Background: Healthcare workers faced unique challenges during the early months of the COVID-19 pandemic which necessitated rapid adaptation. Clinical event debriefings (CEDs) are one tool that teams can use to reflect after events and identify opportunities for improving their performance and their processes. There are few reports of how teams have used CEDs in the COVID-19 pandemic. Our aim is to explore the issues discussed during COVID-19 CEDs and propose a framework model for qualitatively analyzing CEDs.
Methods: This was a descriptive, qualitative study of a hospital-wide CED program at a quaternary children's hospital between March and July 2020. CEDs were in-person, team-led, voluntary, scripted sessions using the Debriefing in Suspected COVID-19 to Encourage Reflection and Team Learning (DISCOVER-TooL). Debriefing content was qualitatively analyzed using constant comparative coding with an integrated deductive and inductive approach. A novel conceptual framework was proposed for understanding how debriefing content can be employed at various levels in a health system for learning and improvement.
Results: Thirty-one debriefings were performed and analyzed. Debriefings had a median of 7 debriefing participants, lasted a median of 10 min, and were associated with multiple systems-based process improvements. Fourteen themes and 25 subthemes were identified and categorized into a novel Input-Mediator-Output-Input Debriefing (IMOID) model. The most common themes included communication, coordination, situational awareness, team member roles, and clinical standards.
Conclusions: Teams identified diverse issues in their debriefing discussions related to areas of high performance and opportunities for improvement in their care of COVID-19 patients. This model may help healthcare systems to understand how CED tools can be used to accelerate organizational learning to promote safety and improve outcomes in changing clinical environments.
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http://dx.doi.org/10.1186/s41077-022-00226-z | DOI Listing |
JAMA Intern Med
January 2025
Research and Development, Veterans Affairs Puget Sound Health Care System, Seattle, Washington.
Importance: SARS-CoV-2, influenza, and respiratory syncytial virus (RSV) contribute to many hospitalizations and deaths each year. Understanding relative disease severity can help to inform vaccination guidance.
Objective: To compare disease severity of COVID-19, influenza, and RSV among US veterans.
JAMA Netw Open
January 2025
Division of Acute Care Surgery, Department of Surgery, University of Michigan, Ann Arbor.
ACS Sens
January 2025
Department of Engineering Physics, McMaster University, 1280 Main Street West, L8S 4L8 Hamilton, Ontario, Canada.
Current approaches for classifying biosensor data in diagnostics rely on fixed decision thresholds based on receiver operating characteristic (ROC) curves, which can be limited in accuracy for complex and variable signals. To address these limitations, we developed a framework that facilitates the application of machine learning (ML) to diagnostic data for the binary classification of clinical samples, when using real-time electrochemical measurements. The framework was applied to a real-time multimeric aptamer assay (RT-MAp) that captures single-frequency (12.
View Article and Find Full Text PDFBrain Struct Funct
January 2025
Department of Radiology, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, 330006, Jiangxi Province, China.
A significant proportion of patients who have recovered from COVID-19 suffer from persistent symptoms, referred to as "post-acute sequelae of SARS-CoV-2 infection (PASC)". Abnormal brain intrinsic activity has been observed in PASC patients, but the patterns of frequency-dependent intrinsic activity in the PASC and non-PASC (recovered COVID-19 patients without persistent symptoms) groups and their association with neuropsychiatric sequelae remain unclear in PASC. Twenty-nine PASC patients, 27 non-PASC subjects, and 31 healthy controls (HCs) were recruited.
View Article and Find Full Text PDFEmerg Microbes Infect
January 2025
Institute for Medical Virology, Goethe University, University Hospital Frankfurt, Frankfurt am Main, Germany.
Viremia defined as detectable SARS-CoV-2 RNA in the blood is a potential marker of disease severity and prognosis in COVID-19 patients. Here, we determined the frequency of viremia in serum of two independent COVID-19 patient cohorts within the German National Pandemic Cohort Network (German: tionales andemie horten etzwerk, NAPKON) with diagnostic RT-PCR against SARS-CoV-2. A cross-sectional cohort with 1,122 COVID-19 patients (German: , SUEP) and 299 patients recruited in a high-resolution platform with patients at high risk to develop severe courses (German: , HAP) were tested for viremia.
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