Trends in nurse practitioners' prescribing to older adults in Ontario, 2000-2010: a retrospective cohort study
Bibliographic record
Abstract
BACKGROUND: Nurse prescribing is a practice that has evolved and will continue to evolve in response to emerging trends, particularly in primary care. The goal of this study was to describe the trends and patterns in medication prescription to adults 65 years of age or older in Ontario by nurse practitioners over a 10-year period. METHODS: We conducted a population-based descriptive retrospective cohort study. All nurse practitioners registered in the Corporate Provider Database between Jan. 1, 2000, and Dec. 31, 2010, were identified. We identified actively prescribing nurse practitioners through linkage of dispensed medications to people aged 65 years or older from the Ontario Drug Benefit database. For comparison, all prescription medications dispensed by family physicians to a similar group were identified. Geographic location was determined based on site of nurse practitioner practice. RESULTS: The number and proportion of actively prescribing nurse practitioners prescribing to older adults increased during the study period, from 44/340 (12.9%) to 888/1423 (62.4%). The number and proportion of medications dispensed for chronic conditions by nurse practitioners increased: in 2010, 9 of the 10 top medications dispensed were for chronic conditions. There was substantial variation in the proportion of nurse practitioners dispensing medication to older adults across provincial Local Health Integration Networks. INTERPRETATION: Prescribing by nurse practitioners to older adults, particularly of medications related to chronic conditions, increased between 2000 and 2010. The integration of nurse practitioners into primary care has not been consistent across the province and has not occurred in relation to population changes and perhaps population needs.
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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 | 0.003 | 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 | 0.001 |
| 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".