). https://doi.org/10.1186/s12913-020-05417-w

Download citation

Received : 29 January 2020

Accepted : 09 June 2020

Published : 17 June 2020

DOI : https://doi.org/10.1186/s12913-020-05417-w

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Emergency departments
• Waiting times
• ED admission rates
• Overcrowding
• Resource allocation

BMC Health Services Research

ISSN: 1472-6963

• General enquiries: [email protected]

Information

• Author Services

Initiatives

You are accessing a machine-readable page. In order to be human-readable, please install an RSS reader.

All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess .

Feature papers represent the most advanced research with significant potential for high impact in the field. A Feature Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for future research directions and describes possible research applications.

Feature papers are submitted upon individual invitation or recommendation by the scientific editors and must receive positive feedback from the reviewers.

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

Original Submission Date Received: .

• Active Journals
• Find a Journal
• Journal Proposal
• Proceedings Series
• For Authors
• For Reviewers
• For Editors
• For Librarians
• For Publishers
• For Societies
• For Conference Organizers
• Open Access Policy
• Institutional Open Access Program
• Special Issues Guidelines
• Editorial Process
• Research and Publication Ethics
• Article Processing Charges
• Testimonials
• Preprints.org
• SciProfiles
• Encyclopedia

Article Menu

• Subscribe SciFeed
• Recommended Articles
• PubMed/Medline
• Google Scholar
• on Google Scholar
• Table of Contents

Find support for a specific problem in the support section of our website.

Please let us know what you think of our products and services.

Visit our dedicated information section to learn more about MDPI.

JSmol Viewer

Overcrowding in emergency department: causes, consequences, and solutions—a narrative review.

1. Introduction

2. materials and methods, 3.1. causes of ed overcrowding, 3.1.1. input factors, 3.1.2. throughput factors, 3.1.3. output factors, 3.1.4. the impact of sars-cov-2 on ed overcrowding, 3.2. effects and consequences of overcrowding in eds, 3.3. solution to overcrowding, 3.3.1. microlevel strategies, acceleration of diagnostic pathways, outpatient services outside the ed, setting home care, team triage, artificial intelligence (ai) and machine learning, 3.3.2. macrolevel strategies, simplifying the admission process, reverse triage, smoothing elective admissions, early discharge, weekend discharge, full capacity protocol or action plan, legislation and guidelines, 3.3.3. observation unit, 4. discussion, 5. conclusions, author contributions, institutional review board statement, informed consent statement, conflicts of interest.

• Babatabar-Darzi, H.; Jafari-Iraqi, I.; Mahmoudi, H.; Ebadi, A. Overcrowding Management and Patient Safety: An Application of the Stabilization Model. Iran. J. Nurs. Midwifery Res. 2020 , 25 , 382. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Lindner, G.; Woitok, B.K. Emergency Department Overcrowding: Analysis and Strategies to Manage an International Phenomenon. Wien. Klin. Wochenschr. 2021 , 133 , 229–233. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Adriani, L.; Dall’Oglio, I.; Brusco, C.; Gawronski, O.; Piga, S.; Reale, A.; Buonomo, E.; Cerone, G.; Palombi, L.; Raponi, M. Reduction of Waiting Times and Patients Leaving Without Being Seen in the Tertiary Pediatric Emergency Department: A Comparative Observational Study. Pediatr. Emerg. Care 2022 , 38 , 219–223. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Kenny, J.F.; Chang, B.C.; Hemmert, K.C. Factors Affecting Emergency Department Crowding. Emerg. Med. Clin. N. Am. 2020 , 38 , 573–587. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Yarmohammadian, M.; Rezaei, F.; Haghshenas, A.; Tavakoli, N. Overcrowding in Emergency Departments: A Review of Strategies to Decrease Future Challenges. J. Res. Med. Sci. 2017 , 22 , 23. [ Google Scholar ] [ CrossRef ]
• Badr, S.; Nyce, A.; Awan, T.; Cortes, D.; Mowdawalla, C.; Rachoin, J.-S. Measures of Emergency Department Crowding, a Systematic Review. How to Make Sense of a Long List. Open Access Emerg. Med. 2022 , 14 , 5–14. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Rabin, E.; Kocher, K.; McClelland, M.; Pines, J.; Hwang, U.; Rathlev, N.; Asplin, B.; Trueger, N.S.; Weber, E. Solutions To Emergency Department ‘Boarding’ And Crowding Are Underused And May Need To Be Legislated. Health Aff. 2012 , 31 , 1757–1766. [ Google Scholar ] [ CrossRef ]
• American College of Emergency Physicians. Practice Guideline. Definition of Boarded Patient. Ann. Emerg. Med. 2011 , 57 , 548. [ Google Scholar ] [ CrossRef ]
• Emergency Medicine Practice Committee. Emergency Department Crowding: High Impact Solutions. 2016. Available online: https://www.acep.org/globalassets/sites/acep/media/crowding/empc_crowding-ip_092016.pdf (accessed on 31 May 2022).
• Savioli, G.; Ceresa, I.F.; Gri, N.; Bavestrello Piccini, G.; Longhitano, Y.; Zanza, C.; Piccioni, A.; Esposito, C.; Ricevuti, G.; Bressan, M.A. Emergency Department Overcrowding: Understanding the Factors to Find Corresponding Solutions. J. Pers. Med. 2022 , 12 , 279. [ Google Scholar ] [ CrossRef ]
• Phillips, J.L.; Jackson, B.E.; Fagan, E.L.; Arze, S.E.; Major, B.; Zenarosa, N.R.; Wang, H. Overcrowding and Its Association With Patient Outcomes in a Median-Low Volume Emergency Department. J. Clin. Med. Res. 2017 , 9 , 911–916. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Epstein, S.K.; Huckins, D.S.; Liu, S.W.; Pallin, D.J.; Sullivan, A.F.; Lipton, R.I.; Camargo, C.A. Emergency Department Crowding and Risk of Preventable Medical Errors. Intern. Emerg. Med. 2012 , 7 , 173–180. [ Google Scholar ] [ CrossRef ]
• Carter, E.J.; Pouch, S.M.; Larson, E.L. The Relationship Between Emergency Department Crowding and Patient Outcomes: A Systematic Review: Emergency Department Crowding and Patient Outcomes. J. Nurs. Scholarsh. 2014 , 46 , 106–115. [ Google Scholar ] [ CrossRef ]
• Welch, S.J.; Augustine, J.J.; Dong, L.; Savitz, L.A.; Snow, G.; James, B.C. Volume-Related Differences in Emergency Department Performance. Jt. Comm. J. Qual. Patient Saf. 2012 , 38 , 395-AP1. [ Google Scholar ] [ CrossRef ]
• Asaro, P.V.; Lewis, L.M.; Boxerman, S.B. Emergency Department Overcrowding: Analysis of the Factors of Renege Rate. Acad. Emerg. Med. 2007 , 14 , 157–162. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Boldori, H.M.; Ciconet, R.M.; Viegas, K.; Schaefer, R.; dos Santos, M.N. Cross-Cultural Adaptation of the Scale National Emergency Department Overcrowding Score (NEDOCS) for Use in Brazil. Rev. Gaúcha De Enferm. 2021 , 42 , e20200185. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Salway, R.; Valenzuela, R.; Shoenberger, J.; Mallon, W.; Viccellio, A. Emergency department (ed) overcrowding: Evidence-based answers to frequently asked questions. Rev. Médica Clínica Las Condes 2017 , 28 , 213–219. [ Google Scholar ] [ CrossRef ]
• Wachtel, G.; Elalouf, A. Addressing Overcrowding in an Emergency Department: An Approach for Identifying and Treating Influential Factors and a Real-Life Application. Isr. J. Health Policy Res. 2020 , 9 , 37. [ Google Scholar ] [ CrossRef ]
• Affleck, A.; Parks, P.; Drummond, A.; Rowe, B.H.; Ovens, H.J. Emergency Department Overcrowding and Access Block. CJEM 2013 , 15 , 359–370. [ Google Scholar ] [ CrossRef ]
• Ministero Della Salute. Linee di Indirizzo Nazionali per lo Sviluppo del Piano di Gestione del Sovraffollamento in Pronto soccorso. Available online: https://www.salute.gov.it/imgs/C_17_pubblicazioni_3143_allegato.pdf (accessed on 31 May 2022).
• Erenler, A.K.; Akbulut, S.; Guzel, M.; Cetinkaya, H.; Karaca, A.; Turkoz, B.; Baydin, A. Reasons for Overcrowding in the Emergency Department: Experiences and Suggestions of an Education and Research Hospital. Turk. J. Emerg. Med. 2014 , 14 , 59–63. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Jung, H.M.; Kim, M.J.; Kim, J.H.; Park, Y.S.; Chung, H.S.; Chung, S.P.; Lee, J.H. The Effect of Overcrowding in Emergency Departments on the Admission Rate According to the Emergency Triage Level. PLoS ONE 2021 , 16 , e0247042. [ Google Scholar ] [ CrossRef ]
• Chen, W.; Linthicum, B.; Argon, N.T.; Bohrmann, T.; Lopiano, K.; Mehrotra, A.; Travers, D.; Ziya, S. The Effects of Emergency Department Crowding on Triage and Hospital Admission Decisions. Am. J. Emerg. Med. 2020 , 38 , 774–779. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Savioli, G.; Ceresa, I.F.; Novelli, V.; Ricevuti, G.; Bressan, M.A.; Oddone, E. How the Coronavirus Disease 2019 Pandemic Changed the Patterns of Healthcare Utilization by Geriatric Patients and the Crowding: A Call to Action for Effective Solutions to the Access Block. Intern. Emerg. Med. 2022 , 17 , 503–514. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Al-Surimi, K.; Yenugadhati, N.; Shaheen, N.; Althagafi, M.; Alsalamah, M. Epidemiology of Frequent Visits to the Emergency Department at a Tertiary Care Hospital in Saudi Arabia: Rate, Visitors’ Characteristics, and Associated Factors. Int. J. Gen. Med. 2021 , 14 , 909–921. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Bittencourt, R.J.; Stevanato, A.D.M.; Bragança, C.T.N.M.; Gottems, L.B.D.; O’Dwyer, G. Interventions in Overcrowding of Emergency Departments: An Overview of Systematic Reviews. Rev. De Saúde Pública 2020 , 54 , 66. [ Google Scholar ] [ CrossRef ]
• af Ugglas, B.; Skyttberg, N.; Wladis, A.; Djärv, T.; Holzmann, M.J. Emergency Department Crowding and Hospital Transformation during COVID-19, a Retrospective, Descriptive Study of a University Hospital in Stockholm, Sweden. Scand. J. Trauma Resusc. Emerg. Med. 2020 , 28 , 107. [ Google Scholar ] [ CrossRef ]
• Richardson, D.B. Increase in Patient Mortality at 10 Days Associated with Emergency Department Overcrowding. Med. J. Aust. 2006 , 184 , 213–216. [ Google Scholar ] [ CrossRef ]
• Menon, N.V.B.; Jayashree, M.; Nallasamy, K.; Angurana, S.K.; Bansal, A. Bed Utilization and Overcrowding in a High-Volume Tertiary Level Pediatric Emergency Department. Indian Pediatr. 2021 , 58 , 723–725. [ Google Scholar ] [ CrossRef ]
• Jo, S.; Jeong, T.; Jin, Y.H.; Lee, J.B.; Yoon, J.; Park, B. ED Crowding Is Associated with Inpatient Mortality among Critically Ill Patients Admitted via the ED: Post Hoc Analysis from a Retrospective Study. Am. J. Emerg. Med. 2015 , 33 , 1725–1731. [ Google Scholar ] [ CrossRef ]
• Crook, H.D.; Taylor, D.M.; Pallant, J.F.; Cameron, P.A. Workplace Factors Leading to Planned Reduction of Clinical Work among Emergency Physicians. Emerg. Med. 2004 , 16 , 28–34. [ Google Scholar ] [ CrossRef ]
• Green, D.; Ruel, J. Impact of Advanced Practice Prehospital Programs on Health Care Costs and ED Overcrowding: A Literature Review. Adv. Emerg. Nurs. J. 2020 , 42 , 128–136. [ Google Scholar ] [ CrossRef ]
• Krochmal, P.; Riley, T.A. Increased Health Care Costs Associated with ED Overcrowding. Am. J. Emerg. Med. 1994 , 12 , 265–266. [ Google Scholar ] [ CrossRef ]
• Pines, J.M.; Batt, R.J.; Hilton, J.A.; Terwiesch, C. The Financial Consequences of Lost Demand and Reducing Boarding in Hospital Emergency Departments. Ann. Emerg. Med. 2011 , 58 , 331–340. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Kim, D.; Park, Y.S.; Park, J.M.; Brown, N.J.; Chu, K.; Lee, J.H.; Kim, J.H.; Kim, M.J. Influence of Overcrowding in the Emergency Department on Return Visit within 72 H. J. Clin. Med. 2020 , 9 , 1406. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Duseja, R.; Bardach, N.S.; Lin, G.A.; Yazdany, J.; Dean, M.L.; Clay, T.H.; Boscardin, W.J.; Dudley, R.A. Revisit Rates and Associated Costs After an Emergency Department Encounter: A Multistate Analysis. Ann. Intern. Med. 2015 , 162 , 750–756. [ Google Scholar ] [ CrossRef ]
• Di Somma, S.; Paladino, L.; Vaughan, L.; Lalle, I.; Magrini, L.; Magnanti, M. Overcrowding in Emergency Department: An International Issue. Intern. Emerg. Med. 2015 , 10 , 171–175. [ Google Scholar ] [ CrossRef ]
• Singer, A.J.; Taylor, M.; LeBlanc, D.; Meyers, K.; Perez, K.; Thode, H.C.; Pines, J.M. Early Point-of-Care Testing at Triage Reduces Care Time in Stable Adult Emergency Department Patients. J. Emerg. Med. 2018 , 55 , 172–178. [ Google Scholar ] [ CrossRef ]
• Oredsson, S.; Jonsson, H.; Rognes, J.; Lind, L.; Göransson, K.E.; Ehrenberg, A.; Asplund, K.; Castrén, M.; Farrohknia, N. A Systematic Review of Triage-Related Interventions to Improve Patient Flow in Emergency Departments. Scand. J. Trauma Resusc. Emerg. Med. 2011 , 19 , 43. [ Google Scholar ] [ CrossRef ]
• Savioli, G.; Ceresa, I.F.; Maggioni, P.; Lava, M.; Ricevuti, G.; Manzoni, F.; Oddone, E.; Bressan, M.A. Impact of ED Organization with a Holding Area and a Dedicated Team on the Adherence to International Guidelines for Patients with Acute Pulmonary Embolism: Experience of an Emergency Department Organized in Areas of Intensity of Care. Medicines 2020 , 7 , 60. [ Google Scholar ] [ CrossRef ]
• Lee, I.-H.; Chen, C.-T.; Lee, Y.-T.; Hsu, Y.-S.; Lu, C.-L.; Huang, H.-H.; Hsu, T.-F.; How, C.-K.; Yen, D.H.-T.; Yang, U.-C. A New Strategy for Emergency Department Crowding: High-Turnover Utility Bed Intervention. J. Chin. Med. Assoc. 2017 , 80 , 297–302. [ Google Scholar ] [ CrossRef ]
• Burström, L.; Nordberg, M.; Örnung, G.; Castrén, M.; Wiklund, T.; Engström, M.-L.; Enlund, M. Physician-Led Team Triage Based on Lean Principles May Be Superior for Efficiency and Quality? A Comparison of Three Emergency Departments with Different Triage Models. Scand. J. Trauma Resusc. Emerg. Med. 2012 , 20 , 57. [ Google Scholar ] [ CrossRef ] [ Green Version ]
• Jeyaraman, M.M.; Copstein, L.; Al-Yousif, N.; Alder, R.N.; Kirkland, S.W.; Al-Yousif, Y.; Suss, R.; Zarychanski, R.; Doupe, M.B.; Berthelot, S.; et al. Interventions and Strategies Involving Primary Healthcare Professionals to Manage Emergency Department Overcrowding: A Scoping Review. BMJ Open 2021 , 11 , e048613. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Debono, P.; Debattista, J.; Attard-Montalto, S.; Pace, D. Adequacy of Pediatric Triage. Disaster Med. Public Health Prep. 2012 , 6 , 151–154. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Sarasa Cabezuelo, A. Application of Machine Learning Techniques to Analyze Patient Returns to the Emergency Department. J. Pers. Med. 2020 , 10 , 81. [ Google Scholar ] [ CrossRef ]
• Arnaud, E.; Elbattah, M.; Gignon, M.; Dequen, G. Deep Learning to Predict Hospitalization at Triage: Integration of Structured Data and Unstructured Text. In Proceedings of the 2020 IEEE International Conference on Big Data (Big Data), Atlanta, GA, USA, 10–13 December 2020; pp. 4836–4841. [ Google Scholar ]
• Lovett, P.B.; Illg, M.L.; Sweeney, B.E. A Successful Model for a Comprehensive Patient Flow Management Center at an Academic Health System. Am. J. Med. Qual. 2016 , 31 , 246–255. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Kelen, G.D.; Wolfe, R.; D’Onofrio, G.; Mills, A.M.; Diercks, D.; Stern, S.A.; Wadman, M.C.; Sokolove, P.E. Emergency Department Crowding: The Canary in the Health Care System. NEJM Catal. Innov. Care Deliv. 2021 , 1–26. [ Google Scholar ] [ CrossRef ]
• Pollaris, G.; Sabbe, M. Reverse Triage: More than Just Another Method. Eur. J. Emerg. Med. 2016 , 23 , 240–247. [ Google Scholar ] [ CrossRef ]
• Syed, S.T.; Gerber, B.S.; Sharp, L.K. Traveling Towards Disease: Transportation Barriers to Health Care Access. J. Community Health 2013 , 38 , 976–993. [ Google Scholar ] [ CrossRef ]
• McKenna, P.; Heslin, S.M.; Viccellio, P.; Mallon, W.K.; Hernandez, C.; Morley, E.J. Emergency Department and Hospital Crowding: Causes, Consequences, and Cures. Clin. Exp. Emerg. Med. 2019 , 6 , 189–195. [ Google Scholar ] [ CrossRef ]
• Boyle, J.; Jessup, M.; Crilly, J.; Green, D.; Lind, J.; Wallis, M.; Miller, P.; Fitzgerald, G. Predicting Emergency Department Admissions. Emerg. Med. J. 2012 , 29 , 358–365. [ Google Scholar ] [ CrossRef ]
• McManus, M.L.; Long, M.C.; Cooper, A.; Mandell, J.; Berwick, D.M.; Pagano, M.; Litvak, E. Variability in Surgical Caseload and Access to Intensive Care Services. Anesthesiology 2003 , 98 , 1491–1496. [ Google Scholar ] [ CrossRef ]
• Litvak, E.; Fineberg, H.V. Smoothing the Way to High Quality, Safety, and Economy. N. Engl. J. Med. 2013 , 369 , 1581–1583. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Powell, E.S.; Khare, R.K.; Venkatesh, A.K.; Van Roo, B.D.; Adams, J.G.; Reinhardt, G. The Relationship between Inpatient Discharge Timing and Emergency Department Boarding. J. Emerg. Med. 2012 , 42 , 186–196. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Wong, H.J.; Wu, R.C.; Caesar, M.; Abrams, H.; Morra, D. Smoothing Inpatient Discharges Decreases Emergency Department Congestion: A System Dynamics Simulation Model. Emerg. Med. J. 2010 , 27 , 593–598. [ Google Scholar ] [ CrossRef ] [ PubMed ]
• Garson, C.; Hollander, J.E.; Rhodes, K.V.; Shofer, F.S.; Baxt, W.G.; Pines, J.M. Emergency Department Patient Preferences for Boarding Locations When Hospitals Are at Full Capacity. Ann. Emerg. Med. 2008 , 51 , 9–12.e3. [ Google Scholar ] [ CrossRef ]
• Aaronson, E.L.; Yun, B.J. Emergency Department Shifts and Decision to Admit: Is There a Lever to Pull to Address Crowding? BMJ Qual. Saf. 2020 , 29 , 443–445. [ Google Scholar ] [ CrossRef ]
• Ross, M.A.; Hockenberry, J.M.; Mutter, R.; Barrett, M.; Wheatley, M.; Pitts, S.R. Protocol-Driven Emergency Department Observation Units Offer Savings, Shorter Stays, And Reduced Admissions. Health Aff. 2013 , 32 , 2149–2156. [ Google Scholar ] [ CrossRef ]
• Al-Kuwaiti, A.; Hefny, A.F.; Bellou, A.; Eid, H.O.; Abu-Zidan, F.M. Epidemiology of Head Injury in the United Arab Emirates. Turk. J. Trauma Emerg. Surg. 2012 , 18 , 213–218. [ Google Scholar ] [ CrossRef ]
• Lim, A.G.; Kivlehan, S.; Losonczy, L.I.; Murthy, S.; Dippenaar, E.; Lowsby, R.; Yang, M.L.C.L.C.; Jaung, M.S.; Stephens, P.A.; Benzoni, N.; et al. Critical Care Service Delivery across Healthcare Systems in Low-Income and Low-Middle-Income Countries: Protocol for a Systematic Review. BMJ Open 2021 , 11 , e048423. [ Google Scholar ] [ CrossRef ] [ PubMed ]

