Process Optimization to Improve Immunosuppressant Drug Testing Turnaround Time
Bibliographic record
Abstract
OBJECTIVES: Timely reporting of immunosuppressant (ISP) drug level results is needed for transplant patient management. This study characterized the local ISP testing process, identified bottlenecks and implemented process improvements to meet turnaround time requirements. METHODS: Laboratory information time stamps, direct observation and discussion with staff were used to construct a value stream map of the ISP testing process to identify process bottlenecks. Improvements were implemented to attain the required turnaround time. RESULTS: Baseline performance of the existing ISP process (seven weeks, n = 272 samples) indicated that only 28% of samples were reported by 2:00 pm Major bottlenecks were identified to be the analytical run schedule, instrument delays, difficulty identifying ISP samples at intake, and difficulty collecting specimens. Process changes resulted in a median of 76% samples reported by 2:00 pm CONCLUSIONS: : Adjusting ISP collection and analysis processes improved the laboratory's ability to meet physician requested result reporting time of 2:00 pm.
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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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".