Impact of feedback from pharmacists in reducing antipsychotic polypharmacy in schizophrenia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The objective was to examine effects of active interventions on physician's prescribing of antipsychotic polypharmacy. Prescriptions for patients with schizophrenia at the Centre for Addiction and Mental Health, Canada were collected in 2006 (n = 648) and 2008 (n = 778). During the intervening period, a pharmacist monitored prescriptions with antipsychotic polypharmacy and contacted corresponding prescribers to provide education on risks of polypharmacy. Moreover, educational sessions on polypharmacy were presented to inpatient and outpatient teams. A three-fold decrease in the prevalence of antipsychotic polypharmacy was observed between 2006 (18.3%) and 2008 (6.6%). Thus, active monitoring of prescriptions with educational interventions could reduce antipsychotic polypharmacy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it