Review of a Large Clinical Series: Structure, Process, and Outcome of all Intensive Care Units Within the Province of British Columbia, Canada
Bibliographic record
Abstract
PURPOSE: To describe the total and regional capacity for critical care in British Columbia (BC), Canada, and to describe regional variation in number of intensive care units (ICUs), size of ICUs, length of ICU stay, ICU occupancy, key processes of critical care, and hospital mortality for ICU patients in B.C. METHODS: In this cross-sectional study, we used retrospectively collected data from all patients admitted to an ICU in BC between April 1, 1998, and March 31, 1999, and responses to a survey about organizational factors for all ICUs in BC that was done in 2001 and updated in 2008. RESULTS: The number of ICU beds in each geographic region in BC is inversely related to the population density and population growth within those regions. In addition, the distribution of ICU beds does not match the distribution of specialized and high-risk clinical services. There is wide variation by geographic region and by size of ICU in physician and nurse staffing, physician model of care, availability and participation of respiratory therapists, and other support services in clinical care and in reported use of clinical practice guidelines. CONCLUSION: Variation and lack of availability of key processes for care of critically ill patients in this population identifies opportunities for knowledge translation and systematic improvement including regionalization of care.
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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 | 0.004 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.010 | 0.025 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".