Cost trends of potentially inappropriate medications among older adults between 2012 and 2021 in Quebec, Canada: a population-based repeated cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Potentially inappropriate medications (PIMs) are frequent in older adults, contributing to hospitalizations, adverse events, and healthcare burden. We aimed to estimate direct PIM cost trends from 2012 to 2021 among older women and men in Quebec, Canada. METHODS: Using medico-administrative data, we assessed direct costs paid by the public insurer (medication cost and professional fee, excluding out-of-pocket payments by individuals) of PIMs claimed by adults ≥65 years covered by the public drug plan. Costs for 16 PIM classes, identified using 2015 and 2019 Beers criteria, were calculated and stratified by sex and age group (65-74, 75-84, ≥85) for each fiscal year. We assessed the proportion of PIMs among all medication expenditures. We computed average costs/enrollee and usage prevalence for the costliest PIM classes. Trends were estimated using univariate linear regression with 95% confidence intervals. RESULTS: We found a non-statistically significant decrease in total PIM claim costs, from $206 million in 2012 to $186 million in 2021 (trend: -2.9[-17.4; 11.6]), representing 5.4% of medication expenditures for adults ≥65 in 2021. The reduction in total costs was more accentuated in women, whose annual costs were higher than those of men in all age groups. Average cost/enrollee decreased from $179 to $119 (trend: -7[-19; 5]), with a drop from $216 to $142 for women and $132 to $92 for men. Costs/enrollee were higher in 75-84 and ≥85 age groups. Costliest PIM classes included proton-pump inhibitors, benzodiazepines, antipsychotics, antidepressants, estrogens (women), and hypoglycemic agents (men). Cost trends did not always follow prevalence trends for these PIM classes. CONCLUSION: PIM costs among older adults slightly decreased from 2012 to 2021. Appropriate prescribing and deprescribing appear crucial for reducing these costs. Further research should focus on estimating the societal impact and the cost-effectiveness analysis of deprescribing initiatives and other regulatory measures.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 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".