Exploring Privatization in Canadian Primary Care: An Environmental Scan of Primary Care Clinics Accepting Private Payment
Bibliographic record
Abstract
Background: Private payment within primary care has not received extensive scrutiny, despite the emergence of "concierge" primary care services.Objective: We conducted an environmental scan to explore the nature of private payment for primary care across Canada.Method: We extracted data from clinic websites on funding models, range of services provided and whether they were independent or part of a chain.We conducted a thematic analysis of service advertisements.Results: We identified 83 private clinics across six provinces, predominately in urban areas.Private payment-only clinics offered the widest range of services and advertisements emphasised timely, comprehensive care.Conclusion: The extent to which these clinics and bundling of primary care with privately paid wellness services impact patients' access to care should be the subject of future research. RésuméContexte : Le paiement privé dans le cadre des soins primaires n' a pas fait l' objet d' un examen minutieux, et ce, malgré l'émergence de services de soins primaires « de conciergerie ».Objectif : Nous avons effectué une analyse environnementale pour explorer la nature du paiement privé des soins primaires au Canada.Méthode : Nous avons extrait, à partir des sites Web des cliniques, des données sur les modèles de financement, sur la gamme de services fournis et sur le type de cliniques, à savoir si elles étaient indépendantes ou faisaient partie d' une chaîne.Nous avons procédé à une analyse thématique des annonces de services offerts.Résultats : Nous avons identifié 83 cliniques privées dans six provinces, principalement dans les zones urbaines.Les cliniques privées payantes offraient la plus large gamme de services et leurs annonces mettaient l' accent sur des soins complets et en temps opportun.Conclusion : La mesure dans laquelle ces cliniques et le regroupement des soins primaires avec des services de bien-être privés ont un impact sur l' accès des patients aux soins devrait faire l' objet de recherches futures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.017 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".