Workforce, Workload, and Burnout in Critical Care Organizations: Survey Results and Research Agenda*
Bibliographic record
Abstract
OBJECTIVES: This report provides analyses and perspective of a survey of critical care workforce, workload, and burnout among the intensivists and advanced practice providers of established U.S. and Canadian critical care organizations and provides a research agenda. DESIGN: A 97-item electronic survey questionnaire was distributed to the leaders of 27 qualifying organizations. SETTING: United States and Canada. PARTICIPANTS: Leaders of critical care organizations in the United States and Canada. INTERVENTIONS: None. DATA SYNTHESIS AND MAIN RESULTS: We received 23 responses (85%). The critical care organization survey recorded substantial variability of most organizational aspects that were not restricted by the critical care organization definition or regulatory mandates. The most common physician staffing model was a combination of full-time and part-time intensivists. Approximately 80% of critical care organizations had dedicated advanced practice providers that staffed some or all their ICUs. Full-time intensivists worked a median of 168 days (range 42-192 d) in the ICU (168 shifts = 24 7-d wk). The median shift duration was 12 hours (range, 7-14 hr), and the median number of consecutive shifts allowed was 7 hours (range 7-14 hr). More than half of critical care organizations reported having burnout prevention programs targeted to ICU physicians, advanced practice providers, and nurses. CONCLUSIONS: The variability of current approaches suggests that systematic comparative analyses could identify best organizational practices. The research agenda for the study of critical care organizations should include studies that provide insights regarding the effects of the integrative structure of critical care organizations on outcomes at the levels of our patients, our workforce, our work practices, and sustainability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".