Variation in Bed-to-Physician Ratios During Weekday Daytime Hours in ICUs in Australia and New Zealand*
Bibliographic record
Abstract
OBJECTIVES: To determine common "bed-to-physician" ratios during weekday hours across ICUs and assess factors associated with variability in this ratio. DESIGN: Retrospective cohort study. SETTING: All ICUs in Australia/New Zealand that participated in a staffing survey administered in 2017-2018. PATIENTS: ICU admissions from 2016 to 2018. METHODS: We linked survey data with patient-level data. We defined: 1) bed-to-intensivist ratio as the number of usually available ICU beds divided by the number of onsite weekday daytime intensivists; and 2) bed-to-physician ratio as the number of available ICU beds divided by the total number of physicians (intensivists + nonintensivists, including trainees). We calculated the median and interquartile range (IQR) of bed-to-intensivist ratio and bed-to-physician ratios during weekday hours. We assessed variability in each by type of hospital and ICU and by severity of illness of patients, defined by the predicted hospital mortality. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Of the 123 (87.2%) of Australia/New Zealand ICUs that returned staffing surveys, 114 (92.7%) had an intensivist present during weekday daytime hours, and 116 (94.3%) reported at least one nonintensivist physician. The median bed-to-intensivist ratio was 8.0 (IQR, 6.0-11.4), which decreased to a bed-to-physician ratio of 3.0 (IQR, 2.2-4.9). These ratios varied with mean severity of illness of the patients in the unit. The median bed-to-intensivist ratio was highest (13.5) for ICUs with a mean predicted mortality > 2-4%, and the median bed-to-physician ratio was highest (5.7) for ICUs with a mean predicted mortality of > 4-6%. Both ratios decreased and plateaued in ICUs with a mean predicted mortality for patients greater than 8% (median bed-to-intensivist ratio range, 6.8-8.0, and bed-to-physician ratio range of 2.4-2.7). CONCLUSIONS: Weekday bed-to-physician ratios in Australia/New Zealand ICUs are lower than the bed-to-intensivist ratios and have a relatively fixed ratio of less than 3 for units taking care of patients with a higher average severity of illness. These relationships may be different in other countries or healthcare systems.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".