The Society of Critical Care Medicine at 50 Years: ICU Organization and Management

Shift-Level Team Familiarity Is Associated with Improved Outcomes in Mechanically Ventilated Adults

Rationale: Organizing ICU interprofessional teams is a high priority because of workforce needs, but the role of interprofessional familiarity remains unexplored. Objectives: Determine if mechanically ventilated patients cared for by teams with greater familiarity have improved outcomes, such as lower mortality, shorter duration of mechanical ventilation (MV), and greater spontaneous breathing trial (SBT) implementation. Methods: We used electronic health records data of five ICUs in an academic medical center to map interprofessional teams and their ICU networks, measuring team familiarity as network coreness and mean team value. We used patient-level regression models to link team familiarity with patient outcomes, accounting for patient and unit factors. We also performed a split-sample analysis by using 2018 team familiarity data to predict 2019 outcomes. Measurements and Main Results: Team familiarity was measured as the average number of patients shared by each clinician with all other clinicians in the ICU (i.e., coreness) and the average number of patients shared by any two members of the team (i.e., mean team value). Among 4,485 encounters, unadjusted mortality was 12.9%, average duration of MV was 2.32 days, and SBT implementation was 89%; average team coreness was 467.2 (standard deviation [SD], 96.15), and average mean team value was 87.02 (SD, 42.42). A 1-SD increase in team coreness was significantly associated with a 4.5% greater probability of SBT implementation, 23% shorter MV duration, and 3.8% lower probability of dying; the mean team value was significantly associated with lower mortality. Split-sample results were attenuated but congruent in direction and interpretation. Conclusions: Interprofessional familiarity was associated with improved outcomes; assignment models that prioritize familiarity might be a novel solution.

Descriptive Comparison of Two Models of Tele-Critical Care Delivery in a Large Multi-Hospital Health Care System

Introduction: The Society of Critical Care Medicine Tele-Critical Care (TCC) Committee has identified the need for rigorous comparative research of different TCC delivery models to support the development of best practices for staffing, application, and approaches to workflow. Our objective was to describe and compare outcomes between two TCC delivery models, TCC with 24/7 Bedside Intensivist (BI) compared with TCC with Private Daytime Attending Intensivist (PI) in relation to intensive care unit (ICU) and hospital mortality, ICU and hospital length of stay (LOS), cost, and complications across the spectrum of routine ICU standards of care. Methods: Observational cohort study at large health care system in 12 ICUs and included patients, ≥18, with Acute Physiology and Chronic Health Evaluation (APACHE) IVa scores and predictions (October 2016-June 2019). Results: Of the 19,519 ICU patients, 71.7% (n = 13,993) received TCC with 24/7 BI while 28.3% (n = 5,526) received TCC with PI. ICU and Hospital mortality (4.8% vs. 3.1%, p < 0.0001; 12.6% vs. 8.1%, p < 0.001); and ICU and Hospital LOS (3.2 vs. 2.4 days, p < 0.001; 9.8 vs. 7.2 days, p < 0.001) were significantly higher among 24/7 BI compared with PI. The APACHE observed/expected ratios (odds ratio [OR]; 95% confidence interval [CI]) for ICU mortality (0.62; 0.58-0.67) vs. (0.53; 0.46-0.61) and Hospital mortality (0.95; 0.57-1.48) vs. (0.77; 0.70-0.84) were significantly different for 24/7 BI compared with PI. Multivariate mixed models that adjusted for confounders demonstrated significantly greater odds of (OR; 95% CI) ICU mortality (1.58; 1.28-1.93), Hospital mortality (1.52; 1.33-1.73), complications (1.55; 1.18-2.04), ICU LOS [3.14 vs. 2.59 (1.25; 1.19-1.51)], and Hospital LOS [9.05 vs. 7.31 (1.23; 1.21-1.25)] among 24/7 BI when compared with PI. Sensitivity analyses adjusting for ICU admission within 24 h of hospital admission, receiving active ICU treatments, nighttime admission, sepsis, and highest third acute physiology score indicated significantly higher odds for 24/7 BI compared with PI. Conclusion: Our comparison demonstrated that TCC delivery model with PI provided high-quality care with significant positive effects on outcomes. This suggests that TCC delivery models have broad-ranging applicability and benefits in routine critical care, thus necessitating progressive research in this direction.

Prognostic Language in Critical Neurologic Illness: A Multicenter Mixed-Methods Study

BACKGROUND AND OBJECTIVES

There are no evidence-based guidelines for discussing prognosis in critical neurologic illness, but in general, experts recommend that clinicians communicate prognosis using estimates, such as numerical or qualitative expressions of risk. Little is known about how real-world clinicians communicate prognosis in critical neurologic illness. Our primary objective was to characterize prognostic language clinicians used in critical neurologic illness. We additionally explored whether prognostic language differed between prognostic domains (e.g., survival, cognition).

