Intravenous albumin utilization audit at a large community hospital
Bibliographic record
Abstract
BACKGROUND: There is a literature gap in terms of albumin utilization practices. METHODS/MATERIALS: We conducted a single-center retrospective observational electronic audit of adult admitted patients who received one or more vials of albumin (5% or 25%) between September 1, 2019 and August 31, 2020 at a large community hospital. The Research Ethics Board approval was obtained. Utilization data identified through the laboratory information system were independently adjudicated by two reviewers and resolved by consensus as appropriate-acceptable, appropriate-may be acceptable, or inappropriate. The primary objective of this audit is to determine the proportion of 5% and 25% intravenous albumin infusions meeting a priori appropriateness criteria for indication. Secondary outcomes include determining the patterns of practice surrounding intravenous albumin use: patient demographics, most responsible diagnosis, location at time of order, clinical outcomes of albumin recipients, and types, volumes, and cost of albumin infused. RESULTS: The mean total albumin administered was 569.2 mL across 456 total recipients (58% male) with a 29% appropriateness rate. This cohort had an in-hospital mortality rate of 38%, with an average of 6 days from first dose of albumin to death. The mean length of stay was 14 days, with a mean intensive care length of stay of 8 days. The purchase cost of inappropriately transfused albumin was CAD $65,538. CONCLUSION: Based on a lack of or an unacceptable indication provided, 71% of patients were inappropriately transfused. Albumin use deviating from guideline recommendations may be contributing to increased healthcare costs, pressure on limited supply, and potential patient harm.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| 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".