An Environmental Scan of Virtual “Walk-In” Clinics in Canada: Comparative Study
Bibliographic record
Abstract
BACKGROUND: Canada has been slow to implement virtual care relative to other countries. However, in recent years, the availability of on-demand, "walk-in" virtual clinics has increased, with the COVID-19 pandemic contributing to the increased demand and provision of virtual care nationwide. Although virtual care facilitates access to physicians while maintaining physical distancing, there are concerns regarding the continuity and quality of care as well as equitable access. There is a paucity of research documenting the availability of virtual care in Canada, thus hampering the efforts to evaluate the impacts of its relatively rapid emergence on the broader health care system and on individual health. OBJECTIVE: We conducted a national environmental scan to determine the availability and scope of virtual walk-in clinics, cataloging the services they offer and whether they are operating through public or private payment. METHODS: We developed a power term and implemented a structured Google search to identify relevant clinics. From each clinic meeting our inclusion criteria, we abstracted data on the payment model, region of operation, services offered, and continuity of care. We compared clinics operating under different payment models using Fisher exact tests. RESULTS: We identified 18 virtual walk-in clinics. Of the 18 clinics, 10 (56%) provided some services under provincial public insurance, although 44% (8/18) operated on a fully private payment model while an additional 39% (7/18) charged patients out of pocket for some services. The most common supplemental services offered included dermatology (15/18, 83%), mental health services (14/18, 78%), and sexual health (11/18, 61%). Continuity, information sharing, or communication with the consumers' existing primary care providers were mentioned by 22% (4/18) of the clinics. CONCLUSIONS: Virtual walk-in clinics have proliferated; however, concerns about equitable access, continuity of care, and diversion of physician workforce within these models highlight the importance of supporting virtual care options within the context of longitudinal primary care. More research is needed to support quality virtual care and understand its effects on patient and provider experiences and the overall health system utilization and costs.
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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 | 0.005 | 0.001 |
| 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 | 0.002 |
| 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 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".