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Karwa ML, Naqvi AA, Betchen M, Puri AK. In-Hospital Triage. Crit Care Clin 2024; 40:533-548. [PMID: 38796226 DOI: 10.1016/j.ccc.2024.03.001] [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: 05/28/2024]
Abstract
The intensive care unit (ICU) is a finite and expensive resource with demand not infrequently exceeding capacity. Understanding ICU capacity strain is essential to gain situational awareness. Increased capacity strain can influence ICU triage decisions, which rely heavily on clinical judgment. Having an admission and triage protocol with which clinicians are very familiar can mitigate difficult, inappropriate admissions. This article reviews these concepts and methods of in-hospital triage.
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Affiliation(s)
- Manoj L Karwa
- Division of Critical Care Medicine, Albert Einstein College of Medicine / Montefiore Medical Center, Weiler Hospital, 4th Floor, 1825 Eastchester Road, Bronx, NY 10461, USA.
| | - Ali Abbas Naqvi
- Division of Critical Care Medicine, Albert Einstein College of Medicine / Montefiore Medical Center, Moses Division, 111 East 210th Street, Gold Zone (Main Floor), Bronx, NY 10467, USA
| | - Melanie Betchen
- Division of Critical Care Medicine, Albert Einstein College of Medicine / Montefiore Medical Center, Moses Division, 111 East 210th Street, Gold Zone (Main Floor), Bronx, NY 10467, USA
| | - Ajay Kumar Puri
- Division of Critical Care Medicine, Albert Einstein College of Medicine / Montefiore Medical Center, Moses Division, 111 East 210th Street, Gold Zone (Main Floor), Bronx, NY 10467, USA
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Anesi GL, Andrews A, Bai HJ, Bhatraju PK, Brett-Major DM, Broadhurst MJ, Campbell ES, Cobb JP, Gonzalez M, Homami S, Hypes CD, Irwin A, Kratochvil CJ, Krolikowski K, Kumar VK, Landsittel DP, Lee RA, Liebler JM, Lutrick K, Marts LT, Mosier JM, Mukherjee V, Postelnicu R, Rodina V, Segal LN, Sevransky JE, Spainhour C, Srivastava A, Uyeki TM, Wurfel MM, Wyles D, Evans L. Perceived Hospital Stress, Severe Acute Respiratory Syndrome Coronavirus 2 Activity, and Care Process Temporal Variance During the COVID-19 Pandemic. Crit Care Med 2023; 51:445-459. [PMID: 36790189 PMCID: PMC10012837 DOI: 10.1097/ccm.0000000000005802] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
OBJECTIVES The COVID-19 pandemic threatened standard hospital operations. We sought to understand how this stress was perceived and manifested within individual hospitals and in relation to local viral activity. DESIGN Prospective weekly hospital stress survey, November 2020-June 2022. SETTING Society of Critical Care Medicine's Discovery Severe Acute Respiratory Infection-Preparedness multicenter cohort study. SUBJECTS Thirteen hospitals across seven U.S. health systems. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS We analyzed 839 hospital-weeks of data over 85 pandemic weeks and five viral surges. Perceived overall hospital, ICU, and emergency department (ED) stress due to severe acute respiratory infection patients during the pandemic were reported by a mean of 43% ( sd , 36%), 32% (30%), and 14% (22%) of hospitals per week, respectively, and perceived care deviations in a mean of 36% (33%). Overall hospital stress was highly correlated with ICU stress (ρ = 0.82; p < 0.0001) but only moderately correlated with ED stress (ρ = 0.52; p < 0.0001). A county increase in 10 severe acute respiratory syndrome coronavirus 2 cases per 100,000 residents was associated with an increase in the odds of overall hospital, ICU, and ED stress by 9% (95% CI, 5-12%), 7% (3-10%), and 4% (2-6%), respectively. During the Delta variant surge, overall hospital stress persisted for a median of 11.5 weeks (interquartile range, 9-14 wk) after local case peak. ICU stress had a similar pattern of resolution (median 11 wk [6-14 wk] after local case peak; p = 0.59) while the resolution of ED stress (median 6 wk [5-6 wk] after local case peak; p = 0.003) was earlier. There was a similar but attenuated pattern during the Omicron BA.1 subvariant surge. CONCLUSIONS During the COVID-19 pandemic, perceived care deviations were common and potentially avoidable patient harm was rare. Perceived hospital stress persisted for weeks after surges peaked.