METHODS

We conducted a multicenter cross-sectional mixed-methods study analyzing deidentified transcripts of audio-recorded clinician-family meetings for patients with neurologic illness requiring intensive care (e.g., intracerebral hemorrhage, traumatic brain injury, severe stroke) from 7 US centers. Two coders assigned codes for prognostic language type and domain of prognosis to each clinician prognostic statement. Prognostic language was coded as probabilistic (estimating the likelihood of an outcome occurring, e.g., "80% survival"; "She'll probably survive") or nonprobabilistic (characterizing outcomes without offering likelihood; e.g., "She may not survive"). We applied univariate and multivariate binomial logistic regression to examine independent associations between prognostic language and domain of prognosis.

RESULTS

We analyzed 43 clinician-family meetings for 39 patients with 78 surrogates and 27 clinicians. Clinicians made 512 statements about survival (median 0/meeting [interquartile range (IQR) 0-2]), physical function (median 2 [IQR 0-7]), cognition (median 2 [IQR 0-6]), and overall recovery (median 2 [IQR 1-4]). Most statements were nonprobabilistic (316/512 [62%]); 10 of 512 prognostic statements (2%) offered numeric estimates; and 21% (9/43) of family meetings only contained nonprobabilistic language. Compared with statements about cognition, statements about survival (odds ratio [OR] 2.50, 95% CI 1.01-6.18, p = 0.048) and physical function (OR 3.22, 95% 1.77-5.86, p < 0.001) were more frequently probabilistic. Statements about physical function were less likely to be uncertainty-based than statements about cognition (OR 0.34, 95% CI 0.17-0.66, p = 0.002).

DISCUSSION

Clinicians preferred not to use estimates (either numeric or qualitative) when discussing critical neurologic illness prognosis, especially when they discussed cognitive outcomes. These findings may inform interventions to improve prognostic communication in critical neurologic illness.

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.

A Constructivist Grounded Theory of Staff Experiences Relating to Early Mobilisation of Mechanically Ventilated Patients in Intensive Care

Early mobilisation of mechanically ventilated patients has been suggested to be effective in mitigating muscle weakness, yet it is not a common practice. Understanding staff experiences is crucial to gain insights into what might facilitate or hinder its implementation. In this constructivist grounded theory study, data from two Scottish intensive care units were collected to understand healthcare staff experiences relating to early mobilisation in mechanical ventilation. Data included observations of mobilisation activities, individual staff interviews and two focus groups with multidisciplinary staff. Managing Risks emerged as the core category and was theorised using the concept of risk. The middle-range theory developed in this study suggests that the process of early mobilisation starts by staff defining patient status and includes a process of negotiating patient safety, which in turn enables performing accountable mobilisation within the dynamic context of an intensive care unit setting.

Variability of Prognostic Communication in Critically Ill Neurologic Patients: A Pilot Multicenter Mixed-Methods Study

IMPORTANCE

Withdrawal-of-life-sustaining treatments (WOLST) rates vary widely among critically ill neurologic patients (CINPs) and cannot be solely attributed to patient and family characteristics. Research in general critical care has shown that clinicians prognosticate to families with high variability. Little is known about how clinicians disclose prognosis to families of CINPs, and whether any associations exist with WOLST.

OBJECTIVES

Primary: to demonstrate feasibility of audio-recording clinician-family meetings for CINPs at multiple centers and characterize how clinicians communicate prognosis during these meetings. Secondary: to explore associations of 1) clinician, family, or patient characteristics with clinicians' prognostication approaches and 2) prognostication approach and WOLST.

DESIGN SETTING AND PARTICIPANTS

Forty-three audio-recorded clinician-family meetings during which prognosis was discussed from seven U.S. centers for 39 CINPs with 88 family members and 27 clinicians.

MAIN OUTCOMES AND MEASURES

Two investigators qualitatively coded transcripts using inductive methods (inter-rater reliability > 80%) to characterize how clinicians prognosticate. We then applied univariate and multivariable multinomial and binomial logistic regression.

RESULTS

Clinicians used four distinct prognostication approaches: Authoritative (21%; recommending treatments without discussing values and preferences); Informational (23%; disclosing just the prognosis without further discussions); advisory (42%; disclosing prognosis followed by discussion of values and preferences); and responsive (14%; eliciting values and preferences, then disclosing prognosis). Before adjustment, prognostication approach was associated with center (p < 0.001), clinician specialty (neurointensivists vs non-neurointensivists; p = 0.001), patient age (p = 0.08), diagnosis (p = 0.059), and meeting length (p = 0.03). After adjustment, only clinician specialty independently predicted prognostication approach (p = 0.027). WOLST decisions occurred in 41% of patients and were most common under the advisory approach (56%). WOLST was more likely in older patients (p = 0.059) and with more experienced clinicians (p = 0.07). Prognostication approach was not independently associated with WOLST (p = 0.198).

CONCLUSIONS AND RELEVANCE

It is feasible to audio-record sensitive clinician-family meetings about CINPs in multiple ICUs. We found that clinicians prognosticate with high variability. Our data suggest that larger studies are warranted in CINPs to examine the role of clinicians' variable prognostication in WOLST decisions.