Share and Cite

Sartini, M.; Carbone, A.; Demartini, A.; Giribone, L.; Oliva, M.; Spagnolo, A.M.; Cremonesi, P.; Canale, F.; Cristina, M.L. Overcrowding in Emergency Department: Causes, Consequences, and Solutions—A Narrative Review. Healthcare 2022 , 10 , 1625. https://doi.org/10.3390/healthcare10091625

Sartini M, Carbone A, Demartini A, Giribone L, Oliva M, Spagnolo AM, Cremonesi P, Canale F, Cristina ML. Overcrowding in Emergency Department: Causes, Consequences, and Solutions—A Narrative Review. Healthcare . 2022; 10(9):1625. https://doi.org/10.3390/healthcare10091625

Sartini, Marina, Alessio Carbone, Alice Demartini, Luana Giribone, Martino Oliva, Anna Maria Spagnolo, Paolo Cremonesi, Francesco Canale, and Maria Luisa Cristina. 2022. "Overcrowding in Emergency Department: Causes, Consequences, and Solutions—A Narrative Review" Healthcare 10, no. 9: 1625. https://doi.org/10.3390/healthcare10091625

Article Metrics

Article access statistics, further information, mdpi initiatives, follow mdpi.

Subscribe to receive issue release notifications and newsletters from MDPI journals

Search form

Emergency department crowding hits crisis levels, risking patient safety.

(© stock.adobe.com)

In a pair of new studies, Yale researchers document a widespread and increasing level of overcrowding in America’s emergency departments (EDs), a crisis that puts patient safety and access to care at risk.

For the studies, the researchers examined, respectively, the progression in recent years of two measures of ED function and hospital capacity: boarding time — or how long patients remain in the ED after physicians have determined they should be admitted to the hospital — and how often patients leave the ED before receiving care.

Their findings, they say, help characterize the bigger issues that underlie ED crowding. And they show that the issue worsened during the COVID-19 pandemic. Their methods also yield more timely assessments of these key indicators, which historically have been hard to come by.

“ This is not an ED management issue,” said Arjun Venkatesh , an associate professor of emergency medicine at Yale School of Medicine and an author of the studies. “These are indicators of overwhelmed resources and symptoms of deeper problems in the health care system.”

The studies were both published Sept. 30 in JAMA Network Open.

It was during the 1980s that ED crowding emerged as an issue of national concern. The problem has only gotten worse in the decades since, with negative effects for patients and hospital staff alike. For patients, studies have found that ED crowding is correlated with discomfort, reduced privacy, treatment delays, and higher risk of prolonged disease and death. ED crowding also leads to increased violence toward staff, greater clinician and nurse turnover, and high rates of burnout. A recent study found nearly 63% of surveyed U.S. physicians experienced burnout in 2021.