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Affiliation(s)
- George L Anesi
- Division of Pulmonary, Allergy, and Critical Care, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA
| | - Adair Andrews
- Society of Critical Care Medicine, Mount Prospect, IL
| | - He Julia Bai
- Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, NE
| | - Pavan K Bhatraju
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington School of Medicine, Seattle, WA
| | - David M Brett-Major
- Department of Epidemiology, College of Public Health, University of Nebraska Medical Center, Omaha, NE
- Global Center for Health Security, University of Nebraska Medical Center, Omaha, NE
| | - M Jana Broadhurst
- Global Center for Health Security, University of Nebraska Medical Center, Omaha, NE
- Department of Pathology and Microbiology, College of Medicine, University of Nebraska Medical Center, Omaha, NE
| | | | - J Perren Cobb
- Departments of Surgery and Anesthesiology, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | | | - Sonya Homami
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington School of Medicine, Seattle, WA
| | - Cameron D Hypes
- Department of Emergency Medicine, College of Medicine, University of Arizona, Tucson, AZ
- Division of Pulmonary, Allergy, Critical Care and Sleep, Department of Medicine, College of Medicine, University of Arizona, Tucson, AZ
| | - Amy Irwin
- Division of Infectious Diseases, Denver Health Medical Center, Denver, CO
| | | | - Kelsey Krolikowski
- Division of Pulmonary, Critical Care, and Sleep Medicine, NYU Grossman School of Medicine, NYU Langone Health, New York, NY
| | | | - Douglas P Landsittel
- Department of Epidemiology and Biostatistics, School of Public Health, Indiana University, Bloomington, IN
| | - Richard A Lee
- Division of Pulmonary Diseases and Critical Care Medicine, University of California, Irvine, School of Medicine, Irvine, CA
| | - Janice M Liebler
- Division of Pulmonary, Critical Care and Sleep Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Karen Lutrick
- Department of Family and Community Medicine, College of Medicine, University of Arizona, Tucson, AZ
| | - Lucian T Marts
- Division of Pulmonary, Allergy, Critical Care and Sleep, School of Medicine, Emory University, Atlanta, GA
| | - Jarrod M Mosier
- Department of Emergency Medicine, College of Medicine, University of Arizona, Tucson, AZ
- Division of Pulmonary, Allergy, Critical Care and Sleep, Department of Medicine, College of Medicine, University of Arizona, Tucson, AZ
| | - Vikramjit Mukherjee
- Division of Pulmonary, Critical Care, and Sleep Medicine, NYU Grossman School of Medicine, NYU Langone Health, New York, NY
| | - Radu Postelnicu
- Division of Pulmonary, Critical Care, and Sleep Medicine, NYU Grossman School of Medicine, NYU Langone Health, New York, NY
| | - Valentina Rodina
- Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - Leopoldo N Segal
- Division of Pulmonary, Critical Care, and Sleep Medicine, NYU Grossman School of Medicine, NYU Langone Health, New York, NY
| | - Jonathan E Sevransky
- Division of Pulmonary, Allergy, Critical Care and Sleep, School of Medicine, Emory University, Atlanta, GA
- Emory Critical Care Center, Emory Healthcare, Atlanta, GA
| | | | - Avantika Srivastava
- Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA
| | - Timothy M Uyeki
- Influenza Division, National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention (CDC), Atlanta, GA
| | - Mark M Wurfel
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington School of Medicine, Seattle, WA
| | - David Wyles
- Division of Infectious Diseases, Denver Health Medical Center, Denver, CO
| | - Laura Evans
- Division of Pulmonary, Critical Care and Sleep Medicine, University of Washington School of Medicine, Seattle, WA
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Chen Z, Bancej C, Lee L, Champredon D. Antigenic drift and epidemiological severity of seasonal influenza in Canada. Sci Rep 2022; 12:15625. [PMID: 36115880 PMCID: PMC9482630 DOI: 10.1038/s41598-022-19996-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 09/07/2022] [Indexed: 12/05/2022] Open
Abstract
Seasonal influenza epidemics circulate globally every year with varying levels of severity. One of the major drivers of this seasonal variation is thought to be the antigenic drift of influenza viruses, resulting from the accumulation of mutations in viral surface proteins. In this study, we aimed to investigate the association between the genetic drift of seasonal influenza viruses (A/H1N1, A/H3N2 and B) and the epidemiological severity of seasonal epidemics within a Canadian context. We obtained hemagglutinin protein sequences collected in Canada between the 2006/2007 and 2019/2020 flu seasons from GISAID and calculated Hamming distances in a sequence-based approach to estimating inter-seasonal antigenic differences. We also gathered epidemiological data on cases, hospitalizations and deaths from national surveillance systems and other official sources, as well as vaccine effectiveness estimates to address potential effect modification. These aggregate measures of disease severity were integrated into a single seasonal severity index. We performed linear regressions of our severity index with respect to the inter-seasonal antigenic distances, controlling for vaccine effectiveness. We did not find any evidence of a statistical relationship between antigenic distance and seasonal influenza severity in Canada. Future studies may need to account for additional factors, such as co-circulation of other respiratory pathogens, population imprinting, cohort effects and environmental parameters, which may drive seasonal influenza severity.
