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      Emergency department crowding and hospital transformation during COVID-19, a retrospective, descriptive study of a university hospital in Stockholm, Sweden

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          Abstract

          Objectives

          COVID-19 presents challenges to the emergency care system that could lead to emergency department (ED) crowding. The Huddinge site at the Karolinska university hospital (KH) responded through a rapid transformation of inpatient care capacity together with changing working methods in the ED. The aim is to describe the KH response to the COVID-19 crisis, and how ED crowding, and important input, throughput and output factors for ED crowding developed at KH during a 30-day baseline period followed by the first 60 days of the COVID-19 outbreak in Stockholm Region.

          Methods

          Different phases in the development of the crisis were described and identified retrospectively based on major events that changed the conditions for the ED. Results were presented for each phase separately. The outcome ED length of stay (ED LOS) was calculated with mean and 95% confidence intervals. Input, throughput, output and demographic factors were described using distributions, proportions and means. Pearson correlation between ED LOS and emergency ward occupancy by phase was estimated with 95% confidence interval.

          Results

          As new working methods were introduced between phase 2 and 3, ED LOS declined from mean (95% CI) 386 (373–399) minutes to 307 (297–317). Imaging proportion was reduced from 29 to 18% and admission rate increased from 34 to 43%. Correlation (95% CI) between emergency ward occupancy and ED LOS by phase was 0.94 (0.55–0.99).

          Conclusions

          It is possible to avoid ED crowding, even during extreme and quickly changing conditions by leveraging previously known input, throughput and output factors. One key factor was the change in working methods in the ED with higher competence, less diagnostics and increased focus on rapid clinical admission decisions. Another important factor was the reduction in bed occupancy in emergency wards that enabled a timely admission to inpatient care. A key limitation was the retrospective study design.

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          Most cited references16

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          Covid-19 in Critically Ill Patients in the Seattle Region — Case Series

          Abstract Background Community transmission of coronavirus 2019 (Covid-19) was detected in the state of Washington in February 2020. Methods We identified patients from nine Seattle-area hospitals who were admitted to the intensive care unit (ICU) with confirmed infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Clinical data were obtained through review of medical records. The data reported here are those available through March 23, 2020. Each patient had at least 14 days of follow-up. Results We identified 24 patients with confirmed Covid-19. The mean (±SD) age of the patients was 64±18 years, 63% were men, and symptoms began 7±4 days before admission. The most common symptoms were cough and shortness of breath; 50% of patients had fever on admission, and 58% had diabetes mellitus. All the patients were admitted for hypoxemic respiratory failure; 75% (18 patients) needed mechanical ventilation. Most of the patients (17) also had hypotension and needed vasopressors. No patient tested positive for influenza A, influenza B, or other respiratory viruses. Half the patients (12) died between ICU day 1 and day 18, including 4 patients who had a do-not-resuscitate order on admission. Of the 12 surviving patients, 5 were discharged home, 4 were discharged from the ICU but remained in the hospital, and 3 continued to receive mechanical ventilation in the ICU. Conclusions During the first 3 weeks of the Covid-19 outbreak in the Seattle area, the most common reasons for admission to the ICU were hypoxemic respiratory failure leading to mechanical ventilation, hypotension requiring vasopressor treatment, or both. Mortality among these critically ill patients was high. (Funded by the National Institutes of Health.)
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            Emergency department crowding: A systematic review of causes, consequences and solutions