In one of the new studies , researchers found that boarding times — or the amount of time patients were kept in the emergency department after clinicians had determined they should be admitted — were related to hospital occupancy rates, or the percentage of staffed inpatient beds that are occupied. The Joint Commission, an independent national health care accrediting body, has recommended that boarding time not exceed four hours.

For the study, Yale researchers evaluated these measures in U.S. hospitals during the COVID-19 pandemic, from January 2020 to December 2021. They found that when occupancy exceeded 85%, boarding times exceeded this four-hour standard. In fact, under those circumstances, the median ED boarding time was 6.58 hours. Boarding times also worsened throughout this time period, outpacing occupancy rates.

This relationship makes sense, says Alexander Janke, lead author of the studies, because when occupancy is high, there are few available beds to move patients from the ED. And with diminishing capacity, wait times are compounded.

“ Hospitals must have some flexible capacity so there are places for patients with emergencies requiring hospitalization to go,” said Janke, who conducted the research while a fellow at Yale School of Medicine and is now at the University of Michigan. “And that capacity doesn’t exist in a lot of places.” Which means patients stay in the ED until space opens at their destination and ED beds remain occupied, limiting the number available to new patients.

This latter impact can affect ED wait times. And when those are long, patients are more likely to leave before being evaluated. In the second study, researchers assessed the rates at which patients in U.S. hospitals decided to leave EDs before even being seen by a clinician.

From January 2017 to December 2021, the median rate of patients leaving without being seen nearly doubled from 1.1% to 2.1%. At the worst performing hospitals, those rates were as high as 10% by the end of 2021, a number Janke called “astonishing.”

“ It’s a measure of access to care,” he said. “If you have to wait hours and hours to be evaluated in the ED, then that’s not the access to care that we have required by law in [the Emergency Medical Treatment and Active Labor Act, or EMTALA].” (Enacted in 1986, EMTALA requires universal provision of emergency care by hospitals that accept Medicare payments.)

These findings, the researchers say, offer a snapshot of the current state of EDs in the United States, and provide critical data that typically are difficult to obtain in a timely manner. Though hospitals are required to report certain measures on a yearly basis, those data often aren’t released publicly for another two or three years, rendering them irrelevant, said Janke.

“ The health care system is a living, breathing organism, and it’s like we measured its vital signs one time three years ago and that’s how we make public policy,” he said. “You and I should know whether the acute care system where we live has the capacity to address, say, a heart attack or a stroke in a family member. This is a problem that affects population health.”

The researchers want people outside of the ED community to recognize this population-level effect and the impacts of ED crowding.

“ We hope our findings begin to draw attention and accountability for the human toll of the ED boarding crisis,” said Ted Melnick , associate professor of emergency medicine at Yale School of Medicine and an author of the studies.

For both studies, the researchers collected data from a large electronic health record vendor, an approach that’s particularly helpful in the absence of other national or local data.

“ Future partnerships with electronic health record vendors can continue to shed light on crises like this,” Melnick said.

Health & Medicine

Media Contact

Fred Mamoun: [email protected] , 203-436-2643

Biomarkers for psychiatric illness? Study gets researchers one step closer

Office Hours with… Alexandra T. Vazquez

Yale poet’s new works wrestle with — and transcend — despair

New project connects zoos and natural history museums

• Show More Articles

• EMResident Archives
• Publications
• Submit an Article

• Critical Care
• Health Policy Journal Club
• Program Director Interviews

2020-2021: 21 Greatest Hits - Emergency Medicine Research Edition

It is often difficult to keep up with all of the highest impact papers in emergency medicine..

The EMRA Research Committee has compiled a quick review of some of the most practice-affirming or practice-changing papers published from September 2020 to September 2021. This is by no means a definitive list, but all of these papers will likely be good to know for your next shift!

THERAPEUTICS

A Randomized Trial Comparing the Efficacy of Five Oral Analgesics for Treatment of Acute Musculoskeletal Extremity Pain in the Emergency Department This randomized control trial compared the efficacy of 5 oral analgesics for the treatment of acute musculoskeletal extremity pain. All patients were deemed to need an x-ray and be appropriate for oral pain control by the treating physician. In the end, no particular analgesic was more efficacious at 1 or 2 hours. However, there was significantly more nausea and vomiting among patients treated with opioids.

Regimens included:

• 400 mg ibuprofen and 1,000 mg acetaminophen
• 800 mg ibuprofen and 1,000 mg acetaminophen
• 30 mg codeine and 300 mg acetaminophen
• 5 mg hydrocodone and 300 mg acetaminophen
• 5 mg oxycodone and 325 mg acetaminophen

The Use of Tranexamic Acid to Reduce the Need for Nasal Packing in Epistaxis (NoPAC): Randomized Controlled Trial The largest RCT of TXA in epistaxis (496 participants) demonstrates that TXA does not provide improved benefit compared to traditional nasal packing at reducing the need for anterior nasal packing (43.7% of the experimental group still required anterior nasal packing to achieve tamponade). Limitations of the study include the studied population (primarily older men on anticoagulation), and the dose of TXA used.

Regional anesthesia on the finger: traditional dorsal digital nerve block versus subcutaneous volar nerve block, a randomized controlled trial A prospective, multicenter, RCT of 409 ED patients compared the subcutaneous volar nerve block vs. the traditional dorsal digital nerve block. All patients had a finger injury requiring regional anesthesia for surgical treatment. Results demonstrated that numbing the thumb via a dorsal block is preferred, whereas individual fingers achieve better dorsal analgesia via the dorsal block and better analgesia on the proximal phalanx via a volar block. Overall, the dorsal nerve block gave greater anesthesia but required 2 injections and a greater amount of lidocaine.

Isopropyl alcohol nasal inhalation for nausea in the triage of an adult emergency department A randomized, double-blind, placebo-controlled trial assessed the efficacy of isopropyl alcohol (IPA) to patients who presented to triage in the ED with the chief complaint of isolated nausea and vomiting. Patients scored 3 or higher on the nausea/vomiting numerical rating scale. Among 118 patients, 62 patients who received IPA reported improved nausea and vomiting-related symptoms vs. placebo and required less rescue treatment. This is the third RCT demonstrating the efficacy of inhaled IPA for the acute treatment of uncomplicated nausea and vomiting.

GASTROENTEROLOGY

A Randomized Trial Comparing Antibiotics with Appendectomy for Appendicitis A non-blinded, pragmatic non-inferiority randomized trial of 1,552 patients with appendicitis compared quality of life at 30 days between patients treated with 10 days of antibiotics vs. appendectomy for appendicitis. The results demonstrated that antibiotics have comparable outcomes to surgery for acute appendicitis etiologies, with the exception of patients with an appendicolith who had higher rates of complications in the antibiotic group.

Prospective Validation of Canadian TIA Score and Comparison with ABCD2 and ABCD2i for subsequent stroke risk after transient ischemic attack: multicenter prospective cohort study This prospective multicenter cohort study was designed to validate the Canadian TIA Score for patients needing risk stratification for future adverse neurologic events. Results demonstrated that among the 7,607 ED patients presenting for TIA, 1.4% had a subsequent stroke within 7 days, and 1.1% required carotid endarterectomy/stenting. The Canadian TIA score outperformed the ABCD2 and ABCD2I in risk stratifying patients with an improved area under the curve. The Canadian TIA risk score was also able to identify a low-risk cohort appropriate for rapid outpatient evaluation. The Canadian TIA score is now validated and can be used in clinical practice.

MAGraine: Magnesium compared to conventional therapy for treatment of migraines The single-center, prospective, double-blinded, randomized, three-armed trial compared magnesium, metoclopramide, and prochlorperazine for the treatment of migraine. This study found that magnesium was not inferior in efficacy to the other two medications, which can be especially useful in patients who simultaneously present with prolonged QT. However, patients who received magnesium for migraine management were more likely to require additional analgesia subsequently. One significant limitation of this study is that it was stopped early due to COVID, causing it to be underpowered, with n = 157.

Effect of a Restrictive vs Liberal Blood Transfusion Strategy on Major Cardiovascular Events Among Patients With Acute Myocardial Infarction and Anemia: The REALITY Randomized Clinical Trial An open-label, noninferiority, randomized trial attempted to identify an optimal transfusion strategy in patients with acute myocardial infarction and anemia. Primary outcome was major 30-day adverse cardiovascular events. The study concluded that among the 668 participants, between the restrictive (transfuse at HgB ≤ 8) and liberal transfusion groups (transfuse at HgB ≤ 10), major adverse cardiac events occurred in 11.0% of patients in the restrictive group vs. 14.0% in the liberal transfusion group. The authors concluded that a restrictive transfusion resulted in a noninferior rate of MACE after 30 days with a relative risk of 0.79 (1-sided 97.5% CI, 0.00-1.19). They also cautioned that the non-inferiority confidence interval was large enough to contain worse outcomes in the restrictive group, warranting a larger study to confirm these results.

  DIagnostic accuracy oF electrocardiogram for acute coronary OCClUsion resuLTing in myocardial infarction (DIFOCCULT Study) This is a retrospective case-control study evaluating the performance of EKG STEMI criteria or expanded EKG Acute Coronary Occlusion Myocardial Infarction(ACOMI) criteria for the identification of Acute Coronary Occlusion. In this study, 1,152 STEMI and 2,353 non-STEMI patients were evaluated. In the non-STEMI group 28% were found to have an acute coronary occlusion identifiable on EKG with ACOMI criteria. These non-STEMI patients with ACOMI had similar mortality rates to STEMI patients. The author shows that a refined EKG paradigm for the identification of acute coronary occlusion would have improved sensitivity to identify those who need acute reperfusion therapy.

Effects of Fluoroquinolones on Outcomes of Patients With Aortic Dissection or Aneurysm This was a retrospective cohort study that compared patients who were diagnosed with aortic aneurysms or aortic dissections and their mortality risk after fluoroquinolone exposure. Patients were identified after their initial hospitalization and then outpatient data was followed, looking at prescription days of fluoroquinolones (experimental group) or amoxicillin (negative control group) and then monitored for adverse outcomes. The study concluded that exposure to fluoroquinolones was associated with a higher risk of all-cause death (adjusted hazard ratio [aHR]: 1.61; 95% confidence interval [CI]: 1.50 to 1.73) as well as aortic-related death (aHR: 1.80; 95% CI: 1.50 to 2.15). Increasing evidence has shown fluoroquinolones should be avoided in high-risk patients unless no other treatment options are available.

CRITICAL CARE

The ED-AWARENESS Study: A Prospective, Observational Cohort Study of Awareness With Paralysis in Mechanically Ventilated Patients Admitted From the Emergency Department The single-center, prospective cohort study assessed the prevalence of awareness with paralysis in ED patients receiving mechanical ventilation. In this study, 383 patients were surveyed following extubation for awareness during paralysis. The study identified a prevalence of 2.6% (10/383), with rocuronium usage at any point resulting in higher instances of awareness (70%) vs. all other paralytics (31.4) (95% confidence interval 0.94 to 8.8). While there are many possible reasons for this prevalence, it is much higher than the rate observed in general anesthesia (~1%), and care should be taken to start appropriate and timely post-intubation sedation.

Hypothermia versus Normothermia after Out-of-Hospital Cardiac Arrest This is an open-label randomized control trial of 1,850 adults with an out-of-hospital cardiac arrest who subsequently underwent targeted hypothermia (at 33°C), or targeted normothermia. Primary outcome was mortality at 6 months. Functional outcomes at 6 months were also evaluated. The study concluded 50% of the patients treated with hypothermia died, compared to 48% of the normothermic group (relative risk with hypothermia, 1.04; 95% confidence interval [CI], 0.94 to 1.14; P = 0.37). Similarly, 55% of patients in the hypothermic group suffered from severe disability (modified Rankin scale score ≥4), compared to 55% of normothermic patients (relative risk with hypothermia, 1.00; 95% CI, 0.92 to 1.09), thus concluding that targeted hypothermia does not decrease mortality within 6 months when compared to targeted normothermia. This study should be narrowly interpreted, as it is a highly selected patient population that does not compare well to the general U.S. cardiac arrest population in regard to rates of bystander CPR, rates of presenting with a shockable rhythm, and neurologically intact survival rates.

