Bibliographic record
Abstract
Aim To know the out-patient prescription quality in a 3A grade hospital,so as to provide the basis for the intervention medication.Methods With a random sampling method,out-patient prescriptions among four sections in the 3rd,4th quarter of 2008 were selected and evaluated,in accordance with the management prescription.At the same time,30 patients were randomly selected every quarter over the same period for care indicators,and relevant statistical data were analyzed.Results Outpatient prescriptions were well written specification,with a pass rate of 20%,39.7%.Non-standard prescriptions were mainly over-prescription,diagnosis is not standardized,the amount of usage is not correct,repeat drug use and irrational drug choices.Conclusion Function of the HIS system setting should be improved.We shoud wake,in-depth study and implementation of relevant laws and regulations,the requirements of medical norms to continuously improve the quality of outpatient prescriptions,so as to achieve the purpose of rational drug use.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".