Patterns of Daily Costs Differ for Medical and Surgical Intensive Care Unit Patients
Bibliographic record
Abstract
RATIONALE: Published studies suggest hospital costs on Day 1 in the intensive care unit (ICU) far exceed those of subsequent days, when costs are relatively stable. Yet, no study stratified patients by ICU type. OBJECTIVES: To determine whether daily cost patterns differ by ICU type. METHODS: We performed a retrospective study of adults admitted to five ICUs (two surgical: quaternary surgical ICU [SICU quat] and quaternary cardiac surgical ICU [CSICU quat]; two medical: tertiary medical ICU [MICU tertiary] and quaternary medical ICU [MICU quat]; one general: community medical surgical ICU [MSICU comm]) at Montefiore Medical Center in the Bronx, New York during 2013. After excluding costs clearly accrued outside the ICU, daily hospital costs were merged with clinical data. Patterns of daily unadjusted costs were evaluated in each ICU using median regression. Generalized estimating equations with first-order autocorrelation were used to identify factors independently associated with daily costs. MEASUREMENTS AND MAIN RESULTS: Unadjusted daily costs were higher on Day 1 than on subsequent days only for surgical ICUs-SICU quat (median [interquartile range], $2,636 [$1,834-$4,282] on Day 1 vs. $1,840 [$1,501-$2,332] on Day 2; P < 0.001) and CSICU quat ($5,166 [$3,136-$9,493] on Day 1 vs. $2,060 [$1,336-$2,528] on Day 2; P < 0.001). In nonsurgical ICUs, there was no change (MICU tertiary P = 0.12) or a small increase (MSICU comm P = 0.03; MICU quat P = 0.01) in cost from Days 1 to 2. After multivariate adjustment, there remained a significant decrease in cost from ICU Day 1 to 2 in surgical units with statistically similar Day 1 and 2 costs for other ICUs. CONCLUSIONS: Higher Day 1 costs are not seen in patients admitted to medical/nonsurgical ICUs.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".