Lung-Protective Ventilation and Associated Outcomes and Costs Among Patients Receiving Invasive Mechanical Ventilation in the ED A retrospective study assessed how ventilation settings in the ED affected ICU outcomes among 4,174 patients. In this study, 58.4% of patients on ventilation received lung-protective ventilation in the ED (defined as tidal volume ≤ 8mL/kg predicted body weight) and were less likely to suffer from ARDS (aOR, 0.87; 95% CI, 0.81-0.92) or in-hospital death (aOR, 0.91; 95% CI, 0.84-0.96). ED ventilatory care of critically ill patients can have lasting effects on mortality and other adverse outcomes.

Early head-to-pelvis computed tomography in out-of-hospital circulatory arrest without obvious etiology In patients who present following an out-of-hospital cardiac arrest, identifying obvious causes can be challenging and not immediately identifiable. A prospective, observational pilot study assessed the safety and efficacy of early head-to-pelvis CT imaging to identify the cause of cardiac arrest. Among 104 patients a sudden death CT scan (SDCT) protocol (non-contrast CT head, ECG-gated cardiac and thoracic CT angiogram, and nongated venous-phase abdominopelvic CT angiogram) identify the cause of cardiac arrest in nearly 39% of patients. In addition, life-threatening complications of resuscitation were identified in 16% of patients. Though exploratory, these findings suggest that a sudden death CT protocol can expedite the diagnosis of potential causes and identify resuscitation complications in patients with out-of-hospital cardiac arrests.

Noninvasive Ventilation Use in Critically Ill Patients with Acute Asthma Exacerbation A retrospective cohort study assessed the association between noninvasive ventilation and a subsequent need for invasive mechanical ventilation and in-hospital mortality among patients admitted to the ICU with an asthma exacerbation. Noninvasive ventilation was associated with a lower likelihood of receiving invasive mechanical ventilation (adjusted generalized estimating equation odds ratio, 0.36; 95% CI, 0.32-0.40) and decreased in-hospital mortality (odds ratio, 0.48; 95% CI 0.40-0.58) unless patients had concomitant comorbid pneumonia and/or severe sepsis.

Short-Course Antimicrobial Therapy for Pediatric Community-Acquired Pneumonia: The SAFER Randomized Clinical Trial A multicenter, blinded, non-inferiority RCT compared rates of cure for community-acquired pneumonia with a short course (5 days) vs. standard course (10 days) of amoxicillin. In this study, 281 pediatric ED patients between 6 months and 10 years old with CAP who were being discharged were randomized. The results demonstrated that the short course of antibiotic therapy was comparable to longer course antibiotics. Clinical cure occurred in 88.6% in the short group and 90.8% in the control group (risk difference, -0.016; 97.5% confidence limit, -0.087). In pediatric patients who are otherwise healthy presenting with community-acquired pneumonia, it is reasonable to consider a shorter course (< 10 days) of antibiotics and follow-up with primary care physician to ensure clinical cure. Though these results are consistent with other trials, the results themselves are not as robust, and an additional trial is likely needed with different endpoints to confirm these findings.

Risk Factors and Outcomes After a Brief Resolved Unexplained Event: A Multicenter Study To evaluate whether current American Academy of Pediatrics risk criteria predict BRUE outcomes, a multicenter retrospective cohort study assessed more than 2,000 infants less than 1 year of age who presented with a suspected BRUE without a probable alternative or definite diagnosis. Among these patients, 87% met AAP higher-risk criteria for having at least 1 AAP risk factor; 63% were hospitalized, with the most common explanations being less serious such as GERD (18.5%), choking or gagging (8.2%), viral respiratory infections (4.4%), and breath-holding spells (4.1%). A serious diagnosis was identified in 4.0% of patients, with 45% of these diagnoses being made after discharge from the index visit without an explanation. Having at least 1 AAP risk factor (ie, higher-risk criteria) was associated with a recurrent event in the ED or hospital (odds ratio [OR] 5.9; 95% confidence interval [CI] 2.7–12.6) and a recurrent event that led to an explanation (OR 15.1; 95% CI 2.1–108.6). The results suggest that while the absence of AAP high-risk criteria had a robust NPV (97%) for underlying serious conditions, the presence of criteria did not have a strong PPV (4%).

Evaluation and Management of Well-Appearing Febrile Infants 8 to 60 Days Old This paper represents the first official guidelines from the American Academy of Pediatrics for the evaluation of well-appearing febrile(≥ 38°C) infants 8-60 days old. These landmark guidelines are divided into three algorithms for infants 8-21 days of age, 22-28 days of age, and 29-60 days of age. There is an abundance of information in this paper and it is worth becoming familiar with and having handy for when this situation arises. Importantly, there are inclusion and exclusion criteria listed to ensure kids are appropriate for utilization of these guidelines.

PRE-HOSPITAL

Tranexamic Acid During Prehospital Transport in Patients at Risk for Hemorrhage After Injury: A Double-blind, Placebo-Controlled, Randomized Clinical Trial Pragmatic, phase 3, multicenter, double-blind, placebo-controlled, superiority randomized trial which assessed clinical outcomes among 6559 patients at risk for hemorrhage who received prehospital tranexamic acid (single dose). The 30-day all-cause mortality was assessed among patients who received 1g TXA (treatment) or 100 mL saline (placebo) prior to hospitalization. Results showed 30-day mortality among patients receiving TXA was 8.1% vs. placebo 9.9% (95% CI, -5.6% to 1.9%; P = .17). Post-hoc analysis, stratified by time to TXA administration, showed giving TXA within 1 hour of injury in patients with severe shock lowers 30-day mortality compared with placebo (18.5% vs 35.5%; difference, -17%; 95% CI, -25.8% to -8.1%; P < .003).  

Diagnostic Accuracy of Lung Point-Of-Care Ultrasonography for Acute Heart Failure Compared with Chest X-ray Study Among Dyspneic Older Patients in the Emergency Department A retrospective cohort study assessed whether POCUS was comparable to chest x-ray in identifying acute heart failure exacerbation among older patients. An 8-zone lung ultrasound protocol was used to look for signs of pulmonary edema; 148 patients were enrolled. For the diagnosis of acute heart failure, POCUS had a sensitivity of 92.5% and a specificity of 85.7% vs. chest x-ray with a sensitivity of 63.6% and specificity of 92.9%. Overall, POCUS had a significantly higher sensitivity for the diagnosis of acute heart failure, while demonstrating comparable specificity.

Impact of point-of-care ultrasound on treatment time for ectopic pregnancy A retrospective, observational, cohort study assessed whether transabdominal POCUS by itself or in addition to consultative radiology ultrasound (RADUS), reduces ED treatment time for patients with ectopic pregnancy requiring operative care. Among 109 patients admitted with ectopic pregnancies, 36 received POCUS (with 23 of those 36 also receiving RADUS), and 73 received RADUS only. POCUS involved the RUPTURE exam (Right Upper and Pelvis Timley Ultrasound for Ruptured Ectopic) to evaluate for an intrauterine pregnancy and abdominal free fluid. The average ED treatment time in the POCUS group was 157.9 min vs. 206.3 min in the RADUS group (p = 0.0141). The median time to OR for ruptured ectopic pregnancies was 203.0 min (interquartile range [IQR] 159.0) in the POCUS group versus 293.0 min (IQR 139.0) in the RADUS group (p = 0.0002). These results conclude that POCUS was associated with significantly faster time to OR for ectopic pregnancies.

Related Articles

Rapid research review: more study types, journal club for dummies: how not to be intimidated by evidence-based medicine, all articles.

• Administration and Operations Committee 2
• Critical Care Committee 4
• Education Committee 10
• Government Services 4
• Health Policy Committee 8
• Informatics Committee 3
• Medical Student Council 7
• Pediatrics Committee 4
• Research Committee 6
• Simulation Committee 3
• Social EM Committee 7
• Wilderness Committee 5
• International Committee 8
• Prehospital and Disaster Medicine Committee 5
• Simulation Division 2
• Sports Medicine Committee 5
• Advancement of EM 110
• Administration & Operations 57
• Admin Ops Literature Review 8
• Diversity and Inclusion 18
• Research 31
• Rapid Research Review 9
• Attending 2
• Award Winners 20
• Educational Courses 2
• Residency Leadership 2
• Travel Scholarships 3
• ACEP Member Benefits 2
• Career Planning 78
• Board Certification 7
• Interviewing 5
• Job Search 3
• Practice Environments 25
• Community 2
• International 10
• Locum Tenens 2
• Clinical 981
• Addiction Medicine 4
• Surgical Airway 1
• Behavioral Health 5
• Cardiology 154
• ECG Challenge 47
• Consult Corner 5
• Critical Care 227
• Critical Care Alert 103
• Critical Care Devices 11
• Critical Care Roadblock 3
• Critical Care Ultrasound 14
• Deep Dive in CritCare 9
• Ventilator Management 6
• Dermatology 8
• Disaster Medicine 12
• Prehospital Care 21
• Endocrinology 11
• Event Medicine 2
• Gastroenterology 15
• Geriatrics 4
• Hematology 19
• Immunology 1
• Infectious Disease 131
• COVID-19 80
• Informatics 19
• Telemedicine 3
• International EM 25
• Nephrology 14
• Neurology 50
• Ophthalmology 16
• Orthopedics 26
• Osteopathic 3
• Pain Management 24
• Palliative Care 14
• Patient Interactions 18
• Pediatric EM 99
• Psychiatry 9
• Mental Health 3
• Pulmonary 17
• Radiology 7
• Rheumatology 1
• Simulation 13
• Social EM 52
• Space Medicine 3
• Sports Medicine 11
• Toxicology 98
• Medications 12
• Recreational Drugs 10
• Penetrating 1
• Traumatic Brain Injury 2
• Ultrasound 84
• Guided Procedures 5
• POCUS For the Win 7
• Undersea and Hyperbaric 2
• Visual Diagnosis 20
• Wilderness Medicine 25
• Editorial 129
• Editor's Forum 54
• Heart of EM 12
• Opinion-Editorial 13
• Leadership Reports 77
• ACEP Representative 2
• ACGME RC-EM 11
• President's Message 48
• Speaker Report 8
• Treasurer's Report 3
• Membership 3
• Events & Activities 21
• ACEP Scientific Assembly 6
• CORD Academic Assembly 2
• EM Wellness Week 1
• EMRA MedWAR 3
• Leadership and Advocacy Conference 6
• Fellowships 12
• Education Fellowships 2
• Global EM Fellowships 2
• Health Policy Fellowships 1
• Pediatric Fellowships 2
• Health Equity 3
• Health Policy 146
• Advocacy 45
• Affordable Care Act 7
• Health Policy Journal Club 78
• Legislation 9
• Regulatory 2
• Leadership 181
• Committees and Divisions 4
• EMRA Board of Directors 40
• EMRA Spotlight 127
• Representative Council 9
• Medical Education 80
• Board Review 2
• Questions 1
• Med Ed Fellowship Director Interview Series 10
• Medical Students 199
• Advising 60
• Away Rotations 8
• Dual Degree Programs 1
• ERAS & Residency Application 3
• Military Advising 2
• Program Director Interviews 83
• Rank List 1
• Residents Program Interviews 4
• Medical Student Council 29
• Mentorship 4
• Non Clinical 64
• Health Care Administration 35
• Otolaryngology 5
• Resuscitation 5
• Wellness 130
• Compassion Fatigue 9
• Financial 10
• Insurance 2
• Loan Refinancing 2
• Personal Finance 4
• Medico Legal 32
• Medical Liability 2
• Risk Management Pitfalls 23
• Personal 14
• Workplace 21
• Med Student 46
• Advertise with us
• Submit an article
• Connect with us

© 2021 Emergency Medicine Residents' Association | Privacy Policy | Website Links Policy | Social Media Policy

Log in using your username and password

• Search More Search for this keyword Advanced search
• Latest content
• Supplements
• BMJ Journals

You are here

• Volume 4, Issue Suppl 6
• Emergency care research as a global health priority: key scientific opportunities and challenges
• Article Text
• Article info
• Citation Tools
• Rapid Responses
• Article metrics

