Quality improvement opportunities for urine culture follow-up in a tertiary care emergency department: A pilot study
Bibliographic record
Abstract
Institutional quality assurance processes have been developed to address the follow up of abnormal test results ordered in the emergency department (ED). We conducted a health records review at an academic tertiary care ED to understand the process and times taken to follow up post-discharge urine culture results transferred to physicians for review. All patients (age ≥18 years) who were seen and discharged between July 1, 2020 and June 30, 2021 and had a positive urine culture were eligible for inclusion. We randomly selected 100 patients, abstracted follow-up times, and reported descriptive statistics. 65 were initially identified as requiring further follow-up for their culture results. Nearly 80% of these patients required new, additional, or revised antimicrobial therapy. Overall, the mean time from ED discharge to follow-up completion was 3.4 days (SD 2.1 days). The longest contributor was the time for transfer of results from nurses to physicians for review at 1.4 days (SD 1.2 days). We demonstrated considerable delay in the follow-up of urine culture results requiring physician review. Future work should address opportunities for reducing times to follow-up, including semi-automation of benign culture results and capture of key patient demographic information in the electronic medical record.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".