Computerized physician order entry of diagnostic tests in an intensive care unit is associated with improved timeliness of service
Bibliographic record
Abstract
OBJECTIVE: To measure the effect of computerized physician order entry on timeliness of urgent laboratory and imaging tests. DESIGN: Before-after. SETTING: Eleven-bed medical-surgical intensive care unit in a tertiary teaching hospital. PATIENTS: All patients who had "stat" laboratory or imaging tests ordered during each of two 1-month periods 10 months before and 2 months after introducing computerized physician order entry. INTERVENTIONS: Introduction of computerized physician order entry. MEASUREMENTS AND MAIN RESULTS: After computerized physician order entry was introduced, median time from ordering to obtaining laboratory specimens decreased from 77 to 21.5 mins, median time from ordering to laboratory result being reported decreased from 148 to 74 mins, and median time from ordering to imaging completed decreased from 96.5 to 29.5 mins. CONCLUSIONS: Introduction of computerized physician order entry for ordering "stat" tests in an intensive care unit is associated with improved timeliness of these tests.
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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 | 0.002 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".