• Junaid Razzak 1 ,
• http://orcid.org/0000-0002-6254-421X Blythe Beecroft 2 ,
• Jeremy Brown 3 ,
• Stephen Hargarten 4 ,
• Nalini Anand 2
• 1 Department of Emergency Medicine , Johns Hopkins University , Baltimore , Maryland , USA
• 2 Center for Global Health Studies , John E Fogarty International Center , Bethesda , Maryland , USA
• 3 Office of Emergency Care Research , National Institutes of Health , Bethesda , Maryland , USA
• 4 Department of Emergency Medicine , Medical College of Wisconsin , Milwaukee , Wisconsin , USA
• Correspondence to Dr Junaid Razzak; junaid.razzak{at}jhu.edu

Quality emergency medical care is critical to reducing the burden of disease in low-income and middle-income countries (LMICs) and protecting the health of populations during disasters and epidemics. However, conducting research in emergency care settings in LMIC settings entails unique methodological and operational challenges. Therefore, new approaches and strategies that address these challenges need to be developed and will require increased attention from scientists, academic institutions and the global health research funding community. Research priorities to address emergency care in LMICs have also not been well defined, resulting in limited research output from LMICs. This manuscript frames the efforts of four multidisciplinary working groups, which were established under the auspices of the Fogarty International Center as part of the Collaborative on Enhancing Emergency Care Research in LMICs and serves as an introduction to this series, which identifies challenges and solutions in the context of emergency care research in LMICs. The objective of this introductory paper is to articulate the need for emergency care research in LMICs and underscore its future promise. We present public health arguments for greater investment in emergency care research, identify barriers to develop and conduct research, and present a list of research priorities for community organizations, academic institutions and funding agencies. We conclude that advances in emergency care research will be critical to achieve national and global health targets, such as the Sustainable Development Goals (SDGs), and to ensure that evidence informs how such research is best conducted.

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/bmjgh-2019-001486

Statistics from Altmetric.com

Request permissions.

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

Summary box

Relatively low research investments and lack of expertise in emergency care research have resulted in considerable disparities between the burden of emergency diseases and research output.

Despite challenges, there are multiple compelling reasons to conduct and invest in emergency care research and research capacity building in low-income and middle-income countries.

The Collaborative on Enhancing Emergency Care Research in LMICs effort recommends: strengthening emergency care research capacity, providing opportunities for collaboration and networking, increasing support for research and training from the research funding community and philanthropic organisations, standardising definitions of outcomes and exploring the use of technology for emergency care research.

Introduction

Approximately half of the total burden of diseases in low-income and middle-income countries (LMICs) is caused by time-sensitive emergency or acute illnesses and injuries. 1–3 According to the Disease Control Priorities Project (DCP2), as much as 45% of the disease burden in LMICs can be at least partially addressed by an effective and functional emergency care system. Five of the most frequent causes of death in LMICs—ischaemic heart disease, stroke, lower respiratory infections, chronic obstructive pulmonary disease (COPD) and diarrheal diseases, primarily present as an emergency, have time-sensitive treatments and show improved outcomes with quality acute care. The same is true for many causes of maternal and neonatal deaths, as well as injuries. 4 A recent analysis has shown a fivefold difference between the prevalence rates of emergency, time-sensitive diseases in high-income versus low-income countries. 2 Effective emergency medical care can serve as a health system intervention impacting health outcomes for a significant percentage of people dying or suffering disabilities in LMICs. Similarly, emergency medical care is a critical healthcare system during public health emergencies caused by various forms of humanitarian crises ( figure 1 ). The recent Ebola outbreak in West Africa highlighted the need to strengthen acute and emergency care systems in LMICs, while benefiting the global community. For purposes of this Supplement and the Collaborative on Enhancing Emergency Care Research in LMICs (CLEER), we focus on emergency care at the individual level.

• Download figure
• Open in new tab
• Download powerpoint

Scope of emergency care.

Definition of emergency care

The term emergency care means different things in different contexts. As shown in figure 2 , our definition encompasses the three essential components of emergency care, that is, time, location and diagnoses/symptoms.

Definition of emergency care.

For this series, we have limited the timeframe to care provided to a patient with acute, potentially life-threatening/disabling symptoms within the first 6 hours of contact with a health facility/provider. The time period of 6 hours captures treatment strategies and critical decisions for many conditions, such as sepsis, myocardial infarction, strokes, acute injury and maternal haemorrhage. The second component, location, generally includes emergency departments, ambulances, urgent care centres, and so on. In places where formal ambulances and emergency departments do not exist or have variable definitions, we define location as the location of the patient, or wherever initial life-saving care can be provided. The third component is the disease/symptom dimension, which includes a considerable number of conditions that can be classified as emergency or conditions, including injuries/trauma, myocardial infarction, stroke, COPD, asthma, allergic reactions, sepsis, maternal haemorrhage and pneumonia. Often early in emergency care, diagnoses are unclear and a patient’s journey starts with certain key symptoms, such as chest pain, severe headache, loss of consciousness or focal weakness. Therefore, the working definition of emergency care combines the time dimension of the first 6 hours with patients presenting potentially life-threatening symptoms or diagnosis anywhere in the healthcare system.

Public health imperative

Strong emergency care systems based on robust evidence are critical to advancing global health. However, conducting research in the context of emergency care involves many unique challenges. This Supplement lays out an agenda for tackling these challenges. There are multiple compelling reasons to invest in emergency care research and research capacity building in LMICs.

Burden of emergency diseases: Emergency, time-sensitive illnesses contribute to the majority of the disease burden in LMICs. According to Chang et al , 60% of disability-adjusted life years in LMICs are caused by emergency medical conditions. 4

Cost-effectiveness of emergency care interventions: Data on the cost-effectiveness of major public health interventions identified emergency medical interventions as some of the most cost-effective. For example, DCP defined the availability of volunteer prehospital care/ambulance services as the second most cost-effective public health intervention. Similarly, aspirin for myocardial infarctions and formal paramedic-run emergency medical care were identified as 6th and 21st most cost-effective interventions. 1

Emergency care systems are sources of important data and can help to better define the epidemiology for acute diseases, such as injuries, myocardial infarctions, cerebrovascular diseases and infections, and serve as surveillance systems during epidemics, such as Ebola, influenza and Zika. The acute care setting can also serve as a site for clinical trials for acute medical and surgical interventions.

Effective emergency care systems can serve as settings for public health interventions for difficult to reach populations: There are successful examples from high-income countries (HICs) on the role of emergency care systems in health promotion and disease prevention, such as smoking, drug and alcohol dependence, domestic violence, self-harm, hypertension screening and referral, and injury prevention. 5

Global health security: The concept of ‘health security’, or the protection from health threats, has recently been recognised as one of the most critical international security issues—particularly in light of the recent Ebola and Zika virus outbreaks. 6 In response to these increasing global health security concerns, efforts to build capacity in infectious disease and all-hazards disaster preparedness and response among developing and developed countries alike is an urgent priority.

Need for context-specific interventions in LMICs: Differences in disease profile and patient characteristics in LMICs require that interventions are properly tailored to specific contexts and not automatically transferred from HICs to LMICs. For example, early data on resuscitation have highlighted crucial differences in emergency patients in some LMICs, which require a different approach to resuscitation. A study by Maitland et al showed the harmful effects of implementing fluid resuscitation guidelines developed in the USA for treating children in Sub-Saharan Africa. 7

Global health and development priorities: The United Nations SDGs expect countries to achieve ambitious targets to reduce mortality and morbidity due to non-communicable diseases, road traffic injuries, and newborn and maternal deaths, which will remain unachievable without strong emergency care systems. 8 Table 1 presents the individual SDG targets and their relationships to emergency care.

• View inline

Sustainable development goals and emergency care

Investments in emergency care research

The National Institutes of Health (NIH) is just one of many funding organisations that share responsibility for supporting critical global health research priorities, but it is nonetheless informative to examine NIH investments in emergency care research. In general, NIH spends about 0.7% of its research budget on new research projects in emergency care. 9 In 2014 that amounted to US$25.5 million, but a further US$34.6 million supported ongoing (rather than new) emergency care research. 9 Among six specialties reviewed (emergency medicine, family medicine, internal medicine, obstetrics-gynaecology, paediatrics, and psychiatry and surgery), emergency medicine was the fifth-lowest in terms of funding per resident in training. 10 An unpublished review of a decade of funding to six specialties revealed that emergency medicine faculty (which is a subset of all those performing research in emergency care ) had the lowest number of NIH grants funded over the 10-year period. 11

Research capacity in emergency care in LMICs is limited. While there has been a significant increase in the number of clinical training programmes in Africa, Latin America and Asia, the focus of these programmes is service delivery and a few programmes have an academic focus or support. Notably, NIH has funded research training programmes, such as the Fogarty Global Injury and Trauma Research Training Program, to support emergency medical care research capacity building, among other areas. 12 This is a relatively small programme and unique effort, given the magnitude of impact emergency care can have on the public health outcomes.

In terms of research output, a PubMed search for the term ‘emergency care’ identified a total of 169 315 articles of which 8064 were identified as ‘clinical trials’ during a 10-year period of 2008–2018. When the search was limited to publications with authors from the current low-income countries (Cambodia, Chad, South Sudan, Tanzania, Zimbabwe, Comoros, Haiti, Benin, Nepal, Mali, Sierra Leone, Burkina Faso, Afghanistan, Uganda, Rwanda, Mozambique, Togo, Guinea-Bissau, North Korea, Ethiopia, Eritrea, Guinea, Gambia, Madagascar, Niger, Democratic Republic of Congo, Liberia, Central African Republic, Burundi, Malawi and Somalia), the total number of publications went down to 1344 (0.79%). Of these, only 44 were clinical trials (0.54%).

Research challenges in emergency care in LMICs

Research in the acute care context in LMICs is challenging for a variety of reasons. Some of these challenges are described below:

Defining and capturing the population of interest: Medical emergencies can happen at any location and because emergency care is provided at any location—from home to transport to the different levels of health facilities—it is often difficult to consistently capture all patients presenting with diseases or symptoms of interest to the researchers. Also, at least initially, patients present with symptoms and not diagnoses; since most of the health research is funded by and focused on diagnoses, this adds another level of complexity. The diagnostic certainty is further compromised in low-resource settings due to the limitation of diagnostic capabilities and trained personnel in emergency care settings.

Defining interventions and outcomes: Interventions are relatively easy to define in emergency care, while outcomes are often difficult to frame. As described in the manuscripts on emergency care clinical research and emergency health systems research in this Supplement, longer-term and more meaningful outcomes are often not available for many emergency care interventions. Outcomes are frequently defined by results in the first few hours of presentation and include either mortality outcomes or health services outcomes, such as admission versus discharge from the hospital. While emergency care interventions are short-term, long-term outcomes need to be captured as well. 13

Study design and data collection: There are clear challenges in data collection, data analysis and comparability of research findings. 14 Data collection is impacted by the acute, often life-threatening nature of disease presentation, the time sensitivity of interventions, the dynamic and volatile research environment and the over-burdened infrastructure. Data analysis is affected by symptom-based diagnosis, the availability of triage information and concerns about confounders in the environment. Data comparison presents challenges due to a lack of standardised data definitions. 13 In most low-resource settings, emergency care data capture is not a priority for the already stretched emergency care system. Clinical information is often captured through a paper-based data system and is rarely archived unless patients are admitted to the hospital. In one review, only 10% of emergency department-based studies from LMICs used a specific diagnosis coding system. 15

Ethical issues: Privacy, community engagement, fair participant selection and the ability to give and obtain quality informed consent in emergency care settings can be difficult. As discussed in the Ethics paper in this series, these challenges are intensified in LMICs by multiple factors including weak health infrastructure, high patient volumes, overworked providers and especially vulnerable populations. 16 Gaps remain regarding ethical guidelines and regulations for research and best practices.

Research capacity and research environment: Few academic departments in LMICs focus on emergency care. Emergency care remains largely a hospital service with no academic home in medical schools and universities.

