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Dreiher J, Einav S, Codish S, Frenkel A. Emergency Department Admission Rates, Waiting Times, and Mortality: An Observational Study in the Tertiary Center Most Proximal to Gaza During a Military Conflict. Disaster Med Public Health Prep 2023; 17:e463. [PMID: 37608756 DOI: 10.1017/dmp.2023.45] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
OBJECTIVES Military conflicts may be ongoing and encompass multiple medical facilities. This study investigated the impact of a military conflict ("Protective Edge" PE) on emergency department (ED) function in a tertiary medical center. METHODS Visits to the ED during PE (July-August 2014) were compared with ED visits during July-August 2013 and 2015 with regard to admission rates, waiting times and 30-d mortality. Odds ratios (ORs) adjusted for confounders were used for the multivariable regression models. RESULTS There were 32,343 visits during PE and 74,279 visits during the comparison periods. A 13% decrease in the daily number of visits was noted. During PE, longer waiting times were found, on average 0.25 h longer, controlling for confounders. The difference in waiting times was greater in medicine and surgery. Admission rates were on average 10% higher during PE military conflict, controlling for confounders. This difference decreased to 7% controlling for the daily number of visits. Thirty-day mortality was significantly increased during PE (OR = 1.42; 95% CI: 1.18-1.70). ORs for mortality during PE were significantly higher in medicine (OR = 1.45; 95% CI: 1.15-1.81) and pediatrics (OR = 4.40; 95% CI: 1.33-14.5). CONCLUSIONS During an ongoing military conflict, waiting times, admission rates, and mortality were statistically significantly increased.
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Affiliation(s)
- Jacob Dreiher
- Hospital Administration, Soroka University Medical Center, and The Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Sharon Einav
- General Intensive Care Unit, Shaare Zedek Medical Center, and Anesthesia and Intensive Care Medicine, Hebrew University-Hadassah Faculty of Medicine, Jerusalem, Israel
| | - Shlomi Codish
- Hospital Administration, Soroka University Medical Center, and The Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Amit Frenkel
- General Intensive Care Unit, Soroka University Medical Center, and The Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
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Halvachizadeh S, Leibovitz D, Held L, Jensen KO, Pape HC, Muller D, Neuhaus V. The number of beds occupied is an independent risk factor for discharge of trauma patients. Medicine (Baltimore) 2022; 101:e31024. [PMID: 36221382 PMCID: PMC9542835 DOI: 10.1097/md.0000000000031024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
Reducing the burden of limited capacity on medical practitioners and public health systems requires a time-dependent characterization of hospitalization rates, such that inferences can be drawn about the underlying causes for hospitalization and patient discharge. The aim of this study was to analyze non-medical risk factors that lead to the discharge of trauma patients. This retrospective cohort study includes trauma patients who were treated in Switzerland between 2011 and 2018. The national Swiss database for quality assurance in surgery (AQC) was reviewed for trauma diagnoses according to the ICD-10 code. Non-medical risk factors include seasonal changes, daily changes, holidays, and number of beds occupied by trauma patients across Switzerland. Individual patient information was aggregated into counts per day of total patients, as well as counts per day of levels of each categorical variable of interest. The ARIMA-modeling was utilized to model the number of discharges per day as a function of auto aggressive function of all previously mentioned risk factors. This study includes 226,708 patients, 118,059 male (age 48.18, standard deviation (SD) 22.34 years) and 108,649 female (age 62.57, SD 22.89 years) trauma patients. The mean length of stay was 7.16 (SD 14.84) days and most patients were discharged home (n = 168,582, 74.8%). A weekly and yearly seasonality trend can be observed in admission trends. The mean number of occupied trauma beds ranges from 3700 to 4000 per day. The number of occupied beds increases on weekdays and decreases on holidays. The number of occupied beds is a positive, independent risk factor for discharge in trauma patients; as the number of occupied beds increases at any given time, so does the risk for discharge. The number of beds occupied represents an independent non-medical risk factor for discharge. Capacity determines triage of hospitalized patients and therefore might increase the risk of premature discharge.
