282 A Time to Wean: An Audit on Benzodiazepine and Z-drug Use Amongst Patients Attending a Geriatric Ambulatory Care Day Hospital
Bibliographic record
Abstract
Abstract Background Benzodiazepine prescription is common among the Irish patient cohort. 23% of medical card holders have been prescribed a benzodiazepine or Z-drug, with a third of these being for a period longer than three months. This is despite these drugs being associated with addiction, falls, cognitive and psychomotor impairment, mood disorder, sleep automatism and drug interactions. We performed an audit looking at the repeat prescriptions of patients attending a geriatric day hospital. Methods The repeat prescriptions of all patients currently enrolled at a day hospital were analysed for benzodiazepines or Z-drugs. Medical records were then analysed to look for indication and whether these patients were currently attending psychiatric services. Subsequent to this, notices were placed in the patient consult room in direct line of sight of the registrar reminding them to consider weaning these drugs and detailing the negative side effects and guidelines for weaning from the Canadian National Pain Centre. Results 59 patients were enrolled at the day hospital when the audit was performed. 11 (19%) had either a benzodiazepine or Z-drug as part of their repeat prescription (benzodiazepine-5, Z-drug-5, both-1). The most common benzodiazepines prescribed were diazepam and clonazepam (2 patients on each). Of those prescribed a benzodiazepine, none were currently being weaned. Of those on benzodiazepines, 4 of 6 had a documented psychiatric diagnosis, and 1 of 6 had documented that they were currently attending psychiatric services. A re-audit three months later showed no change in those prescribed benzodiazepines (5/59), and a non-significant increase in those on Z-drugs (9/59, p=0.26). Conclusion This audit showed a significant number of patients attending our day hospital are being prescribed long term benzodiazepines or Z-drugs, and highlights that this setting is an opportune time and place to establish a supported program to wean people off these medications.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".