Collaborative on Enhancing Emergency Care Research in LMICs

In July 2017, the Center for Global Health Studies at the Fogarty International Center at the NIH, convened a group of researchers with expertise in emergency care in LMICs to explore pressing research priorities in emergency care in LMICs, as part of the CLEER. The 39 expert participants were accepted from a pool of applicants and subsequently divided into four working groups of 7–12 focusing on (1) ethics, (2) surveillance and registries, (3) health systems and (4) clinical research. The participants represented 16 different countries and were mainly emergency medicine clinicians in both HICs and LMICs, joined by a few bioethicists and paediatricians. The group met physically at NIH for 2 days in July 2017 and then continued to teleconference several times over the next year in the four separate working groups.

The goal of CLEER is to promote research that improves outcomes for patients and populations with acute life-threatening or disabling conditions, focused on the care provided in the first minutes to hours of illness or injury. The groups’ mandate was to (1) identify important research gaps and critical research questions based on the level of the current evidence ( table 2 ) and (2) explore the methodological issues in answering some of these questions with a focus on population, design, outcomes, ethics and research environment and support structure.

Key research gaps and questions

CLEER was not intended to duplicate existing work focused on strengthening emergency care research. Previous efforts to examine how to best strengthen research in acute care settings and have largely been limited to the USA and Europe, and thus have not addressed the specific challenges for acute care research in LMICs. The Society of Academic Emergency Medicine did call a consensus meeting in 2013 to identify gaps and develop a research agenda for acute care services delivery in LMICs. The conference and resulting publication provided a broad research agenda with specific questions related to strengthening and sustaining effective acute care systems. 16 CLEER has built on this agenda, focusing on four distinct aspects of research conducted in emergency care settings: emergency care surveillance and emergency care registries, clinical emergency care research, establishing economic value of emergency care and research on emergency care system and emergency care research ethics.

Recommendations

Strengthening emergency care research capacity in lmics.

Almost all subgroups of CLEER highlight the need for building the individual and institutional capacity for research in emergency care in LMICs. There have been few successful models, such as the Fogarty International Center’s D43 training grant mechanism, which has helped emergency care research capacity in South Asia and Africa. Similarly, the Medical Education Partnership Initiative targeted academic capacity in emergency medicine in a few institutions in Sub-Saharan Africa. More targeted programmes on emergency care research would provide support and incentives for research institutions in HICs to collaborate and support emergency care researchers in LMICs.

Create opportunities for collaboration and networking

There are several professional societies and groups with an interest in various aspects of emergency care. Besides the societies in emergency medicine, national and international associations of paediatrics, surgery, infectious diseases and critical care include emergency care as part of their larger portfolio. However, CLEER is the first multidisciplinary group specifically targeting emergency care research in LMICs. If formalised, such groups can provide the necessary structure for global collaboration and networking.

Funding and support for emergency care research

Challenges with respect to funding include the fact that disease-focused requests for proposals often do not clearly fit the syndrome/symptom-based patient presentations in the emergency care setting. Also, ethical and logistical challenges make these grants less competitive in contrast to cleaner, stable research environments in non-emergency settings. Support specifically for research in emergency care settings would enable the science to grow and research methodologies in emergency medicine to be developed such that emergency medicine researchers can compete with more established fields of medicine and public health.

Standardised credible outcome measures

All of the CLEER subgroups highlight the difficulty in defining the input and outcome indicators for emergency care—at the individual, population and system level. Further work needs to be encouraged by the specialty societies to develop credit indicators, their definitions and method of measurement.

Explore use of technology for research

The surveillance and clinical research groups of CLEER highlight the need for better use of technology, especially mobile technology, for data collection as well as potential clinical interventions.

Emergency care is a critical entryway into the healthcare system and a key determinant of individual and population health, especially in LMICs. In this Supplement, experts articulate research gaps, needs and opportunities, while presenting a way forward with some innovative solutions. Specifically, the CLEER effort calls for strengthening emergency care research capacity, providing opportunities for collaboration and networking, increasing support for research and training from the research funding community and philanthropic organisations, standardising definitions of outcomes and exploring the use of technology for emergency care research.

• Mabweijano J , et al
• Reynolds TA ,
• Rubiano AM , et al
• Razzak JA ,
• Abujaber S ,
• Reynolds TA , et al
• Bernstein SL ,
• D’Onofrio G
• Heymann DL ,
• Takemi K , et al
• Maitland K ,
• Opoka RO , et al
• The United Nations
• Shofer FS , et al
• Fogarty International Center,
• Bisanzo M ,
• Dworkis D , et al
• Dickert NW ,
• Cairns CB , et al
• Beecroft B ,
• Hardcastle TC , et al

Handling editor Seye Abimbola

Contributors JR, BB and NA conceptualised and drafted the manuscript. JB and SH contributed to various sections of the manuscript and reviewed several drafts, providing critical inputs. JR created all tables and figures.

Funding This work was partly supported by the Center for Global Health Studies at the Fogarty International Center, National Institutes of Health, USA.

Disclaimer The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position or policy of the US National Institutes of Health, the US Department of Health and Human Services or any other institutions with which authors are affiliated.

Competing interests None declared.

Patient consent for publication Not required.

Provenance and peer review Not commissioned; externally peer reviewed.

Data availability statement The data that support the figures in this manuscript are available upon request from the corresponding author.

Read the full text or download the PDF:

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings
• My Bibliography
• Collections
• Citation manager

Save citation to file

Email citation, add to collections.

• Create a new collection
• Add to an existing collection

Add to My Bibliography

Your saved search, create a file for external citation management software, your rss feed.

• Search in PubMed
• Search in NLM Catalog
• Add to Search

The use of the word "quiet" in the emergency department is not associated with patient volume: A randomized controlled trial

Affiliations.

• 1 Rutgers Robert Wood Johnson Medical School, Piscataway, NJ, USA. Electronic address: [email protected].
• 2 Rutgers University School of Public Health, Piscataway, NJ, USA.
• 3 Robert Wood Johnson Medical School, Department of Emergency Medicine, Piscataway, NJ, USA. Electronic address: [email protected].
• PMID: 35339973
• DOI: 10.1016/j.ajem.2022.03.020

PubMed Disclaimer

Conflict of interest statement

Declaration of Competing Interest JEG, POS, and JTB do not have any conflicts of interest to disclose.

Similar articles

• Impact of Attending Physicians' Comments on Residents' Workloads in the Emergency Department: Results from Two J(^o^)PAN Randomized Controlled Trials. Kuriyama A, Umakoshi N, Fujinaga J, Kaihara T, Urushidani S, Kuninaga N, Ichikawa M, Ienaga S, Sasaki A, Ikegami T. Kuriyama A, et al. PLoS One. 2016 Dec 9;11(12):e0167480. doi: 10.1371/journal.pone.0167480. eCollection 2016. PLoS One. 2016. PMID: 27936189 Free PMC article. Clinical Trial.
• The influence of quotations uttered in emergency service triage traffic and hospitalization (Quiet). Norkus CL, Butler AL, Smarick SD. Norkus CL, et al. Open Vet J. 2019 Apr;9(1):99-102. doi: 10.4314/ovj.v9i1.17. Epub 2019 Mar 29. Open Vet J. 2019. PMID: 31086774 Free PMC article.
• Validation of the modified Skåne emergency department assessment of patient load (mSEAL) model for emergency department crowding and comparison with international models; an observational study. Wretborn J, Starkenberg H, Ruge T, Wilhelms DB, Ekelund U. Wretborn J, et al. BMC Emerg Med. 2021 Feb 22;21(1):21. doi: 10.1186/s12873-021-00414-6. BMC Emerg Med. 2021. PMID: 33618658 Free PMC article.
• Emergency physician workload modeling. Dubinsky I. Dubinsky I. CJEM. 2012 Jul;14(4):215-20. doi: 10.2310/8000.2012.120532. CJEM. 2012. PMID: 22813394 Review.
• [Workload in emergency departments : A Problem for personnel and patients?]. Skowron N, Wilke P, Bernhard M, Hegerl U, Gries A. Skowron N, et al. Anaesthesist. 2019 Nov;68(11):762-769. doi: 10.1007/s00101-019-00686-5. Anaesthesist. 2019. PMID: 31690959 Review. German.
• Debunking the myth of using "quiet" in clinical departments: an integrative overview of available literature. Umar TP, Jain N. Umar TP, et al. Ann Med Surg (Lond). 2022 Oct 6;82:104792. doi: 10.1016/j.amsu.2022.104792. eCollection 2022 Oct. Ann Med Surg (Lond). 2022. PMID: 36268415 Free PMC article. No abstract available.

Publication types

• Search in MeSH

LinkOut - more resources

Full text sources.

• ClinicalKey
• Elsevier Science
• Ovid Technologies, Inc.
• Citation Manager

NCBI Literature Resources

MeSH PMC Bookshelf Disclaimer

The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.

Recency of Suicide Attempt, Ideation, and Reattempt in the Emergency Department: Managing Youth With a Past Attempt

Information & authors, metrics & citations, view options, conclusions, setting and participants.

Reattempt within 3 months post‐ED‐discharge

Statistical analyses.

Recency of Past Attempt Before Index ED Visit, Full Sample

Ed disposition, full sample, past attempt and past month si, past attempt and no past month si, reattempt post‐ed‐discharge and recency of past attempt/ideation, associations between recency of past attempt and reattempt.

Associations Between Recency of SI and Reattempt

Clinical Implications: Detecting and Managing Suicide Risk

Limitations, information, published in.

Funding Information

Export citations.

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu .

View options

Login options.

Already a subscriber? Access your subscription through your login credentials or your institution for full access to this article.

Not a subscriber?

Subscribe Now / Learn More

PsychiatryOnline subscription options offer access to the DSM-5-TR ® library, books, journals, CME, and patient resources. This all-in-one virtual library provides psychiatrists and mental health professionals with key resources for diagnosis, treatment, research, and professional development.

Need more help? PsychiatryOnline Customer Service may be reached by emailing [email protected] or by calling 800-368-5777 (in the U.S.) or 703-907-7322 (outside the U.S.).

Share article link

Copying failed.

PREVIOUS ARTICLE

Next article, request username.

Can't sign in? Forgot your username? Enter your email address below and we will send you your username

If the address matches an existing account you will receive an email with instructions to retrieve your username

Create a new account

Change password, password changed successfully.

Your password has been changed

Reset password

Can't sign in? Forgot your password?

Enter your email address below and we will send you the reset instructions

If the address matches an existing account you will receive an email with instructions to reset your password.

Your Phone has been verified

As described within the American Psychiatric Association (APA)'s Privacy Policy and Terms of Use , this website utilizes cookies, including for the purpose of offering an optimal online experience and services tailored to your preferences. Please read the entire Privacy Policy and Terms of Use. By closing this message, browsing this website, continuing the navigation, or otherwise continuing to use the APA's websites, you confirm that you understand and accept the terms of the Privacy Policy and Terms of Use, including the utilization of cookies.

Transforming the understanding and treatment of mental illnesses.

Información en español

Celebrating 75 Years! Learn More >>

• Opportunities & Announcements
• Funding Strategy for Grants
• Grant Writing & Approval Process
• Managing Grants
• Clinical Research
• Small Business Research

Navigator Emergency Department Diversion Models for Non-Urgent Mental Health Concerns

Mary Acri, Ph.D.  Division of Services and Intervention Research  

The purpose of this concept is to support research examining the effectiveness, implementation, adoption and scale-up of patient navigation emergency department (ED) diversion models for youth with non-urgent mental health concerns and their caregivers. 

Up to 40% of ED visits by youth are for non-urgent mental health concerns such as symptoms of depression, anxiety, and maladaptive behaviors. A non-urgent ED visit is defined as one in which a delay of several hours would not increase the potential for an adverse outcome to occur. Commonly, caregivers who are overwhelmed or unsure about how to address their child’s mental health needs utilize the ED as a safety net; additionally, EDs are widely perceived as a primary point of entry into mental health services, circumventing barriers due to a congested mental health service system. However, non-urgent ED visits are problematic because: (1) youth are unlikely to see a mental health professional or receive evidence-based mental health services, (2) caregivers are unlikely to receive emotional support, information about their child’s mental health and treatment options, and other family strengthening supports, and, (3) the family is unlikely to be linked to mental health services beyond a passive referral or have barriers to help seeking addressed in a meaningful way.

