Funding models and medical dominance in interdisciplinary primary care teams: qualitative evidence from three Canadian provinces
Bibliographic record
Abstract
Abstract Background Primary care in Canada is the first point of entry for patients needing specialized services, the fundamental source of care for those living with chronic illness, and the main supplier of preventive services. Increased pressures on the system lead to changes such as an increased reliance on interdisciplinary teams, which are advocated to have numerous advantages. The functioning of teams largely depends on inter-professional relationships that can be supported or strained by the financial arrangements within teams. We assess which types of financial environments perpetuate and which reduce the challenge of medical dominance. Methods Using qualitative interview data from 19 interdisciplinary teams/networks in three Canadian provinces, as well as related policy documents, we develop a typology of financial environments along two dimensions, financial hierarchy and multiplicity of funding sources. A financial hierarchy is created when the incomes of some providers are a function of the incomes of other providers. A multiplicity of funding sources is created when team funding is provided by several funders and a team faces multiple lines of accountability. Results We argue that medical dominance is perpetuated with higher degrees of financial hierarchy and higher degrees of multiplicity. We show that the financial environments created in the three provinces have not supported a reduction in medical dominance. The longstanding Community Health Centre model, however, displays the least financial hierarchy and the least multiplicityâ an environment least fertile for medical dominance. Conclusions The functioning of interdisciplinary primary care teams can be negatively affected by the unique positioning of the medical profession. The financial environment created for teams is an important consideration in policy development, as it plays an important role in establishing inter-professional relationships. Policies that reduce financial hierarchies and funding multiplicities are optimal in this regard.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.153 | 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".