Team dynamics in a COVID-19 intensive care unit: A qualitative study.

BACKGROUND: During the COVID-19 pandemic, new intensive care units (ICUs) were created and clinicians were assigned or volunteered to work in these ICUs. These new ICU teams were newly formed and may have had varying practice styles which could affect team dynamics. The purpose of our qualitative descriptive study was to explore clinician perceptions of team dynamics in this newly formed ICU and specifically understand the challenges and potential improvements in this environment to guide future planning and preparedness in ICUs. METHODS: We conducted 14 semistructured one-on-one interviews with six nurses and eight physicians from a newly formed 36- to 50-bed medical ICU designed for COVID-19 patients in a teaching hospital. We purposively sampled and recruited ICU nurses, medical/surgical nurses, fellows, and attending physicians (with pulmonary/critical care and anaesthesia training) to participate. Participants were asked about team dynamics in the ICU, its challenges, and potential solutions. We then used a rapid analytic approach by first deductively categorising interview data into themes, based on our interview guide, to create a unique data summary for each interview. Then, these data were transferred to a matrix to compare data across all interviews and inductively analysed these data to provide deeper insights into team dynamics in ICUs. RESULTS: We identified two themes that impacted team dynamics positively (facilitator) and negatively (barrier): interpersonal factors (individual character traits and interactions among clinicians) and structural factors (unit-level factors affecting workflow, organisation, and administration). Clinicians had several suggestions to improve team dynamics (e.g., scheduling to ensure clinicians familiar with one another worked together, standardisation of care processes across teams, and disciplines). CONCLUSIONS: In a newly formed COVID ICU, interpersonal factors and structural factors impacted the team's ability to work together. Considering team dynamics during ICU reorganisation is crucial and requires thoughtful attention to interpersonal and structural factors.

COVID-19 Transmission to Health Care Personnel During Tracheostomy Under a Multidisciplinary Safety Protocol.

BACKGROUND: Tracheostomies are highly aerosolizing procedures yet are often indicated in patients with COVID-19 who require prolonged intubation. Robust investigations of the safety of tracheostomy protocols and provider adherence and evaluations are limited. OBJECTIVES: To determine the rate of COVID-19 infection of health care personnel involved in COVID-19 tracheostomies under a multidisciplinary safety protocol and to investigate health care personnel's attitudes and suggested areas for improvement concerning the protocol. METHODS: All health care personnel involved in tracheostomies in COVID-19-positive patients from April 9 through July 11, 2020, were sent a 22-item electronic survey. RESULTS: Among 107 health care personnel (80.5%) who responded to the survey, 5 reported a positive COVID-19 test result (n = 2) or symptoms of COVID-19 (n = 3) within 21 days of the tracheostomy. Respondents reported 100% adherence to use of adequate personal protective equipment. Most (91%) were familiar with the tracheostomy protocol and felt safe (92%) while performing tracheostomy. Suggested improvements included creating dedicated tracheostomy teams and increasing provider choices surrounding personal protective equipment. CONCLUSIONS: Multidisciplinary engagement in the development and implementation of a COVID-19 tracheostomy protocol is associated with acceptable safety for all members of the care team.

One-Year Functional, Cognitive, and Psychological Outcomes Following the Use of Extracorporeal Membrane Oxygenation in Coronavirus Disease 2019: A Prospective Study.

To prospectively describe 1-year outcomes, with a focus on functional outcome, cognitive outcome, and the burden of anxiety, depression, and post-traumatic stress disorder, in coronavirus disease 2019 patients managed with extracorporeal membrane oxygenation. DESIGN: Prospective case series. SETTING: Tertiary extracorporeal membrane oxygenation center in the United States. PATIENTS: Adult coronavirus disease 2019 acute respiratory distress syndrome patients managed with extracorporeal membrane oxygenation March 1, 2020, to July 31, 2020. INTERVENTIONS: Baseline variables, treatment measures, and short-term outcomes were obtained from the medical record. Survivors were interviewed by telephone, a year following the index intensive care admission. Functional outcome was assessed using the modified Rankin Scale and the World Health Organization Disability Assessment Scale 2.0. Cognitive status was assessed with the 5-minute Montreal Cognitive Assessment. The Hospital Anxiety and Depression Scale was used to screen for anxiety and depression. Screening for post-traumatic stress disorder was performed with the Posttraumatic Stress Disorder Checklist 5 instrument. MEASUREMENTS AND MAIN RESULTS: Twenty-three patients were managed with extracorporeal membrane oxygenation, 14 (61%) survived to hospital discharge. Thirteen (57%) were alive at 1 year. One patient was dependent on mechanical ventilation, another intermittently required supplemental oxygen at 1 year. The median modified Rankin Scale score was 2 (interquartile range, 1-2), median World Health Organization Disability Assessment Scale 2.0 impairment score was 21% (interquartile range, 6-42%). Six of 12 previously employed individuals (50%) had returned to work, and 10 of 12 (83%) were entirely independent in activities of daily living. The median Montreal Cognitive Assessment score was 14 (interquartile range, 13-14). Of 10 patients assessed with Hospital Anxiety and Depression Scale, 4 (40%) screened positive for depression and 6 (60%) for anxiety. Four of 10 (40%) screened positive for post-traumatic stress disorder. CONCLUSIONS: Functional impairment was common a year following the use of extracorporeal membrane oxygenation in coronavirus disease 2019, although the majority achieved independence in daily living and about half returned to work. Long-term anxiety, depression, and post-traumatic stress disorder were common, but cognitive impairment was not.