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Affiliation(s)
- Zishu Chen
- National Microbiology Laboratory, Public Health Risk Sciences Division, Public Health Agency of Canada, Guelph, ON, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Christina Bancej
- Surveillance and Epidemiology Division, Centre for Immunization and Respiratory Infectious Disease, Public Health Agency of Canada, Ottawa, ON, Canada
| | - Liza Lee
- Surveillance and Epidemiology Division, Centre for Immunization and Respiratory Infectious Disease, Public Health Agency of Canada, Ottawa, ON, Canada
| | - David Champredon
- National Microbiology Laboratory, Public Health Risk Sciences Division, Public Health Agency of Canada, Guelph, ON, Canada.
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Hong TH, Lee HS, Kim NE, Lee KJ, Kim YK, An JN, Kim JH, Kim HW, Park S. Recent Increases in Influenza-Related Hospitalizations, Critical Care Resource Use, and In-Hospital Mortality: A 10-Year Population-Based Study in South Korea. J Clin Med 2022; 11:jcm11164911. [PMID: 36013150 PMCID: PMC9410240 DOI: 10.3390/jcm11164911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Revised: 08/15/2022] [Accepted: 08/18/2022] [Indexed: 12/05/2022] Open
Abstract
Background: Long-term trends in influenza-related hospitalizations, critical care resource use, and hospital outcomes since the 2009 H1N1 influenza pandemic season have been rarely studied for adult populations. Materials and Methods: Adult patients from the Korean Health Insurance Review and Assessment Service who were hospitalized with influenza over a 10-year period (2009−2019) were analyzed. The incidence rates of hospitalization, critical care resource use, and in-hospital death were calculated using mid-year population census data. Results: In total, 300,152 hospitalized patients with influenza were identified (men, 35.7%; admission to tertiary hospitals, 9.4%). Although the age-adjusted hospitalization rate initially decreased since the 2009 H1N1 pandemic (52.61/100,000 population in 2009/2010), it began to increase again in 2013/2014 and reached a peak of 169.86/100,000 population in 2017/2018 (p < 0.001). The in-hospital mortality rate showed a similar increasing trend as the hospitalization, with a peak of 1.44/100,000 population in 2017/2018 (vs. 0.35/100,000 population in 2009/2010; p < 0.001). The high incidence rates of both hospitalization and in-hospital mortality were mainly attributable to patients aged ≥60 years. The rate of intensive care unit admission and the use of mechanical ventilation, continuous renal replacement therapy and vasopressors have also increased from the 2013/2014 season. The incidence of heart failure was the most frequent complication investigated, with a three-fold increase in the last two seasons since 2009/2010. In multivariate analysis adjusted for covariates, among hospitalized patients, type of hospitals and 2009 H1N1 pandemic season were associated with in-hospital mortality. Conclusions: We confirmed that the rates of hospitalization, critical care resource use, and in-hospital mortality by influenza have increased again in recent years. Therefore, strategies are needed to reduce infections and optimize resource use with a greater focus on older people.