            Background Emergency department crowding is a major global healthcare issue. There is much debate as to the causes of the phenomenon, leading to difficulties in developing successful, targeted solutions. Aim The aim of this systematic review was to critically analyse and summarise the findings of peer-reviewed research studies investigating the causes and consequences of, and solutions to, emergency department crowding. Method The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. A structured search of four databases (Medline, CINAHL, EMBASE and Web of Science) was undertaken to identify peer-reviewed research publications aimed at investigating the causes or consequences of, or solutions to, emergency department crowding, published between January 2000 and June 2018. Two reviewers used validated critical appraisal tools to independently assess the quality of the studies. The study protocol was registered with the International prospective register of systematic reviews (PROSPERO 2017: CRD42017073439). Results From 4,131 identified studies and 162 full text reviews, 102 studies met the inclusion criteria. The majority were retrospective cohort studies, with the greatest proportion (51%) trialling or modelling potential solutions to emergency department crowding. Fourteen studies examined causes and 40 investigated consequences. Two studies looked at both causes and consequences, and two investigated causes and solutions. Conclusions The negative consequences of ED crowding are well established, including poorer patient outcomes and the inability of staff to adhere to guideline-recommended treatment. This review identified a mismatch between causes and solutions. The majority of identified causes related to the number and type of people attending ED and timely discharge from ED, while reported solutions focused on efficient patient flow within the ED. Solutions aimed at the introduction of whole-of-system initiatives to meet timed patient disposition targets, as well as extended hours of primary care, demonstrated promising outcomes. While the review identified increased presentations by the elderly with complex and chronic conditions as an emerging and widespread driver of crowding, more research is required to isolate the precise local factors leading to ED crowding, with system-wide solutions tailored to address identified causes.
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              A conceptual model of emergency department crowding.

              Emergency department (ED) crowding has become a major barrier to receiving timely emergency care in the United States. Despite widespread recognition of the problem, the research and policy agendas needed to understand and address ED crowding are just beginning to unfold. We present a conceptual model of ED crowding to help researchers, administrators, and policymakers understand its causes and develop potential solutions. The conceptual model partitions ED crowding into 3 interdependent components: input, throughput, and output. These components exist within an acute care system that is characterized by the delivery of unscheduled care. The goal of the conceptual model is to provide a practical framework on which an organized research, policy, and operations management agenda can be based to alleviate ED crowding.
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                Author and article information

                Contributors
                bjorn.af.ugglas@ki.se
                Journal
                Scand J Trauma Resusc Emerg Med
                Scand J Trauma Resusc Emerg Med
                Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine
                BioMed Central (London )
                1757-7241
                28 October 2020
                28 October 2020
                2020
                : 28
                : 107
                Affiliations
                [1 ]GRID grid.24381.3c, ISNI 0000 0000 9241 5705, Theme of Emergency and Reparative Medicine, , Karolinska University Hospital, ; 141 86 Stockholm, Sweden
                [2 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Department of Medicine, , Solna, Karolinska Institutet, ; 171 77 Stockholm, Sweden
                [3 ]GRID grid.24381.3c, ISNI 0000 0000 9241 5705, Department of Medical Informatics, , Karolinska University Hospital, ; 141 86 Stockholm, Sweden
                [4 ]GRID grid.4714.6, ISNI 0000 0004 1937 0626, Department of Learning, Informatics, Management and Ethics, , Karolinska Institutet, ; 171 77 Stockholm, Sweden
                [5 ]GRID grid.411384.b, ISNI 0000 0000 9309 6304, Division of Surgery, Orthopaedics and Oncology, , Linköping University Hospital, ; 581 85 Linköping, Sweden
                [6 ]GRID grid.5640.7, ISNI 0000 0001 2162 9922, Department of Biomedical and Clinical Sciences, , Linköping University, ; 581 83 Linköping, Sweden
                Author information
                http://orcid.org/0000-0003-2841-0661
                Article
                799
                10.1186/s13049-020-00799-6
                7592192
                33115521
                b699b166-a2b7-413c-b863-102ec143f58d
                © The Author(s) 2020

                Open AccessThis 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.

                History
                : 20 May 2020
                : 7 October 2020
                Funding
                Funded by: Karolinska University Hospital
                Funded by: Idorsia Pharmaceuticals
                Funded by: Hjärt-Lungfonden (SE)
                Award ID: 20170804
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100004348, Stockholms Läns Landsting;
                Award ID: 20170686
                Award Recipient :
                Categories
                Original Research
                Custom metadata
                © The Author(s) 2020

                Emergency medicine & Trauma
                emergency department,crowding,covid-19,surge capacity,bed occupancy
                Emergency medicine & Trauma
                emergency department, crowding, covid-19, surge capacity, bed occupancy

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