Impact of two-step urine culture ordering in the emergency department: a time series analysis
Bibliographic record
Abstract
BACKGROUND: Despite evidence against the use of antimicrobials for asymptomatic bacteriuria (ASB), they are frequently prescribed leading to unnecessary adverse events. Prior studies have shown that reducing unnecessary urine cultures (UCs) results in decreased antimicrobial utilisation for ASB. Emergency departments (EDs) submit the largest volume of UCs, yet efforts to limit overordering in this patient setting have had limited success. METHODS: A new two-step model of care for urine collection, using a novel UC collection container, was implemented in the ED of a large community hospital. The collection system contains a preservative allowing UCs to be held at room temperature for up to 48 hours before processing. UCs were collected by front-line staff, but only processed in the microbiology lab if requested by ED physicians after clinical assessment. RESULTS: Following implementation there was a decrease in the percentage of weekly ED visits associated with a processed UC (5.97% vs 4.68%, p<0.001), a decrease in the percentage of monthly ED visits requiring a callback for positive urine culture (1.84% to 1.12%, p<0.001) and a decrease in antimicrobial prescriptions for urinary indication among admitted patients (20.6% to 10.9%, p<0.01). There was a false omission rate of 1.35% (95% CI 0.7% to 2.2%), yet no identified cases of untreated urinary tract infection (UTI), or significant change in repeat ED visits or ED length of stay. CONCLUSIONS: Changing to two-step urine culture ordering in the ED resulted in a decrease in UCs processed, callbacks for positive results and antimicrobial use without evidence of untreated UTIs. This model of care has strong potential to improve the use of hospital resources while minimising detection and inappropriate treatment of ASB.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".