Tracheostomy for COVID-19 respiratory failure: timing, ventilatory characteristics, and outcomes.

BACKGROUND: Whereas data from the pre-pandemic era have demonstrated that tracheostomy can accelerate liberation from the ventilator, reduce need for sedation, and facilitate rehabilitation, concerns for healthcare worker safety have led to disagreement on tracheostomy placement in COVID-19 patients. Data on COVID-19 patients undergoing tracheostomy may inform best practices. Thus, we report a retrospective institutional cohort experience with tracheostomy in ventilated patients with COVID-19, examining associations between time to tracheostomy and duration of mechanical ventilation in relation to patient characteristics, clinical course, and survival. METHODS: Clinical data were extracted for all COVID-19 tracheostomies performed at a quaternary referral center from April-July 2020. Outcomes studied included mortality, adverse events, duration of mechanical ventilation, and time to decannulation. RESULTS: Among 64 COVID-19 tracheostomies (13% of COVID-19 hospitalizations), patients were 64% male and 42% African American, with a median age of 54 (range, 20-89). Median time to tracheostomy was 22 (range, 7-60) days and median duration of mechanical ventilation was 39.4 (range, 20-113) days. Earlier tracheostomy was associated with shortened mechanical ventilation (R2=0.4, P<0.01). Median decannulation time was 35.3 (range, 7-79) days. There was 19% mortality and adverse events in 45%, mostly from bleeding in therapeutically anticoagulated patients. CONCLUSIONS: Tracheostomy was associated with swifter liberation from the ventilator and acceptable safety for physicians in this series of critically ill COVID-19 patients. Patient mortality was not increased relative to historical data on acute respiratory distress syndrome (ARDS). Future studies are required to establish conclusions of causality regarding tracheostomy timing with mechanical ventilation, complications, or mortality in COVID-19 patients.

Predicting Intensive Care Transfers and Other Unforeseen Events: Analytic Model Validation Study and Comparison to Existing Methods.

BACKGROUND: COVID-19 has led to an unprecedented strain on health care facilities across the United States. Accurately identifying patients at an increased risk of deterioration may help hospitals manage their resources while improving the quality of patient care. Here, we present the results of an analytical model, Predicting Intensive Care Transfers and Other Unforeseen Events (PICTURE), to identify patients at high risk for imminent intensive care unit transfer, respiratory failure, or death, with the intention to improve the prediction of deterioration due to COVID-19. OBJECTIVE: This study aims to validate the PICTURE model's ability to predict unexpected deterioration in general ward and COVID-19 patients, and to compare its performance with the Epic Deterioration Index (EDI), an existing model that has recently been assessed for use in patients with COVID-19. METHODS: The PICTURE model was trained and validated on a cohort of hospitalized non-COVID-19 patients using electronic health record data from 2014 to 2018. It was then applied to two holdout test sets: non-COVID-19 patients from 2019 and patients testing positive for COVID-19 in 2020. PICTURE results were aligned to EDI and NEWS scores for head-to-head comparison via area under the receiver operating characteristic curve (AUROC) and area under the precision-recall curve. We compared the models' ability to predict an adverse event (defined as intensive care unit transfer, mechanical ventilation use, or death). Shapley values were used to provide explanations for PICTURE predictions. RESULTS: In non-COVID-19 general ward patients, PICTURE achieved an AUROC of 0.819 (95% CI 0.805-0.834) per observation, compared to the EDI's AUROC of 0.763 (95% CI 0.746-0.781; n=21,740; P<.001). In patients testing positive for COVID-19, PICTURE again outperformed the EDI with an AUROC of 0.849 (95% CI 0.820-0.878) compared to the EDI's AUROC of 0.803 (95% CI 0.772-0.838; n=607; P<.001). The most important variables influencing PICTURE predictions in the COVID-19 cohort were a rapid respiratory rate, a high level of oxygen support, low oxygen saturation, and impaired mental status (Glasgow Coma Scale). CONCLUSIONS: The PICTURE model is more accurate in predicting adverse patient outcomes for both general ward patients and COVID-19 positive patients in our cohorts compared to the EDI. The ability to consistently anticipate these events may be especially valuable when considering potential incipient waves of COVID-19 infections. The generalizability of the model will require testing in other health care systems for validation.