From pharmaco-therapy to pharmaco-prevention: trends in prescribing to older adults in Ontario, Canada, 1997-2006
Bibliographic record
Abstract
BACKGROUND: The developed world is undergoing a demographic transition with greater numbers of older adults and higher rates of chronic disease. Most elder care is now provided by primary care physicians, who prescribe the majority of medications taken by these patients. Despite these significant trends, little is known about population-level prescribing patterns to primary care patients aged 65+. METHODS: We conducted a population-based retrospective cohort study to examine 10-year prescribing trends among family physicians providing care to patients aged 65+ in Ontario, Canada. RESULTS: Both crude number of prescription claims and prescription rates (i.e., claims per person) increased dramatically over the 10-year study period. The greatest change was in prescribing patterns for females aged 85+. Dramatic increases were observed in the prescribing of preventive medications, such as those to prevent osteoporosis (+2,347%) and lipid-lowering agents (+697%). And lastly, the number of unique classes of medications prescribed to older persons has increased, with the proportion of older patients prescribed more than 10 classes of medications almost tripling during the study period. CONCLUSIONS: Prescribing to older adults by family physicians increased substantially during the study period. This raises important concerns regarding quality of care, patient safety, and cost sustainability. It is evident that further research is urgently needed on the health outcomes (both beneficial and harmful) associated with these dramatic increases in prescribing rates.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".