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Affiliation(s)
- Sascha Halvachizadeh
- University Hospital Zurich, Department of Trauma, Zurich, Switzerland
- University of Zurich, Faculty of Medicine, Zürich, Switzerland
- * Correspondence: Sascha Halvachizadeh, University Hospital Zurich, Department of Trauma, Raemistrasse 100, Zurich 8091, Switzerland (e-mail: )
| | - Daniel Leibovitz
- University of Zurich, Epidemiology, Biostatistics and Prevention Institute, Zurich, Switzerland
- Cantonal Hospital Thurgau, Frauenfeld, Department of Surgery, Frauenfeld, Switzerland
| | - Leonhard Held
- University of Zurich, Epidemiology, Biostatistics and Prevention Institute, Zurich, Switzerland
- Cantonal Hospital Thurgau, Frauenfeld, Department of Surgery, Frauenfeld, Switzerland
| | - Kai Oliver Jensen
- University Hospital Zurich, Department of Trauma, Zurich, Switzerland
- University of Zurich, Faculty of Medicine, Zürich, Switzerland
| | - Hans-Christoph Pape
- University Hospital Zurich, Department of Trauma, Zurich, Switzerland
- University of Zurich, Faculty of Medicine, Zürich, Switzerland
| | - Dominik Muller
- University of Zurich, Epidemiology, Biostatistics and Prevention Institute, Zurich, Switzerland
- Cantonal Hospital Thurgau, Frauenfeld, Department of Surgery, Frauenfeld, Switzerland
| | - Valentin Neuhaus
- University Hospital Zurich, Department of Trauma, Zurich, Switzerland
- University of Zurich, Faculty of Medicine, Zürich, Switzerland
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Phattharapornjaroen P, Carlström E, Sivarak O, Tansuwannarat P, Chalermdamrichai P, Sittichanbuncha Y, Kongtoranin L, Phattranonuthai R, Marlow P, Winyuchonjaroen W, Pongpasupa N, Khorram-Manesh A. Community-Based Response to the COVID-19 Pandemic: Case Study of a Home Isolation centre using Flexible Surge Capacity. Public Health 2022; 211:29-36. [PMID: 35994836 PMCID: PMC9276643 DOI: 10.1016/j.puhe.2022.06.025] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 05/29/2022] [Accepted: 06/21/2022] [Indexed: 11/25/2022]
Abstract
Objectives Coronavirus disease 2019 (COVID-19) has consumed many available resources within contingency plans, necessitating new capacity surges and novel approaches. This study aimed to explore the possibility of implementing the concept of flexible surge capacity to reduce the burden on hospitals by focussing on community resources to develop home isolation centres in Bangkok, Thailand. Study design A qualitative study consisted of observational and semi-structured interview data. Methods The development and activities of home isolation centres were observed, and interviews were conducted with leaders and operational workforces. Data were deductively analysed and categorised based on the practical elements necessary in disaster and emergency management. Results Data were categorised into the seven collaborative elements of the major incident medical management and support model. The command-and-control category demonstrated four subcategories: (1) coordination and collaboration; (2) staff engagement; (3) responsibility clarification; and (4) sustainability. Safety presented two subcategories: (1) patients' information privacy and treatment; and (2) personnel safety and privacy. Communication showed internal and external communications subcategories. Assessment, triage, treatment and transport followed the processes of the COVID-19 treatment protocols according to the World Health Organisation (WHO) guidelines and hospital operations. Several supply- and patient-related challenges were identified and managed during centre development. Conclusions The use of community resources, based on the flexible surge capacity concept, is feasible under restricted circumstances and reduced the burden on hospitals during the COVID-19 pandemic. Continuous education among multidisciplinary volunteer teams facilitated their full participation and engagement. The concept of flexible surge capacity may promote an alternative community-based care opportunity, irrespective of emergencies' aetiology.
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Abstract
Introduction: Mass-casualty incidents (MCIs) are events in which many people are injured during the same period of time. This has major implications in regards to practical concerns and planning for both personnel and medical equipment. Smart glasses are modern tools that could help Emergency Medical Services (EMS) in the estimation of the number of potential patients in an MCI. However, currently there is no study regarding the advantage of employing the use of smart glasses in MCIs in Thailand. Study Objective: This study aims to compare the overall accuracy and amount of time used with smart glasses and comparing it to manual counting to assess the number of casualties from the scene. Methods: This study was a randomized controlled trial, field exercise experimental study in the EMS unit of Srinagarind Hospital, Thailand. The participants were divided into two groups (those with smart glasses and those doing manual counting). On the days of the simulation (February 25 and 26, 2022), the participants in the smart glasses group received a 30-minute training session on the use of the smart glasses. After that, both groups of participants counted the number of casualties on the simulation field independently. Results: Sixty-eight participants were examined, and in the smart glasses group, a total of 58.8% (N = 20) of the participants were male. The mean age in this group was 39.4 years old. The most experienced in the EMS smart glasses group had worked in this position for four-to-six years (44.1%). The participants in the smart glasses group had the highest scores in accurately assessing the number of casualties being between 21-30 (98.0%) compared with the manual counting group (89.2%). Additionally, the time used for assessing the number of casualties in the smart glasses group was shorter than the manual counting group in tallying the number of casualties between 11-20 (6.3 versus 11.2 seconds; P = .04) and between 21-30 (22.1 versus 44.5 seconds; P = .02). Conclusion: The use of smart glasses to assess the number of casualties in MCIs when the number of patients is between 11 and 30 is useful in terms of greater accuracy and less time being spent than with manual counting.
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