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Affiliation(s)
- Tae Hwa Hong
- Department of Surgery, Hallym University Sacred Heart Hospital, Anyang 14068, Korea
| | - Hyung Seok Lee
- Department of Nephrology, Hallym University Sacred Heart Hospital, Anyang 14068, Korea
| | - Nam-Eun Kim
- Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul 08826, Korea
| | - Kyu Jin Lee
- Department of Pulmonary, Allergy and Critical Care Medicine, Hallym University Sacred Heart Hospital, Anyang 14068, Korea
| | - Yong Kyun Kim
- Department of Infectious Disease, Hallym University Sacred Heart Hospital, Anyang 14068, Korea
| | - Jung Nam An
- Department of Nephrology, Hallym University Sacred Heart Hospital, Anyang 14068, Korea
| | - Joo-Hee Kim
- Department of Pulmonary, Allergy and Critical Care Medicine, Hallym University Sacred Heart Hospital, Anyang 14068, Korea
| | - Hyung Won Kim
- Department of Surgery, Hallym University Sacred Heart Hospital, Anyang 14068, Korea
| | - Sunghoon Park
- Department of Pulmonary, Allergy and Critical Care Medicine, Hallym University Sacred Heart Hospital, Anyang 14068, Korea
- Correspondence:
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Brown J, Bhatnagar M, Gordon H, Goodner J, Cobb JP, Lutrick K. Data Collection during Public Health Emergencies: Design Tenets and Usability of an Electronic Data Capture Tool (Preprint). JMIR Hum Factors 2021; 9:e35032. [PMID: 35679114 PMCID: PMC9227656 DOI: 10.2196/35032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 04/23/2022] [Accepted: 04/23/2022] [Indexed: 11/17/2022] Open
Abstract
Background The Discovery Critical Care Research Network Program for Resilience and Emergency Preparedness (Discovery PREP) partnered with a third-party technology vendor to design and implement an electronic data capture tool that addressed multisite data collection challenges during public health emergencies (PHE) in the United States. The basis of the work was to design an electronic data capture tool and to prospectively gather data on usability from bedside clinicians during national health system stress queries and influenza observational studies. Objective The aim of this paper is to describe the lessons learned in the design and implementation of a novel electronic data capture tool with the goal of significantly increasing the nation’s capability to manage real-time data collection and analysis during PHE. Methods A multiyear and multiphase design approach was taken to create an electronic data capture tool, which was used to pilot rapid data capture during a simulated PHE. Following the pilot, the study team retrospectively assessed the feasibility of automating the data captured by the electronic data capture tool directly from the electronic health record. In addition to user feedback during semistructured interviews, the System Usability Scale (SUS) questionnaire was used as a basis to evaluate the usability and performance of the electronic data capture tool. Results Participants included Discovery PREP physicians, their local administrators, and data collectors from tertiary-level academic medical centers at 5 different institutions. User feedback indicated that the designed system had an intuitive user interface and could be used to automate study communication tasks making for more efficient management of multisite studies. SUS questionnaire results classified the system as highly usable (SUS score 82.5/100). Automation of 17 (61%) of the 28 variables in the influenza observational study was deemed feasible during the exploration of automated versus manual data abstraction.
The creation and use of the Project Meridian electronic data capture tool identified 6 key design requirements for multisite data collection, including the need for the following: (1) scalability irrespective of the type of participant; (2) a common data set across sites; (3) automated back end administrative capability (eg, reminders and a self-service status board); (4) multimedia communication pathways (eg, email and SMS text messaging); (5) interoperability and integration with local site information technology infrastructure; and (6) natural language processing to extract nondiscrete data elements. Conclusions The use of the electronic data capture tool in multiple multisite Discovery PREP clinical studies proved the feasibility of using the novel, cloud-based platform in practice. The lessons learned from this effort can be used to inform the improvement of ongoing global multisite data collection efforts during the COVID-19 pandemic and transform current manual data abstraction approaches into reliable, real time, and automated information exchange. Future research is needed to expand the ability to perform automated multisite data extraction during a PHE and beyond.
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Affiliation(s)
- Joan Brown
- Clinical Operations Business Intelligence, The Keck School of Medicine of the University of Southern California, Los Angeles, CA, United States
| | - Manas Bhatnagar
- Department of Surgery, The Keck School of Medicine of the University of Southern California, Los Angeles, CA, United States
| | - Hugh Gordon
- Akido Labs Inc, Los Angeles, CA, United States
| | | | - J Perren Cobb
- Department of Surgery, The Keck School of Medicine of the University of Southern California, Los Angeles, CA, United States
| | - Karen Lutrick
- Department of Family and Community Medicine, University of Arizona, Tucson, AZ, United States
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