Patient navigation, an evidence-based practice that guides individuals through the health care system, is a promising approach to support caregivers and connect youth to needed mental health services. However, there is limited knowledge regarding the effectiveness and implementation of patient navigation models for children and adolescents with non-urgent mental health concerns and their caregivers. Additionally, there is a considerable gap in ED diversion models that aim to strengthen the family and facilitate service utilization.

The proposed concept would support clinical trials that pilot and fully test the effectiveness of patient navigation ED diversion models that (a) triage youth with varying mental health acuity and provide a level of risk/corresponding service response, (b) provide family strengthening supports to caregivers (e.g., emotional support, mental health knowledge) and facilitate engagement in community mental health services (c) utilize novel technologies to monitor/track symptoms, engagement in community mental health services, and ED utilization over time, and (d) advance understanding about how, why and for whom these models may work NIMH encourages practice partner approaches with the hopes of informing study design and ensuring that . findings that can be readily put into practice. This concept aligns with Goal 4 of the NIMH Strategic Plan for Research that calls for developing innovative service delivery models and expediting the adoption, sustained implementation, and continuous improvement of evidence-based mental health services. 

An official website of the United States government

Here's how you know

Official websites use .gov A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

•   Facebook
•   Twitter
•   Linkedin
•   Digg
•   Reddit
•   Pinterest
•   Email

Latest Earthquakes |    Chat Share Social Media  

The Future of Climate Research at the USGS – Our Climate Science Plan is Released

The new USGS Climate Science Plan provides guidelines for conducting the bureau’s climate science, sets priorities, goals, and strategies, and identifies outcomes as well as opportunity gaps 

On September 6, the USGS released the  U.S. Geological Survey Climate Science Plan—Future Research Directions , the culmination of a two-year effort by the Climate Science Plan Writing Team. The team was charged with identifying the major climate science topics of future concern and developing an integrated approach to conducting climate science in support of the USGS, Department of the Interior (DOI), and administration priorities. The overarching purpose of the plan was to define the scope and delivery of critical climate science, identify future research directions, and outline opportunities to increase our climate science capacity and expand our research portfolio.  

Climate is one of the primary drivers of environmental change and a priority in defining science conducted across all USGS mission areas. USGS climate science provides the nation with forward-looking, evidence-based information and approaches to assist in planning for and adapting to a changing world. For the first time, the USGS Climate Science Plan provides guidelines for conducting the bureau’s climate science, emphasizing the transdisciplinary nature of the work. The plan embraces co-produced science and Indigenous Knowledge, understanding that climate change disproportionately affects less resilient communities. And no science plan would be complete without focusing on clear, consistent, and equitable communication of our scientific activities. The guidelines acknowledge the USGS’s unique climate science niche within DOI and the federal government, the role our science plays in potentially informing policy, as well as the relevance of our research for the nation, our stakeholders, and our international partners.  

The plan highlights three future climate science research directions: 1) characterizing climate change and associated impacts, 2) assessing climate change risks and developing approaches to mitigate climate change, and 3) providing climate science tools and support.  

Characterizing climate change and its impacts includes goals related to long-term, broad-scale monitoring, providing leadership on greenhouse gas emissions on DOI lands, collaborating with federal programs and other agencies to study climate impacts on ecosystems, and improving data synthesis both within the USGS and between the USGS and agency partners. Key goals related to assessing and reducing climate change risk include linking climate change impacts to risk assessments; reducing uncertainties in models and designing early warning systems; and creating decision support tools to inform and expand mitigation and adaptation measures, particularly through collaboration with land management agencies, use of nature-based solutions, or integration with federal greenhouse gas monitoring efforts. To provide climate adaptation services, the USGS’s goals are to facilitate co-production of knowledge, enhance data capabilities, build capacity through development of training curricula, and coordinate with other agencies.  

Twelve specific goals are identified to achieve these future research directions and are supported by specific strategies and expected impacts and outcomes of research investments.  

• Conduct long-term, broad-scale, and multidisciplinary measurements and monitoring and research activities to define, quantify, and predict the impacts of climate change on natural and human systems .  
• Provide leadership to standardize measuring, monitoring, reporting, and verifying greenhouse gas emissions, lateral carbon fluxes, and carbon sinks across lands managed by the DOI. 
• Provide science capacity, training, tools, and infrastructure to Tribal partners; support Tribal-led science initiatives. 
• Conduct climate change research in partnership with the broader climate science community. 
• Develop improved data synthesis methods through collaborative and open science across mission areas and between the USGS and bureau partners.  
• Translate climate change impacts into risk assessments in support of risk management strategies. 
• Develop new and improved risk assessments, models, and approaches for mitigating climate change, adapting to its impacts, and reducing uncertainties; design early warning systems for risk mitigation. 
• Investigate climate change mitigation strategies and create decision-science support tools to inform climate change mitigation and adaptation. 
• Provide a framework that facilitates knowledge co-production needed to inform policy decisions. 
• Provide access to USGS data and information through novel integration and visualization approaches. 
• Build capacity within the USGS and DOI through development of scientific training curricula. 
• Coordinate science and capacity building efforts broadly across the federal government. 

To ensure successful implementation of the USGS Climate Science Plan, the authors outline numerous opportunities, including strategic planning for workforce development, the recruitment of the next generation of climate scientists, social scientists, and support staff, and investments in long-term scientific innovation across USGS mission areas. The plan also details the existing USGS climate science capabilities to demonstrate the breadth of our work, while also identifying capacity gaps.  

By defining the USGS’s long-term climate science priorities, we can ensure that critical science themes and activities will continue and expand along with newly available data, innovative technologies, and evolving scientific and public information needs. This will position the USGS to continue to serve as one of the nation’s leading climate science agencies.  

Special thanks to the members of the writing team for their contributions : 

Tamara Wilson – Western Geographic Science Center  

Ryan Boyles – Southeast Climate Adaptation Science Center 

Nicole DeCrappeo – Northwest Climate Adaptation Science Center  

Judith Drexler – California Water Science Center  

Kevin Kroeger – Wood Hole Coastal and Marine Science Center 

Rachel Loehman – Alaska Science Center 

John Pearce – Alaska Science Center 

Mark Waldrop – Geology, Minerals, Energy, and Geophysics Science Center 

Peter Warwick – Geology, Energy, and Minerals Science Center 

Anne Wein – Western Geographic Science Center 

Sarah Zeigler – St. Petersburg Coastal and Marine Science Center 

Doug Beard – National Climate Adaptation Science Center 

Tamara Wilson   Acting   Assistant Regional Administrator, Southwest Climate Adaptation Science Center 

Research Geographer, Western Geographic Science Center 

Doug Beard   Director, National Climate Adaptation Science Center 

Get Our News

These items are in the RSS feed format (Really Simple Syndication) based on categories such as topics, locations, and more. You can install and RSS reader browser extension, software, or use a third-party service to receive immediate news updates depending on the feed that you have added. If you click the feed links below, they may look strange because they are simply XML code. An RSS reader can easily read this code and push out a notification to you when something new is posted to our site.

Climate Adaptation Science Centers News

Climate News

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

The PMC website is updating on October 15, 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• BMJ Open Qual
• v.7(1); 2018

Improving the wait time to consultation at the emergency department

Yuzeng shen.

1 Department of Emergency Medicine, Singapore General Hospital, Singapore, Singapore

Lin Hui Lee

2 Operations and Performance Management, Singapore General Hospital, Singapore, Singapore

Prolonged wait times at the emergency department (ED) are associated with increased morbidity and mortality, and decreased patient satisfaction. Reducing wait times at the ED is challenging. The objective of this study is to determine if the implementation of a series of interventions would help decrease the wait time to consultation (WTC) for patients at the ED within 6 months. Interventions include creation of a common board detailing work output, matching manpower to patient arrivals and adopting a team-based model of care. A retrospective analysis of the period from January 2015 to May 2016 was undertaken to define baseline duration for WTC. Rapid PDSA (Plan, Do, Study, Act) cycles were used to implement a series of interventions, and changes in wait time were tracked, with concurrent patient load, rostered manpower and number of admissions from ED. Results of the interventions were tracked from 1 October 2016 to 30 April 2017. There was improvement in WTC within 6 months of initiation of interventions. The improvements demonstrated appeared consistent and sustained. The average 95th centile WTC decreased by 38 min to 124 min, from the baseline duration of 162 min. The median WTC improved to 21 min, compared with a baseline timing of 24 min. The improvements occurred despite greater patient load of 4317 patients per month, compared with baseline monthly average of 4053 patients. There was no increase in admissions from ED and no change in the amount of ED manpower over the same period. We demonstrate how implementation of low-cost interventions, enabling transparency, equitable workload and use of a team-based care model can help to bring down wait times for patients. Quality improvement efforts were sustained by employing a data-driven approach, support from senior clinicians and providing constant feedback on outcomes.

Timeliness and efficiency form two of the six domains of healthcare quality as defined by the Institute of Medicine. 1 At the emergency department (ED), prolonged wait times have been found to be associated with increased morbidity and mortality, and decreased patient satisfaction. 2 3 Increasing attendances to the ED, an ageing population and greater disease complexity, coupled with manpower and physical infrastructural limitations, have made reducing wait times at the ED more difficult.

A team-based approach to care of patients has been found to be associated with better patient outcomes and improved patient satisfaction, 4–6 likely due to closer communication and coordination between patients and care providers. When implemented at the ED, a team-based patient care has been shown to have positive outcomes. 7–9

Within the department, there have been prior efforts to decrease patients’ wait time to consultation (WTC), which did not attain the desired outcome due to manpower and space limitations, fragmentation and variability of care, the lack of tracking and auditing of work output, and the absence of feedback mechanisms to staff regarding individual work output.

Singapore General Hospital (SGH) is the largest public hospital in Singapore, with 1600 inpatient beds. The Department of Emergency Medicine (DEM) sees more than 135 000 patients annually. On arrival at DEM, patients are triaged according to specific patient acuity categories (PAC) as defined by the Ministry of Health of Singapore (MOH), 10 ranging from priority 1 (P1) patients who are critically ill and require immediate management and resuscitation, P2 patients who have acute medical conditions or severe symptoms that require very early medical attention, and the P3 and P4 patients who have minor emergency and non-emergency conditions, respectively.

Depending on the patient’s condition and assigned PAC score, the patient is assigned to various treatment areas within the department for consultation with attending doctors. There is senior doctor supervision of all treatment areas within the department. P1 patients are usually seen at the resuscitation area, P2 patients at the critical care area and P3 patients at the ambulatory care area. The department staffing is structured towards patient acuity, with 70% of doctors staffed to cover P1 and P2 patients. The close proximity between each treatment area allows doctors to cross-cover areas during periods of surge when there may be a resultant imbalance of attendances between each treatment area.

One of the MOH key performance indicators for DEM is the P2 patients’ WTC. The clock begins when patients register on arrival at DEM and ends when the consultation begins. The SGH target for the 95th centile WTC is currently 76 min, with a threshold waiting time of 122 min. The targets are derived from a moving average of monthly institutional WTC over a predetermined period. Over the years, increasing attendances to the ED, an ageing population and greater disease complexity, coupled with manpower and physical infrastructural limitations, have made achieving the target more difficult.

As prolonged wait times and ED crowding are associated with poorer patient outcomes, the quality improvement team aimed to reduce the 95th centile WTC for P2 patients to less than 76 min in 6 months.

The team first embarked on a root cause analysis to identify reasons for prolonged wait time. The main cause identified was inefficiencies in the consultation model for P2 patients after they were triaged and assigned to their respective treatment areas. The lack of a standardised consultation model meant that interactions between junior doctors and supervising senior doctors regarding patient management plans can vary as much as up to 2 hours when comparing between different shifts within the same day, corrected for patient load. Another significant cause identified was a lack of real-time feedback regarding the work output of doctors on the floor in helping clear the queue of unseen waiting patients.

