Shifting sands: assessing the balance between public, private not‐for‐profit and private for‐profit physical therapy delivery in Ontario, Canada
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The vast majority of health services within Canada's single payer universal health care system are publicly funded. Despite the highly political and controversial emphasis placed on public funding, the structure of delivery within this health care system does not require public ownership. In this research, we developed a conceptual framework for analysing the public and private mix of physical therapy (PT) delivery in the province of Ontario. We then applied this framework to examine the shifts in employment structure of physical therapists (PTs) in Ontario. METHODS: A two-phased health policy case study methodology was used. In the first phase, we reviewed publicly available documents and conducted a series of 30 key informant interviews in order to develop our framework. In the second phase, we applied the framework and performed secondary analysis of the provincial PT registration database to assess change in practice setting between 1996 and 2002. RESULTS: We identified nine models of delivery that fall into three categories of ownership structure: (a) public; (b) private not-for-profit; and (c) private for-profit. During the six-year period between 1996 and 2002, the relative proportion of PTs employed in the not-for-profit sector decreased (from 59.6% to 54.8%) whereas the share in the for-profit sector grew (from 40.4% to 45.2%). CONCLUSIONS: The shifting balance in the structure of delivery may be transforming how PT services are provided in the province. Private for-profit providers appear to be increasing their market share; however, the outcomes relative to this shift has yet to be fully explored. Further policy and health services research is warranted to more fully understand the consequences of this shift on variables such as professional autonomy, access, cost and quality of services across Canada, but also within similar and dissimilar international jurisdictions.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| 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".