Variation in benzodiazepine and antipsychotic use in people aged 65 years and over in New Zealand.
Bibliographic record
Abstract
AIMS: To examine the variation in the dispensing of antipsychotic and benzodiazepine medicines in the elderly (aged 65+) across New Zealand. METHODS: Data drawn from the New Zealand Pharmaceutical Collection for the New Zealand Atlas of Healthcare Variation was used to establish a regression model to examine dispensing rates by age, gender, district health board (DHB) of domicile and aged residential care usage rates over a 4 year period 2008/09 to 2011/12. RESULTS: On average 24 per 1000 people aged 65+ in New Zealand were dispensed an antipsychotic in any given quarter. Benzodiazepine dispensing rates were even higher, at 109 per 1000 aged 65+. Both rates climbed steeply with age, were higher in females, and had a 1.6 to 1.8 fold variation across DHBs. Rates did not vary significantly with rest home and private hospital residential care usage, but antipsychotic rates appeared related to the use of psychogeriatric and dementia beds. CONCLUSION: Given the evident harms associated with the use of antipsychotic and benzodiazepine medicines in the elderly, and the relatively poor efficacy of antipsychotics in dementia care, prescribing of these medicines should be reassessed. DHBs should examine the causes of the high rates in their area and design interventions to reduce the rates.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".