Baseline measurement

Baseline data from January 2015 to May 2016 was collected, and analysis of 32,420 P2 patient visits was done. To understand the processes and problems faced on the ground, an actual state analysis was performed. All work processes were assessed and extensive data analysis was conducted over a month. A value stream map of the P2 patient journey was created, detailing the process flow, time elements and analysis of limitations. This helped to highlight possible operational constraints and areas for improvement.

Effort was focused to understand the processes that affected WTC directly. Rework and chaos were notable during the consultation stage of the value stream map. With the current consultation practice in ED, care management plans may be modified (rework) when junior doctors seek the opinion of the supervising senior doctors only at the later stage of patient care. It was estimated that an average of 7.3% of orders were cancelled, with each of them amounting to an average of 34 min delay for a P2 patient.

In a dynamic (chaos) environment of ED, it is also very easy for staff to get lost in their own list of tasks before attending to a new patient, and hence there is little command and control of how each area is coping with their queue and workload. Exacerbated further by a lack of manpower during peak periods, the chaos was represented by an average delay of 1 hour before a doctor reviews a patient in the critical care area.

The baseline preintervention median WTC was 24 min and the 95th centile WTC was 162 min. The 95th centile WTC was found to be largely dependent on how fast DEM doctors attend to the P2 patients after they have been triaged. A comparison of the hourly patient arrival pattern with the hourly WTC performance revealed that a significant backlog of patients formed after 11:00, which lasted for the rest of the day. This problem was exacerbated by the slow outflow of admitted patients to inpatient wards. As a result, more ED resources were used to care for these patients.

The team was led by an emergency physician, with two emergency nurse clinicians and an analyst from the hospital’s Operations and Performance Management department. The team was further supported by IT analysts, who provided data for baseline analysis, and backed by senior clinicians who approved interventions and ensured their smooth implementation. Members of the team assisted in the dissemination of information and instructions, and encouraged compliance during implementation. They also gathered ground feedback to identify issues faced and for ideas to further improve processes.

To ensure the sustainability of interventions, feedback was extensively sought from the ground to shape implementation. Although the main goal for the team was to decrease the WTC, all interventions were made with the prevailing aim of improving patient safety. We focused on three areas for improvement and used rapid PDSA (Plan, Do, Study, Act) cycles: the real-time reflection of patient flow and work output, the levelling of workload to staff ratio, and the implementation of a team-based model of care.

PDSA cycle 1

Doctors and nurses did not have visibility to the department’s overall workload, as well as how each area was coping with their patient load. To tackle the issue, a board was constructed and placed within the care area for P2 patients. This board detailed the names of the junior doctors on shift with accompanying columns for the patients seen by them. On initiating consultation with a patient, the junior doctors would place the patient’s sticker within their personal column during their shift.

The board, although manual in nature, enabled real-time visibility of workload distribution and patients seen, and allowed senior doctor in the team to identify and aid junior doctors who may be bogged down by patients with complex medical conditions or requiring difficult procedures. Reminders were given to doctors, verbally and via email feedback, emphasising the importance of complying with the logging of the patients seen. Implementation cost was negligible, mainly secondary to the stationery used.

PDSA cycle 2

A review of the department manpower and throughput showed a mismatch between patients’ arrival pattern and junior doctor manpower on shift. The mismatch in the demand and supply of junior doctors resulted in a challenging workload of up to 3.4 new patients hourly and an accumulation of patients from 11:00 until the end of the day.

We sought to adjust the roster to match the supply of doctors on shift to the anticipated patient arrivals by time of day. This would greatly reduce any backlog of patients waiting for consultation and allow doctors to see patients at a manageable pace.

Based on the ideal junior doctor output of seeing 1.5 new patients hourly over a shift, the junior doctors’ roster was modified to match patients’ arrival pattern. This resulted in more doctors being deployed during the day when patient arrivals tend to peak, and allowed junior doctors to see patients at a manageable rate. This allowed more time to be devoted to complex medical cases without being overwhelmed by a huge backlog of patients waiting for consultation.

PDSA cycle 3

The team found that it was common practice among junior doctors to seek the opinion of the supervising senior doctors only at the later stage of patient care, leading to additional time spent on modifying care management plans and ordering additional investigations. To encourage junior doctors to seek the inputs of senior doctors in the early stage of patient care, a team-based model of care was implemented as a solution.

Previously, senior doctors, junior doctors and nurses mostly worked in silos. The team-based model of care grouped a senior doctor, junior doctors and nurses into a team. Two teams were assigned to the care area for P2 patients and received triaged patients in an alternating manner to ensure equitable workload for each team. With this model, staff will have to work with each other in teams, bringing about better division of labour and more effective communication within each team.

Junior doctors were given the mandate to seek the senior doctor’s input upfront so that patient management plans can be initiated and carried out with minimal deviation. Nurses were encouraged to participate in patient care by initiating department protocols, such as providing analgesia for patients in pain and carrying out investigations for other selected conditions.

The team-based model of care enhanced the clarity of patient care between doctors and promoted ownership and accountability for patients. Between shift changes, patients were handed over within teams, therefore strengthening the coherence and continuation of patient care. Furthermore, with the aid of the board in PDSA 1, staff were able to see how each team was coping and manage their queue accordingly.

To sustain the interventions, daily wait times and individual doctor output were tracked. The team actively looked for significant deviations in the tracked data and sought to identify system issues early. Individual doctors were fed back regarding their work output and counselled by their supervisors when required.

The period from the initiation of intervention on 1 October 2016 up to 30 April 2017 was evaluated. During this period, there were two rotations of junior doctors into the department. The median and 95th centile WTC were calculated over the said period, as represented by a control chart ( figure 1 ).

Daily Department of Emergency Medicine priority 2 (P2) wait time to consultation (WTC) median and 95th centile performance. PDSA, Plan, Do, Study, Act.

The 95th centile WTC saw the greatest positive effect from implementation of the PDSA cycles. Over the period of intervention, the average 95th centile WTC was 124 min, which was a decrease of 38 min from the baseline duration of 162 min ( table 1 ). The implementation of PDSA cycle 3 saw significant and sustained improvements in the WTC, with an average of 114 min during the period after PDSA cycle 3, lower than the threshold target of 122 min. This further supports the utility of a team-based care model at the ED.

Comparison of intervention period with baseline period

WTC, wait time to consultation.

The median WTC improved to 21 min, compared with a baseline timing of 24 min ( table 1 ). The effect on median WTC was seen with implementation of PDSA cycle 1 and maintained through the study period. The implementation of PDSA cycles 2 and 3 resulted in further marginal improvement in median WTC.

The improvements in wait times occurred during the period with an average P2 patient load of 4317 patients per month, which was greater than the baseline monthly average of 4053 patients ( table 1 ). Department manpower remained stable. After the implementation of all three PDSA cycles, improvement was observed in several process outcome and measures. There was a 15% decrease in inpatient admissions from ED of P2 patients compared with the prior period (66% pre-intervention to 52% post-intervention; P<0.05), thereby relieving the daily requirement of an average of 20 beds.

The flow of patients through the consultation stage has improved. Time to review by a doctor in critical care area has improved by 14 min (60 min pre-intervention to 46 min post-intervention; P<0.05). There is also a 0.6% decrease in the cancellations of orders for patients’ management plan (7.3% pre-implementation to 6.7% post-implementation; P<0.05).

There was a 1.6% decrease for patient admissions from the ED compared with the prior period (56.0% post-intervention and 57.6% pre-intervention; P=0.004). The total time duration to ED disposition also saw a decrease of 17 min during the study period, compared with the prior period (145 min post-intervention and 162 min pre-intervention; P<0.001).

Feedback from doctors and nurses within the department was uniformly positive. Commonly cited reasons included increased efficiencies, greater clarity and a transparent yet equitable workload. Feedback was markedly positive for the group of junior doctors who experienced the pre-intervention phase and post-intervention phase within the same posting period. As the study was focused on quantitative outcomes, no formal pre-intervention and post-intervention comparison on feedback was carried out.

To ensure patient safety and outcomes were not compromised, reattendances to SGH ED within 72 hours were tracked as a balancing measure to make sure the quality of care for all ED patients would not be compromised for pursuing a faster process time. This indicator was measured with patients who were discharged home and subsequently returned to SGH ED within 72 hours. Comparing with the rates of reattendances 6 months prior to implementation, the rates during post-implementation have remained steady at an average of 3.4% (P>0.1).

Lessons learnt

Data analytics played a significant role in the successful implementation of PDSA cycles. The team could identify significant areas for improvement with in-depth analysis of baseline data, and results were corroborated with root cause analysis findings. The ability to identify patterns in patient arrivals allowed us to match department manpower to periods of surge. Expected work output, based on frequently refreshed data, was communicated to staff, enabling clarity and equitable workload.

To gain constant buy-in from staff on the ground and ensure sustainability of the interventions, results and findings were shared with doctors and nurses regularly through the study period. We identified best practices and encouraged staff to share positive actions that contributed to better team-based care for the patient. Feedback was also constantly received from staff during the study period and has helped to further adjust interventions.

Numbers and data gleaned were distilled into easy-to-understand charts and tables, and disseminated to the department, to keep everyone updated on the progress of the quality improvement effort. Having regular feedback to stakeholders and department staff helped to allay concerns early and allowed a visual translation of the hard work performed on the ground. This helped improve acceptance and compliance to the interventions. Senior clinicians were extremely supportive of interventions and enabled the smooth implementation of measures taken.

Using a simple board that highlighted everyone’s workload contribution for the day was effective, as the transparency it offered allowed juniors on shift to keep pace with one another, allowed fairer sharing of load and gave them the psychological effect of wanting to keep up with their peers’ output. There was clarity into the distribution of work done within the area by individual, and allowed seniors on shift to visualise the tempo of their shift and easy identification of junior doctors in need of assistance.

Limitations

Although the median WTC target was achieved, we were not able to meet the 95th centile target of 76 min, and thus did not attain the stated goal of this study. WTC starts from the time the patient is registered. Subsequent analysis postintervention has identified the wait time to triage now as a significant contributor to both median and 95th centile WTC. We are currently conducting a separate quality improvement effort to decrease the wait time for triage.

During periods of prolonged wait for inpatient beds for patients admitted from ED, the increased workload due to boarded patients places strains on the team-based care model, as teams need to care for both incoming and boarded patients at the same time. This manifests in increased WTC during days with higher proportion of boarded patients.

Despite initiatives on the ground to improve processes within the ED, wait times also depend on the smooth flow of admitted patients out of the ED into the inpatient wards. Studies have shown that boarded patients at the ED contribute to overcrowding, affect the delivery of care and may lead to increased costs and length of stay. 11 12

Currently, data on daily WTC and individual work output are retrospectively collated every 2–4 weeks for feedback and analysis. To have to manually paste patient stickers on the board also contributes to time spent by doctors, which may be better used on actual patient care. We are looking to develop an intelligent electronic version of the board, which removes the need for use of stickers, and that also allows for real-time capability for feedback and automated reporting.

Implementing the package of changes to improve the P2 WTC was a major effort that required a data-driven approach, catalysed by the staffs’ conviction to improve patient outcomes. We demonstrated how implementation of low-cost interventions, enabling equitable workload and how breaking down work silos with the use of a team-based care model can help to bring down wait times for patients.

The insights gleaned from the analysed data allowed the team to make quick and informed decisions, while teamwork and staff buy-in ensured the sustainability of the project. The team is currently looking to further decrease the total time duration to ED disposition for patients by implementation of further quality improvement initiatives targeting other aspects of the patient’s journey at the ED.

Acknowledgments

The authors would like to acknowledge the following: Dr Evelyn Wong, Head DEM; Tan Puay Hwang, Nurse Clinician, DEM; Muqtasidatum Binte Mustaffa, Nurse Clinician, DEM; and Ryan Koh Zhao Yuan, Hospital Executive, OPM.

Contributors: All authors contributed to the design and writing, data collection and interpretation of the results of this study.

Competing interests: None declared.

Ethics approval: The SingHealth Centralised Institutional Review Board exempted the study from ethical approval as the work was deemed a quality improvement study and not a study on human subjects.

Provenance and peer review: Not commissioned; externally peer reviewed.