Trends in the use and cost of antipsychotics among older adults from 2007 to 2013: a repeated cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Recently, several new atypical antipsychotic agents have been introduced in Ontario, and regulatory warnings have been issued regarding use of atypical antipsychotics in older adults. We sought to establish the impact of newer atypical antipsychotics on prescribing rates and costs. METHODS: We performed a population-based cross-sectional study of Ontario adults aged 65 years or more using atypical antipsychotics from Jan. 1, 2007, to Mar. 31, 2013. These people have universal access to publicly funded drugs through the Ontario Health Insurance Plan and the Ontario Drug Benefit. We conducted time-series analysis to assess the impact of the introduction of new atypical antipsychotics on rates of use of atypical antipsychotics and associated expenditures. RESULTS: Rates of atypical antipsychotic use increased following the introduction of new agents in 2009, from 27.6 users per 1000 older adults in the third quarter of 2009 to 29.1 users per 1000 older adults at the end of the study period (p = 0.04). Although prescribing rates for the newer atypical agents (paliperidone, ziprasidone and aripiprazole) remained low relative to their older counterparts (risperidone, olanzapine and quetiapine), rates of aripiprazole use rose to 1.0 user per 1000 older adults by the end of the study period. The proportion of prescriptions that were for brand-name agents fell from 57.5% in the second quarter of 2007 to 6.1% in the second quarter of 2009, and then rose to 11.7% by the end of the study period. By the first quarter of 2013, newer atypical antipsychotic agents were used by 4.4% of atypical antipsychotic users but accounted for 14.1% ($1.2 million of $8.5 million) of atypical antipsychotic expenditures. INTERPRETATION: Although the overall prevalence of use of new atypical antipsychotic agents remains low, their introduction has led to increased prescribing of this class of drugs in older adults. Given the potential cost implications, further study of these trends would be prudent.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".