27 Years of retention outcomes for a nine-university primary health care nurse practitioner program in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND: In this article we present 27 years of graduate retention outcomes for a nine-university consortium education program for Primary Health Care Nurse Practitioners (NPs) in Ontario, Canada. We assessed graduate retention in terms of whether graduates are or were practicing: 1) as an NP in Ontario; and 2) as an NP in the geographic region of Ontario where they graduated. It also looks at the geographic distribution of graduates retained as NPs in the province and measures the percentage of graduate NPs who were working in rural and remote areas. METHODS: The authors mined the Ontario nursing public registry to identify how many graduates were, or had been, registered as an NP in Ontario at any time between 1996 and December 2022. The authors used registry data to identify the agency where these NP graduates were practising in the province, and then used a google map interface to identify what percentage were still practising in the university region where they graduated. The Rurality Index of Ontario (RIO), a tool used to measure the level of rurality of Ontario communities in terms of health care access, was used to assess the percentage of NPs grads practising in rural and remote areas. RESULTS: 86.7% of NP graduates were registered as practising NPs in Ontario at the time of the study, or had been registered as practising at some time in the past, with a range of 84% to 91% across the universities. 48% to 79% of graduates registered as currently practising NPs in Ontario remained in the region where they had graduated. Geographic maps show a broad distribution of graduates both within university regions and across the province. 8.6% to 38.9% of graduates were working in rural or remote areas. Graduates from universities in northern Ontario had the highest percentage practising in rural and remote areas. Graduate NP rural practice rates in both northern and southern regions reflected the rural demographics of their regions. CONCLUSIONS: The findings show that the university consortium model supports NP recruitment and retention across the province, including in rural and remote areas. TRIAL REGISTRATION: Not applicable.
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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) | 0.001 | 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 | 0.001 |
| 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".