Antipsychotic use in the elderly: shifting trends and increasing costs
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to assess trends in utilization and costs of antipsychotic drugs among a population of older adults over time, with respect to the prevalence of users, shifts in prescribing patterns, and related financial implications. DESIGN: Cross-sectional time series of quarterly and annual antipsychotic utilization and cost were obtained from administrative databases for calendar years 1993 through 2002. SETTING AND PARTICIPANTS: A population-based study of more than 1.4 million residents of the province of Ontario aged 65 years or older. MEASUREMENTS: Data sources used included the Ontario Drug Benefits (ODB) database and Statistics Canada census data. RESULTS: The prevalence of antipsychotic users increased by 34.8% over the study period from 2.2% at the beginning of 1993 to 3.0% of the elderly at the end of 2002 (p < 0.01). This was associated with a 749% increase in total cost (from $3.7 million in 1993 to $31.4 million in 2002; p < 0.01). The atypical antipsychotics, which were not available in 1993, made up 82.5% of the antipsychotics dispensed and 95.2% of costs in 2002. CONCLUSIONS: The modest increase in antipsychotic prevalence in the elderly over the last ten years has been associated with a substantial increase in cost, with a significant shift towards use of the atypical antipsychotics. As the atypical antipsychotics are increasingly used for patients with dementia, which is becoming more prevalent in the aging population, an understanding of the benefits of these medications must be balanced with a detailed understanding of the material and financial implications.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".